json_data.txt

{'data': {'data': [{'title': 'shift distribution – shiftdistribution.com',
    'paper': 'http://www.shiftdistribution.com/',
    'topic': 'medical distribution shift'},
   {'title': 'ehr foundation models improve robustness in the presence ...',
    'paper': 'https://www.medrxiv.org/content/10.1101/2022.04.15.22273900v1.full',
    'topic': 'medical distribution shift'},
   {'title': 'maintaining fairness across distribution shift: do we have ...',
    'paper': 'https://montrealethics.ai/maintaining-fairness-across-distribution-shift-do-we-have-viable-solutions-for-real-world-applications/',
    'topic': 'medical distribution shift'},
   {'title': 'characterizing the value of information in medical notes',
    'paper': 'https://aclanthology.org/2020.findings-emnlp.187',
    'topic': 'medical distribution shift'},
   {'title': 'assessing group-level gender bias in professional evaluations',
    'paper': 'https://aclanthology.org/2022.gebnlp-1.11.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'ziad obermeyer - acl anthology',
    'paper': 'https://aclanthology.org/people/z/ziad-obermeyer/',
    'topic': 'medical distribution shift'},
   {'title': 'preventing failures due to dataset shift: learning predictive ...',
    'paper': 'http://proceedings.mlr.press/v89/subbaswamy19a/subbaswamy19a.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'enhancing unsupervised domain adaptation via semantic ...',
    'paper': 'https://www.ijcai.org/proceedings/2022/0426.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'forecasting patient outcomes in kidney exchange - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0701.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'distributed patient scheduling in hospitals - ijcai',
    'paper': 'https://www.ijcai.org/Proceedings/03/Papers/175.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'a fine-grained analysis of distribution shifts - openreview',
    'paper': 'https://openreview.net/pdf?id=AVTfiZgV64X',
    'topic': 'medical distribution shift'},
   {'title': '[2110.14019] reliable and trustworthy machine learning for health ...',
    'paper': 'https://ar5iv.labs.arxiv.org/html/2110.14019',
    'topic': 'medical distribution shift'},
   {'title': 'arxiv:1910.00199v3 [cs.cv] 10 feb 2021',
    'paper': 'https://arxiv.org/pdf/1910.00199',
    'topic': 'medical distribution shift'},
   {'title': 'frequency dropout: feature-level regularization via randomized filtering',
    'paper': 'https://arxiv.org/abs/2209.09844',
    'topic': 'medical distribution shift'},
   {'title': 'q-net: query-informed few-shot medical image segmentation',
    'paper': 'https://arxiv.org/abs/2208.11451',
    'topic': 'medical distribution shift'},
   {'title': 'fusion: fully unsupervised test-time stain adaptation via fused normalization statistics',
    'paper': 'https://arxiv.org/abs/2208.14206',
    'topic': 'medical distribution shift'},
   {'title': 'domain adaptation under open set label shift',
    'paper': 'https://arxiv.org/abs/2207.13048',
    'topic': 'medical distribution shift'},
   {'title': 'revisiting inlier and outlier specification for improved out-of-distribution detection',
    'paper': 'https://arxiv.org/abs/2207.05286',
    'topic': 'medical distribution shift'},
   {'title': 'unsupervised domain adaptation using feature disentanglement and gcns for medical image classification',
    'paper': 'https://arxiv.org/abs/2206.13123',
    'topic': 'medical distribution shift'},
   {'title': 'single-domain generalization in medical image segmentation via test-time adaptation from shape dictionary',
    'paper': 'https://arxiv.org/abs/2206.14467',
    'topic': 'medical distribution shift'},
   {'title': 'distributional gaussian processes layers for out-of-distribution detection',
    'paper': 'https://arxiv.org/abs/2206.13346',
    'topic': 'medical distribution shift'},
   {'title': 'certifying some distributional fairness with subpopulation decomposition',
    'paper': 'https://arxiv.org/abs/2205.15494',
    'topic': 'medical distribution shift'},
   {'title': 'fedilc: weighted geometric mean and invariant gradient covariance for federated learning on non-iid data',
    'paper': 'https://arxiv.org/abs/2205.09305',
    'topic': 'medical distribution shift'},
   {'title': 'dltta: dynamic learning rate for test-time adaptation on cross-domain medical images',
    'paper': 'https://arxiv.org/abs/2205.13723',
    'topic': 'medical distribution shift'},
   {'title': 'fraug: tackling federated learning with non-iid features via representation augmentation',
    'paper': 'https://arxiv.org/abs/2205.14900',
    'topic': 'medical distribution shift'},
   {'title': 'cd$^2$-pfed: cyclic distillation-guided channel decoupling for model personalization in federated learning',
    'paper': 'https://arxiv.org/abs/2204.03880',
    'topic': 'medical distribution shift'},
   {'title': 'direct mapping from pet coincidence data to proton-dose and positron activity using a deep learning approach',
    'paper': 'https://arxiv.org/abs/2204.13905',
    'topic': 'medical distribution shift'},
   {'title': 'rood-mri: benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in mri',
    'paper': 'https://arxiv.org/abs/2203.06060',
    'topic': 'medical distribution shift'},
   {'title': 'efficient fully distributed federated learning with adaptive local links',
    'paper': 'https://arxiv.org/abs/2203.12281',
    'topic': 'medical distribution shift'},
   {'title': 'larmor frequency shift from magnetized cylinders with arbitrary orientation distribution',
    'paper': 'https://arxiv.org/abs/2203.01191',
    'topic': 'medical distribution shift'},
   {'title': 'biomechanical lower limb model to predict patellar position alteration after medial open wedge high tibial osteotomy',
    'paper': 'https://arxiv.org/abs/2203.16903',
    'topic': 'medical distribution shift'},
   {'title': 'unsupervised domain adaptation for cross-modality retinal vessel segmentation via disentangling representation style transfer and collaborative consistency learning',
    'paper': 'https://arxiv.org/abs/2201.04812',
    'topic': 'medical distribution shift'},
   {'title': 'comparison of measurement systems for assessing number- and mass-based particle filtration efficiency',
    'paper': 'https://arxiv.org/abs/2201.12446',
    'topic': 'medical distribution shift'},
   {'title': 'multi-domain balanced sampling improves out-of-distribution generalization of chest x-ray pathology prediction models',
    'paper': 'https://arxiv.org/abs/2112.13734',
    'topic': 'medical distribution shift'},
   {'title': 'specificity-preserving federated learning for mr image reconstruction',
    'paper': 'https://arxiv.org/abs/2112.05752',
    'topic': 'medical distribution shift'},
   {'title': 'mitigating domain shift in ai-based tuberculosis screening with unsupervised domain adaptation',
    'paper': 'https://arxiv.org/abs/2111.04893',
    'topic': 'medical distribution shift'},
   {'title': 'reliable and trustworthy machine learning for health using dataset shift detection',
    'paper': 'https://arxiv.org/abs/2110.14019',
    'topic': 'medical distribution shift'},
   {'title': 'natural attribute-based shift detection',
    'paper': 'https://arxiv.org/abs/2110.09276',
    'topic': 'medical distribution shift'},
   {'title': 'dispensed transformer network for unsupervised domain adaptation',
    'paper': 'https://arxiv.org/abs/2110.14944',
    'topic': 'medical distribution shift'},
   {'title': 'adapt to adaptation: learning personalization for cross-silo federated learning',
    'paper': 'https://arxiv.org/abs/2110.08394',
    'topic': 'medical distribution shift'},
   {'title': 'distributionally robust multi-output regression ranking',
    'paper': 'https://arxiv.org/abs/2109.12803',
    'topic': 'medical distribution shift'},
   {'title': 'unsupervised domain adaptation in semantic segmentation based on pixel alignment and self-training',
    'paper': 'https://arxiv.org/abs/2109.14219',
    'topic': 'medical distribution shift'},
   {'title': 'the impact of domain shift on left and right ventricle segmentation in short axis cardiac mr images',
    'paper': 'https://arxiv.org/abs/2109.13230',
    'topic': 'medical distribution shift'},
   {'title': 'a study of the multi-agent benefit distribution model in the transformation of medical science and technology achievements',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3340037.3340038',
    'topic': 'medical distribution shift'},
   {'title': 'research of selection of distribution in the tasks of the regional system of medical prevention',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3388984.3390873',
    'topic': 'medical distribution shift'},
   {'title': 'comparative study of mutualisation scenarios for distribution of non-medical products',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3286606.3286828',
    'topic': 'medical distribution shift'},
   {'title': 'medical specialists retrieval system using unified medical language system',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3107514.3107521',
    'topic': 'medical distribution shift'},
   {'title': 'distribution scheduling model of multiple temperature refrigerated container system',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3317614.3317628',
    'topic': 'medical distribution shift'},
   {'title': 'phosphorylated physarum polycephalum 14-3-3 modulates the distribution of the p. polycephalum sr-like protein through the arginine/serine-rich domain: p14-3-3 modulates the distribution of psr',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3460238.3460261',
    'topic': 'medical distribution shift'},
   {'title': 'energy exchange model in routed energy distribution network',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3360322.3361017',
    'topic': 'medical distribution shift'},
   {'title': 'a study on the impact of shopping value on loyalty due to the activation of omni-channel based on mobile application by distribution companies',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3317614.3317636',
    'topic': 'medical distribution shift'},
   {'title': 'a phase shifting multiple filter design methodology for lucy-richardson deconvolution of log-mixtures complex rtn tail distribution',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2800986.2800996',
    'topic': 'medical distribution shift'},
   {'title': 'efficient signature scheme using extended chaotic maps for medical imaging records',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3418094.3418144',
    'topic': 'medical distribution shift'},
   {'title': 'maximum domain of attraction of the conditional exponential-weibull distribution',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3274250.3274256',
    'topic': 'medical distribution shift'},
   {'title': 'medical nutrition therapy for adult patients receiving extracorporeal membrane oxygenation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3472813.3472829',
    'topic': 'medical distribution shift'},
   {'title': 'optimization of contract distribution based on multi-objective estimation of distribution algorithm',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3194452.3194455',
    'topic': 'medical distribution shift'},
   {'title': 'open routed energy distribution network based on a concept of energy router in smart grid',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3366030.3366036',
    'topic': 'medical distribution shift'},
   {'title': 'distribution big data technology of active distribution network based on edge computing',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3501409.3501637',
    'topic': 'medical distribution shift'},
   {'title': 'kernel distribution embeddings: universal kernels, characteristic kernels and kernel metrics on distributions',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3291125.3309606',
    'topic': 'medical distribution shift'},
   {'title': 'fisher consistency for prior probability shift',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3122009.3176839',
    'topic': 'medical distribution shift'},
   {'title': 'distribution-level markets under high renewable energy penetration',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3538637.3538846',
    'topic': 'medical distribution shift'},
   {'title': 'an estimation of distribution algorithm based on the natural gradient and the boltzmann distribution',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2739480.2754803',
    'topic': 'medical distribution shift'},
   {'title': 'research on university takeaway o2o distribution mode based on centralized distribution of third-party sub-region',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3404649.3404651',
    'topic': 'medical distribution shift'},
   {'title': 'niching an estimation-of-distribution algorithm by hierarchical gaussian mixture learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3071178.3071283',
    'topic': 'medical distribution shift'},
   {'title': 'the line loss calculation method of active distribution network based on equivalent capacity method',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3331453.3361314',
    'topic': 'medical distribution shift'},
   {'title': 'simulation application for improving the efficiency of new distribution centers',
    'paper': 'https://dl.acm.org/doi/pdf/10.1109/DS-RT.2015.20',
    'topic': 'medical distribution shift'},
   {'title': 'application and effect analysis of series reactive power compensation in low voltage distribution network',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3429536.3429537',
    'topic': 'medical distribution shift'},
   {'title': 'supporting the self-care practices of shift workers',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3282894.3282914',
    'topic': 'medical distribution shift'},
   {'title': 'towards flexible wireless charging for medical implants using distributed antenna system',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3372224.3380899',
    'topic': 'medical distribution shift'},
   {'title': 'multiobjective discrete differential evolution for service restoration in energy distribution systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2908961.2931642',
    'topic': 'medical distribution shift'},
   {'title': 'medical modeling and numerical analysis of thoracoabdominal aortic aneurysm',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3340037.3340048',
    'topic': 'medical distribution shift'},
   {'title': 'tough shift: exploring the complexities of shifting residential electricity use through a casual mobile game',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2793107.2793108',
    'topic': 'medical distribution shift'},
   {'title': 'accessibility analysis of hospitals medical services in urban modernization',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3418094.3418101',
    'topic': 'medical distribution shift'},
   {'title': 'test-time adaptation with calibration of medical image classification nets for label distribution shift',
    'paper': 'https://arxiv.org/pdf/2207.00769.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'performance deterioration of deep neural networks for lesion classification in mammography due to distribution shift: an analysis based on artificially created distribution shift',
    'paper': 'https://doi.org/10.1117/12.2551346',
    'topic': 'medical distribution shift'},
   {'title': 'how reliable are out-of-distribution generalization methods for medical image segmentation?',
    'paper': 'https://arxiv.org/pdf/2109.01668.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'the domain shift problem of medical image segmentation and vendor-adaptation by unet-gan',
    'paper': 'https://arxiv.org/pdf/1910.13681.pdf',
    'topic': 'medical distribution shift'},
   {'title': 'is the trend of increasing use of patient-reported outcome measures in medical device studies the sign of shift towards value-based purchasing in europe?',
    'paper': 'https://doi.org/10.1007/s10198-019-01070-1',
    'topic': 'medical distribution shift'},
   {'title': 'influence of response shift and disposition on patient-reported outcomes may lead to suboptimal medical decisions: a medical ethics perspective',
    'paper': 'https://doi.org/10.1186/s12910-019-0397-3',
    'topic': 'medical distribution shift'},
   {'title': 'impact of shift duration on alertness among air‐medical emergency care clinician shift workers',
    'paper': 'https://doi.org/10.1002/ajim.22956',
    'topic': 'medical distribution shift'},
   {'title': 'vaccine distribution-equity left behind?',
    'paper': 'https://www.ncbi.nlm.nih.gov/pubmed/33512381',
    'topic': 'medical distribution shift'},
   {'title': 'methods of generating submicrometer phase-shift perfluorocarbon droplets for applications in medical ultrasonography',
    'paper': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7604095',
    'topic': 'medical distribution shift'},
   {'title': 'robust machine learning variable importance analyses of ...',
    'paper': 'https://pubmed.ncbi.nlm.nih.gov/29527659/',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'secure and robust machine learning for healthcare ... - core',
    'paper': 'https://core.ac.uk/download/pdf/328760438.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'rethink robustness of deep learning models for medical ...',
    'paper': 'https://aimi.stanford.edu/events/research-meeting/aimi-research-meeting-rethink-robustness-deep-learning-models-medical-image',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'identification of robust deep neural network models of ... - nature',
    'paper': 'https://www.nature.com/articles/s41746-022-00651-4',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robustness of ai-based prognostic and systems health ...',
    'paper': 'https://www.sciencedirect.com/science/article/abs/pii/S1367578821000195',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'scalable few-shot learning of robust biomedical name ...',
    'paper': 'https://aclanthology.org/2021.bionlp-1.3.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'applied medical code mapping with character-based deep ...',
    'paper': 'https://aclanthology.org/2021.naloma-1.2.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'enhancing model robustness and fairness with causality',
    'paper': 'https://aclanthology.org/2021.cinlp-1.3.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'identifying patients with pain in emergency departments ...',
    'paper': 'https://aclanthology.org/U19-1015.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust machine translation evaluation with entailment ...',
    'paper': 'https://aclanthology.org/P09-1034.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'does robustness improve fairness? approaching fairness ...',
    'paper': 'https://aclanthology.org/2021.findings-acl.294.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'on the lack of robust interpretability of neural text classifiers',
    'paper': 'https://aclanthology.org/2021.findings-acl.327.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'supervised machine learning for extractive query based ...',
    'paper': 'https://aclanthology.org/W18-5604.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust benchmarking for machine learning of clinical entity ...',
    'paper': 'http://proceedings.mlr.press/v126/agrawal20a/agrawal20a.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'feature robustness in non-stationary health records:',
    'paper': 'http://proceedings.mlr.press/v106/nestor19a/nestor19a.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'just train twice: improving group robustness without ...',
    'paper': 'http://proceedings.mlr.press/v139/liu21f/liu21f.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'addressing the false negative problem of deep learning ...',
    'paper': 'https://proceedings.mlr.press/v121/cheng20a.html',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'what clinicians want: contextualizing explainable machine ...',
    'paper': 'http://proceedings.mlr.press/v106/tonekaboni19a/tonekaboni19a.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'smoothed geometry for robust attribution - nips papers',
    'paper': 'https://papers.nips.cc/paper/2020/file/9d94c8981a48d12adfeecfe1ae6e0ec1-Paper.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'distilling robust and non-robust features in adversarial ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/8e5e15c4e6d09c8333a17843461041a9-Paper.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'exploring architectural ingredients of adversarially robust ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/2bd7f907b7f5b6bbd91822c0c7b835f6-Paper.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'adversarial training helps transfer learning via better ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/d3aeec875c479e55d1cdeea161842ec6-Paper.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'on single source robustness in deep fusion models',
    'paper': 'https://papers.nips.cc/paper/8728-on-single-source-robustness-in-deep-fusion-models.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'coresets for robust training of neural networks against ...',
    'paper': 'https://papers.nips.cc/paper/2020/file/8493eeaccb772c0878f99d60a0bd2bb3-Paper.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust classification under sample selection bias',
    'paper': 'http://papers.nips.cc/paper/5458-robust-classification-under-sample-selection-bias.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'metric learning for adversarial robustness',
    'paper': 'https://papers.nips.cc/paper/8339-metric-learning-for-adversarial-robustness.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust high-dimensional classification from few positive ...',
    'paper': 'https://www.ijcai.org/proceedings/2022/271',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust high-dimensional classification from few ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0271.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'multimodal attentional neural networks for diagnosis prediction',
    'paper': 'https://www.ijcai.org/proceedings/2019/0823.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'towards adversarially robust deep image denoising - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0211.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'hybrid learning system for large-scale medical image analysis',
    'paper': 'https://www.ijcai.org/proceedings/2022/0824.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'ai-powered posture training: application of machine learning ...',
    'paper': 'https://www.ijcai.org/proceedings/2019/0805.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'certified robustness via randomized smoothing over ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0467.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust interpretable text classification against spurious ...',
    'paper': 'https://www.ijcai.org/proceedings/2022/0616.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust and sparse fuzzy k-means clustering - ijcai',
    'paper': 'https://www.ijcai.org/Proceedings/16/Papers/317.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'carben: composite adversarial robustness benchmark',
    'paper': 'https://www.ijcai.org/proceedings/2022/0851.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust medical image segmentation by adapting neural ...',
    'paper': 'https://openreview.net/pdf?id=tv_pkmFzdC',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'measuring robustness in deep learning based compressive ...',
    'paper': 'https://openreview.net/pdf?id=HqUeGFCQzX5',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'conditional synthetic data generation for robust machine ...',
    'paper': 'https://openreview.net/pdf?id=o4JWdxYTjL8',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust training of recurrent neural networks to handle missing ...',
    'paper': 'https://openreview.net/forum?id=S1jqMb2oM',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'reliable and trustworthy machine learning for ... - nips papers',
    'paper': 'https://openreview.net/pdf?id=hNMOSUxE8o6',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust neural networks are more interpretable for genomics',
    'paper': 'https://openreview.net/pdf/6b9befb80f2336b2c81716f766c4d4572c2fc827.pdf',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust image segmentation quality assessment - openreview',
    'paper': 'https://openreview.net/pdf?id=nyhZXiaotm',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'out of distribution detection and adversarial attacks on deep ...',
    'paper': 'https://openreview.net/forum?id=1iy7rdPCt_',
    'topic': 'Robust Machine Learning Medical'},
   {'title': '[2103.08291] robust machine learning in critical care - arxiv',
    'paper': 'https://arxiv.org/abs/2103.08291',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'secure and robust machine learning for healthcare ... - arxiv',
    'paper': 'https://arxiv.org/pdf/2001.08103',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust machine learning in critical care - arxiv',
    'paper': 'https://arxiv.org/pdf/2103.08291',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'online reflective learning for robust medical image ... - arxiv',
    'paper': 'http://arxiv.org/abs/2207.00476',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'style curriculum learning for robust medical image ... - arxiv',
    'paper': 'https://arxiv.org/abs/2108.00402',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'deep learning models are not robust against noise in clinical ...',
    'paper': 'https://arxiv.org/abs/2108.12242',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'evaluating the robustness of self-supervised learning in ...',
    'paper': 'https://arxiv.org/abs/2105.06986',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'towards to robust and generalized medical image ... - arxiv',
    'paper': 'https://arxiv.org/abs/2108.03823',
    'topic': 'Robust Machine Learning Medical'},
   {'title': "uncertainty estimations methods for a deep learning model to aid in clinical decision-making -- a clinician's perspective",
    'paper': 'https://arxiv.org/abs/2210.00589',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'feddar: federated domain-aware representation learning',
    'paper': 'https://arxiv.org/abs/2209.04007',
    'topic': 'Robust Machine Learning Medical'},
   {'title': '3d ux-net: a large kernel volumetric convnet modernizing hierarchical transformer for medical image segmentation',
    'paper': 'https://arxiv.org/abs/2209.15076',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'stacking ensemble learning in deep domain adaptation for ophthalmic image classification',
    'paper': 'https://arxiv.org/abs/2209.13420',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'identifying differential equations to predict blood glucose using sparse identification of nonlinear systems',
    'paper': 'https://arxiv.org/abs/2209.13852',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust and efficient imbalanced positive-unlabeled learning with self-supervision',
    'paper': 'https://arxiv.org/abs/2209.02459',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'generalizability of adversarial robustness under distribution shifts',
    'paper': 'https://arxiv.org/abs/2209.15042',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'fairness and robustness in anti-causal prediction',
    'paper': 'https://arxiv.org/abs/2209.09423',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'feature selection integrated deep learning for ultrahigh dimensional and highly correlated feature space',
    'paper': 'https://arxiv.org/abs/2209.07011',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'de-identification of french unstructured clinical notes for machine learning tasks',
    'paper': 'https://arxiv.org/abs/2209.09631',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'boxshrink: from bounding boxes to segmentation masks',
    'paper': 'https://arxiv.org/abs/2208.03142',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'rrwavenet: a compact end-to-end multi-scale residual cnn for robust ppg respiratory rate estimation',
    'paper': 'https://arxiv.org/abs/2208.08672',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'geoecg: data augmentation via wasserstein geodesic perturbation for robust electrocardiogram prediction',
    'paper': 'https://arxiv.org/abs/2208.01220',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'adaptive temperature scaling for robust calibration of deep neural networks',
    'paper': 'https://arxiv.org/abs/2208.00461',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'rethinking degradation: radiograph super-resolution via aid-srgan',
    'paper': 'https://arxiv.org/abs/2208.03008',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'an intertwined neural network model for eeg classification in brain-computer interfaces',
    'paper': 'https://arxiv.org/abs/2208.08860',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'machine learning-based eeg applications and markets',
    'paper': 'https://arxiv.org/abs/2208.05144',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'bayesian pseudo labels: expectation maximization for robust and efficient semi-supervised segmentation',
    'paper': 'https://arxiv.org/abs/2208.04435',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'deformation equivariant cross-modality image synthesis with paired non-aligned training data',
    'paper': 'https://arxiv.org/abs/2208.12491',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'federated learning for medical applications: a taxonomy, current trends, challenges, and future research directions',
    'paper': 'https://arxiv.org/abs/2208.03392',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'fast-aid brain: fast and accurate segmentation tool using artificial intelligence developed for brain',
    'paper': 'https://arxiv.org/abs/2208.14360',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'slice-level detection of intracranial hemorrhage on ct using deep descriptors of adjacent slices',
    'paper': 'https://arxiv.org/abs/2208.03403',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'vector-based data improves left-right eye-tracking classifier performance after a covariate distributional shift',
    'paper': 'https://arxiv.org/abs/2208.00465',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'learning from imperfect training data using a robust loss function: application to brain image segmentation',
    'paper': 'https://arxiv.org/abs/2208.04941',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'predicting microsatellite instability and key biomarkers in colorectal cancer from h&e-stained images: achieving sota predictive performance with fewer data using swin transformer',
    'paper': 'https://arxiv.org/abs/2208.10495',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'bpfish: blockchain and privacy-preserving fl inspired smart healthcare',
    'paper': 'https://arxiv.org/abs/2207.11654',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'decorrelative network architecture for robust electrocardiogram classification',
    'paper': 'https://arxiv.org/abs/2207.09031',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'liver segmentation using turbolift learning for ct and cone-beam c-arm perfusion imaging',
    'paper': 'https://arxiv.org/abs/2207.10167',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'online reflective learning for robust medical image segmentation',
    'paper': 'https://arxiv.org/abs/2207.00476',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'representation learning with information theory for covid-19 detection',
    'paper': 'https://arxiv.org/abs/2207.01437',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'suppressing poisoning attacks on federated learning for medical imaging',
    'paper': 'https://arxiv.org/abs/2207.10804',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'advances in prediction of readmission rates using long term short term memory networks on healthcare insurance data',
    'paper': 'https://arxiv.org/abs/2207.00066',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'vector quantisation for robust segmentation',
    'paper': 'https://arxiv.org/abs/2207.01919',
    'topic': 'Robust Machine Learning Medical'},
   {'title': "pose-based tremor classification for parkinson's disease diagnosis from video",
    'paper': 'https://arxiv.org/abs/2207.06828',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'machine learning to predict the antimicrobial activity of cold atmospheric plasma-activated liquids',
    'paper': 'https://arxiv.org/abs/2207.12478',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'towards accurate and robust classification in continuously transitioning industrial sprays with mixup',
    'paper': 'https://arxiv.org/abs/2207.09609',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'identifying the context shift between test benchmarks and production data',
    'paper': 'https://arxiv.org/abs/2207.01059',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'pro-tip: phantom for robust automatic ultrasound calibration by tip detection',
    'paper': 'https://arxiv.org/abs/2206.05962',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'a review of causality for learning algorithms in medical image analysis',
    'paper': 'https://arxiv.org/abs/2206.05498',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'decentralized distributed learning with privacy-preserving data synthesis',
    'paper': 'https://arxiv.org/abs/2206.10048',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'self-supervision on images and text reduces reliance on visual shortcut features',
    'paper': 'https://arxiv.org/abs/2206.07155',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'amos: a large-scale abdominal multi-organ benchmark for versatile medical image segmentation',
    'paper': 'https://arxiv.org/abs/2206.08023',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'from labels to priors in capsule endoscopy: a prior guided approach for improving generalization with few labels',
    'paper': 'https://arxiv.org/abs/2206.05288',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'breast cancer classification using deep learned features boosted with handcrafted features',
    'paper': 'https://arxiv.org/abs/2206.12815',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'cass: cross architectural self-supervision for medical image analysis',
    'paper': 'https://arxiv.org/abs/2206.04170',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'adaptive adversarial training to improve adversarial robustness of dnns for medical image segmentation and detection',
    'paper': 'https://arxiv.org/abs/2206.01736',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'learning underrepresented classes from decentralized partially labeled medical images',
    'paper': 'https://arxiv.org/abs/2206.15353',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'independent evaluation of state-of-the-art deep networks for mammography',
    'paper': 'https://arxiv.org/abs/2206.12407',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust monitoring for medical cyber-physical systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3446913.3460318',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'detection of nasopharyngeal carcinoma using routine medical tests via machine learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3524086.3524102',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'a machine learning approach for medical device classification',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3494193.3494232',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'machine learning for the developing world',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3210548',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'prediction of adverse drug reaction using machine learning and deep learning based on an imbalanced electronic medical records dataset',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3472813.3472817',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'explainability methods for machine learning systems for multimodal medical datasets: research proposal',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3524273.3533925',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'analyzing the robustness of open-world machine learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3338501.3357372',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'validation methods to promote real-world applicability of machine learning in medicine',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3441369.3441372',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'machine learning approaches for extracting genetic medical data information',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3018896.3066906',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'deep learning for medical anomaly detection – a survey',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3464423',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'evaluation of applied machine learning for health misinformation detection via survey of medical professionals on controversial topics in pediatrics',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3472813.3472814',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust i/o-compute concurrency for machine learning pipelines in constrained cyber-physical devices',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3461648.3463842',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'the early detection of subclinical ketosis in dairy cows using machine learning methods',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3055635.3056625',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'text classification of diseases treated by traditional chinese medicine prescription based on machine learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3429889.3429895',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'deep learning in medical imaging: fmri big data analysis via convolutional neural networks',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3219104.3229250',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'multi-layer representation learning for medical concepts',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2939672.2939823',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'a robust framework for accelerated outcome-driven risk factor identification from ehr',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3292500.3330718',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'improving early prognosis of dementia using machine learning methods',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3502433',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'on the need of machine learning as a service for the internet of things',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3109761.3109783',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'federated multi-view learning for private medical data integration and analysis',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3501816',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'federated learning in a medical context: a systematic literature review',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3412357',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'automatic processing of electronic medical records using deep learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3240925.3240961',
    'topic': 'Robust Machine Learning Medical'},
   {'title': "a multi-agent feature selection and hybrid classification model for parkinson's disease diagnosis",
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3433180',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'object detection and classification using machine learning techniques: a comparison of haar cascades and neural networks',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3484824.3484895',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'automatic differentiation in machine learning: a survey',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3122009.3242010',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'an adversarial approach for the robust classification of pneumonia from chest radiographs',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3368555.3384458',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'analysis of machine learning models predicting quality of life for cancer patients',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3444757.3485103',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'diagnosis of methylmalonic acidemia using machine learning methods',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3340997.3341000',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'assuring the machine learning lifecycle: desiderata, methods, and challenges',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3453444',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'bringing machine learning closer to non-experts: proposal of a user-friendly machine learning tool in the healthcare domain',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3486011.3486469',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust machine learning in critical care — software engineering and medical perspectives',
    'paper': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9474414',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'open source robust machine learning software for medical patient data analysis and cloud storage',
    'paper': 'https://doi.org/10.1007/978-3-030-64610-3_104',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust machine learning variable importance analyses of medical conditions for health care spending',
    'paper': 'https://doi.org/10.1111/1475-6773.12848',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'robust machine learning against adversarial samples at test time',
    'paper': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9149002',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'lung cancer prediction using robust machine learning and image enhancement methods on extracted gray-level co-occurrence matrix features',
    'paper': 'https://doi.org/10.3390/app12136517',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'a robust machine learning predictive model for maternal health risk',
    'paper': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9885515',
    'topic': 'Robust Machine Learning Medical'},
   {'title': "robust medical image registration and motion modeling based on machine learning. (le recalage robuste d'images médicales et la modélisation du mouvement basée sur l'apprentissage profond)",
    'paper': 'https://tel.archives-ouvertes.fr/tel-02954033',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'a robust and stable gene selection algorithm based on graph theory and machine learning',
    'paper': 'https://doi.org/10.1186/s40246-021-00366-9',
    'topic': 'Robust Machine Learning Medical'},
   {'title': 'data distribution shifts and monitoring - chip huyen',
    'paper': 'https://huyenchip.com/2022/02/07/data-distribution-shifts-and-monitoring.html',
    'topic': 'clinical distribution shift'},
   {'title': 'shifting the distribution | evidence for population health',
    'paper': 'https://academic.oup.com/book/9251/chapter/155945428',
    'topic': 'clinical distribution shift'},
   {'title': 'principles for tackling distribution shift - youtube',
    'paper': 'https://www.youtube.com/watch?v=QKBh6TmvBaw',
    'topic': 'clinical distribution shift'},
   {'title': 'zachary c. lipton: deep learning under distribution shift',
    'paper': 'https://www.youtube.com/watch?v=WhpZKIra-FQ',
    'topic': 'clinical distribution shift'},
   {'title': 'preventing dataset shift from breaking machine-learning ...',
    'paper': 'https://hal.archives-ouvertes.fr/hal-03293375/file/main.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'adapting event extractors to medical data - acl anthology',
    'paper': 'https://aclanthology.org/2021.eacl-main.258.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'distinguishing clinical sentiment: the importance of domain ...',
    'paper': 'https://aclanthology.org/W19-1915.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'the performance differences of a medical code prediction ...',
    'paper': 'https://aclanthology.org/2022.clinicalnlp-1.10.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'investigating the challenges of temporal relation extraction ...',
    'paper': 'https://aclanthology.org/W18-5607.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'rethinking group-robust algorithms in a label-wise setting',
    'paper': 'https://aclanthology.org/2022.findings-acl.192.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'analyzing dynamic adversarial training data in the limit',
    'paper': 'https://aclanthology.org/2022.findings-acl.18.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'how to leverage the multimodal ehr data for better medical ...',
    'paper': 'https://aclanthology.org/2021.emnlp-main.329.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'gcn with external knowledge for clinical event detection',
    'paper': 'https://aclanthology.org/2021.ccl-1.106.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'examining dataset shift during prospective validation',
    'paper': 'https://proceedings.mlr.press/v149/otles21a/otles21a.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'evaluating domain generalization for survival analysis in ...',
    'paper': 'https://proceedings.mlr.press/v174/pfisterer22a/pfisterer22a.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'understanding clinical collaborations through federated ...',
    'paper': 'https://proceedings.mlr.press/v149/caldas21a/caldas21a.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'domain adaptation under target and conditional shift',
    'paper': 'http://proceedings.mlr.press/v28/zhang13d.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'robust causal inference under covariate shift via worst-case ...',
    'paper': 'http://proceedings.mlr.press/v125/jeong20a/jeong20a.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'what went wrong and when ... - review for neurips paper',
    'paper': 'https://papers.nips.cc/paper/2020/file/08fa43588c2571ade19bc0fa5936e028-Review.html',
    'topic': 'clinical distribution shift'},
   {'title': 'what went wrong and when? instance-wise feature ...',
    'paper': 'https://papers.nips.cc/paper/2020/hash/08fa43588c2571ade19bc0fa5936e028-Abstract.html',
    'topic': 'clinical distribution shift'},
   {'title': 'evaluating model performance under worst-case ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/908075ea2c025c335f4865f7db427062-Paper.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'from predictions to decisions: using l kahead regularization',
    'paper': 'https://papers.nips.cc/paper/2020/file/2adcfc3929e7c03fac3100d3ad51da26-Paper.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'domain generalization via model-agnostic learning of ...',
    'paper': 'https://papers.nips.cc/paper/8873-domain-generalization-via-model-agnostic-learning-of-semantic-features.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'improving robustness against common corruptions by ...',
    'paper': 'https://papers.nips.cc/paper/2020/file/85690f81aadc1749175c187784afc9ee-Paper.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'likelihood ratios for out-of-distribution detection - openreview',
    'paper': 'https://papers.nips.cc/paper/9611-likelihood-ratios-for-out-of-distribution-detection.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'the "moving targets" training algorithm',
    'paper': 'http://papers.nips.cc/paper/233-the-moving-targets-training-algorithm.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'self-supervised adversarial distribution regularization for ...',
    'paper': 'https://www.ijcai.org/proceedings/2021/0431.pdf',
    'topic': 'clinical distribution shift'},
   {'title': "modeling physicians' utterances to explore diagnostic ... - ijcai",
    'paper': 'https://www.ijcai.org/proceedings/2017/0517.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'unsupervised domain adaptation with dual-scheme fusion ...',
    'paper': 'https://www.ijcai.org/proceedings/2020/0455.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'unsupervised cross-modality domain adaptation of ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2018/0096.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'metric learning in optimal transport for domain adaptation',
    'paper': 'https://www.ijcai.org/proceedings/2020/0299.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'truly batch apprenticeship learning with deep successor ...',
    'paper': 'https://www.ijcai.org/proceedings/2019/0819.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'collaborative filtering on ordinal user feedback - ijcai',
    'paper': 'https://www.ijcai.org/Proceedings/13/Papers/449.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'prototypes and production rulest an approach ...',
    'paper': 'https://www.ijcai.org/Proceedings/79-1/Papers/004.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'learning sparse interpretable features for nas scoring ...',
    'paper': 'https://www.ijcai.org/proceedings/2022/0220.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'building text classifiers with minimal supervision - ijcai',
    'paper': 'http://www.ijcai.org/Proceedings/11/Papers/208.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'reliable and trustworthy machine learning for health using ...',
    'paper': 'https://openreview.net/forum?id=hNMOSUxE8o6',
    'topic': 'clinical distribution shift'},
   {'title': 'a benchmark of in-the-wild distribution shift over time - openreview',
    'paper': 'https://openreview.net/pdf?id=F9ENmZABB0',
    'topic': 'clinical distribution shift'},
   {'title': 'hidden in plain sight: subgroup shifts escape ood detection',
    'paper': 'https://openreview.net/forum?id=aZgiUNye2Cz',
    'topic': 'clinical distribution shift'},
   {'title': 'neurips 2021 workshop distshift - openreview',
    'paper': 'https://openreview.net/group?id=NeurIPS.cc/2021/Workshop/DistShift',
    'topic': 'clinical distribution shift'},
   {'title': 'beds-bench: behavior of ehr-models under distributional ...',
    'paper': 'https://openreview.net/pdf?id=IKWYt4w1uDp',
    'topic': 'clinical distribution shift'},
   {'title': 'continual domain incremental learning for chest x-ray ...',
    'paper': 'https://openreview.net/forum?id=tjUEd5OsxuA',
    'topic': 'clinical distribution shift'},
   {'title': 'a benchmark for text quantification learning under ... - openreview',
    'paper': 'https://openreview.net/pdf?id=MndqjaCwQX',
    'topic': 'clinical distribution shift'},
   {'title': 'metashift:adataset of datasets for evaluat',
    'paper': 'https://openreview.net/pdf?id=MTex8qKavoS',
    'topic': 'clinical distribution shift'},
   {'title': 'medshift: identifying shift data for medical dataset curation',
    'paper': 'https://arxiv.org/pdf/2112.13885',
    'topic': 'clinical distribution shift'},
   {'title': 'test-time adaptation with calibration of medical image ... - arxiv',
    'paper': 'http://arxiv.org/abs/2207.00769',
    'topic': 'clinical distribution shift'},
   {'title': 'arxiv:2207.05796v1 [cs.lg] 12 jul 2022',
    'paper': 'https://arxiv.org/pdf/2207.05796',
    'topic': 'clinical distribution shift'},
   {'title': 'distribution shift in airline customer behavior during covid-19',
    'paper': 'https://arxiv.org/abs/2111.14938',
    'topic': 'clinical distribution shift'},
   {'title': 'understanding behavior of clinical models under domain shifts',
    'paper': 'https://arxiv.org/pdf/1809.07806',
    'topic': 'clinical distribution shift'},
   {'title': 'arxiv:2206.15274v1 [eess.iv] 30 jun 2022',
    'paper': 'https://arxiv.org/pdf/2206.15274',
    'topic': 'clinical distribution shift'},
   {'title': 'arxiv:2207.00769v2 [eess.iv] 9 jul 2022',
    'paper': 'https://arxiv.org/pdf/2207.00769',
    'topic': 'clinical distribution shift'},
   {'title': 'robust and efficient medical imaging with self-supervision',
    'paper': 'https://arxiv.org/pdf/2205.09723',
    'topic': 'clinical distribution shift'},
   {'title': 'feather-light fourier domain adaptation in magnetic resonance imaging',
    'paper': 'https://arxiv.org/abs/2208.00474',
    'topic': 'clinical distribution shift'},
   {'title': 'optimal transport features for morphometric population analysis',
    'paper': 'https://arxiv.org/abs/2208.05891',
    'topic': 'clinical distribution shift'},
   {'title': 'distance-based detection of out-of-distribution silent failures for covid-19 lung lesion segmentation',
    'paper': 'https://arxiv.org/abs/2208.03217',
    'topic': 'clinical distribution shift'},
   {'title': 'task-agnostic continual hippocampus segmentation for smooth population shifts',
    'paper': 'https://arxiv.org/abs/2208.03206',
    'topic': 'clinical distribution shift'},
   {'title': 'continual learning for tumor classification in histopathology images',
    'paper': 'https://arxiv.org/abs/2208.03609',
    'topic': 'clinical distribution shift'},
   {'title': 'generalizable and robust deep learning algorithm for atrial fibrillation diagnosis across ethnicities, ages and sexes',
    'paper': 'https://arxiv.org/abs/2207.09667',
    'topic': 'clinical distribution shift'},
   {'title': 'domain-adaptive 3d medical image synthesis: an efficient unsupervised approach',
    'paper': 'https://arxiv.org/abs/2207.00844',
    'topic': 'clinical distribution shift'},
   {'title': 'risk-sensitive reinforcement learning: iterated cvar and the worst path',
    'paper': 'https://arxiv.org/abs/2206.02678',
    'topic': 'clinical distribution shift'},
   {'title': 'three applications of conformal prediction for rating breast density in mammography',
    'paper': 'https://arxiv.org/abs/2206.12008',
    'topic': 'clinical distribution shift'},
   {'title': 'exposing and addressing the fragility of neural networks in digital pathology',
    'paper': 'https://arxiv.org/abs/2206.15274',
    'topic': 'clinical distribution shift'},
   {'title': 'maxstyle: adversarial style composition for robust medical image segmentation',
    'paper': 'https://arxiv.org/abs/2206.01737',
    'topic': 'clinical distribution shift'},
   {'title': 'test-time adaptation with shape moments for image segmentation',
    'paper': 'https://arxiv.org/abs/2205.07983',
    'topic': 'clinical distribution shift'},
   {'title': 'uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology',
    'paper': 'https://arxiv.org/abs/2204.04516',
    'topic': 'clinical distribution shift'},
   {'title': 'on-the-fly test-time adaptation for medical image segmentation',
    'paper': 'https://arxiv.org/abs/2203.05574',
    'topic': 'clinical distribution shift'},
   {'title': 'chexstray: real-time multi-modal data concordance for drift detection in medical imaging ai',
    'paper': 'https://arxiv.org/abs/2202.02833',
    'topic': 'clinical distribution shift'},
   {'title': 'a field of experts prior for adapting neural networks at test time',
    'paper': 'https://arxiv.org/abs/2202.05271',
    'topic': 'clinical distribution shift'},
   {'title': 'a privacy-preserving unsupervised domain adaptation framework for clinical text analysis',
    'paper': 'https://arxiv.org/abs/2201.07317',
    'topic': 'clinical distribution shift'},
   {'title': 'robust scatterer number density segmentation of ultrasound images',
    'paper': 'https://arxiv.org/abs/2201.06143',
    'topic': 'clinical distribution shift'},
   {'title': 'bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees',
    'paper': 'https://arxiv.org/abs/2110.06866',
    'topic': 'clinical distribution shift'},
   {'title': 'quantifying the reproducibility of graph neural networks using multigraph brain data',
    'paper': 'https://arxiv.org/abs/2109.02248',
    'topic': 'clinical distribution shift'},
   {'title': 'memory-aware curriculum federated learning for breast cancer classification',
    'paper': 'https://arxiv.org/abs/2107.02504',
    'topic': 'clinical distribution shift'},
   {'title': 'anatomy of domain shift impact on u-net layers in mri segmentation',
    'paper': 'https://arxiv.org/abs/2107.04914',
    'topic': 'clinical distribution shift'},
   {'title': 'temporal dependencies in feature importance for time series predictions',
    'paper': 'https://arxiv.org/abs/2107.14317',
    'topic': 'clinical distribution shift'},
   {'title': 'intra- and inter-fraction relative range verification in heavy-ion therapy using filtered interaction vertex imaging',
    'paper': 'https://arxiv.org/abs/2106.09090',
    'topic': 'clinical distribution shift'},
   {'title': 'cross-modality brain tumor segmentation via bidirectional global-to-local unsupervised domain adaptation',
    'paper': 'https://arxiv.org/abs/2105.07715',
    'topic': 'clinical distribution shift'},
   {'title': 'more generalizable models for sepsis detection under covariate shift',
    'paper': 'https://arxiv.org/abs/2105.09385',
    'topic': 'clinical distribution shift'},
   {'title': 'out-of-distribution detection in dermatology using input perturbation and subset scanning',
    'paper': 'https://arxiv.org/abs/2105.11160',
    'topic': 'clinical distribution shift'},
   {'title': 'feddg: federated domain generalization on medical image segmentation via episodic learning in continuous frequency space',
    'paper': 'https://arxiv.org/abs/2103.06030',
    'topic': 'clinical distribution shift'},
   {'title': 'multi-institutional collaborations for improving deep learning-based magnetic resonance image reconstruction using federated learning',
    'paper': 'https://arxiv.org/abs/2103.02148',
    'topic': 'clinical distribution shift'},
   {'title': 'spectral decoupling allows training transferable neural networks in medical imaging',
    'paper': 'https://arxiv.org/abs/2103.17171',
    'topic': 'clinical distribution shift'},
   {'title': 'therapeutics data commons: machine learning datasets and tasks for drug discovery and development',
    'paper': 'https://arxiv.org/abs/2102.09548',
    'topic': 'clinical distribution shift'},
   {'title': 'chexternal: generalization of deep learning models for chest x-ray interpretation to photos of chest x-rays and external clinical settings',
    'paper': 'https://arxiv.org/abs/2102.08660',
    'topic': 'clinical distribution shift'},
   {'title': 'computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation',
    'paper': 'https://arxiv.org/abs/2012.10564',
    'topic': 'clinical distribution shift'},
   {'title': 'deeplesionbrain: towards a broader deep-learning generalization for multiple sclerosis lesion segmentation',
    'paper': 'https://arxiv.org/abs/2012.07950',
    'topic': 'clinical distribution shift'},
   {'title': 'federated semi-supervised learning for covid region segmentation in chest ct using multi-national data from china, italy, japan',
    'paper': 'https://arxiv.org/abs/2011.11750',
    'topic': 'clinical distribution shift'},
   {'title': 'transducer adaptive ultrasound volume reconstruction',
    'paper': 'https://arxiv.org/abs/2011.08419',
    'topic': 'clinical distribution shift'},
   {'title': 'multi-coil mri reconstruction challenge -- assessing brain mri reconstruction models and their generalizability to varying coil configurations',
    'paper': 'https://arxiv.org/abs/2011.07952',
    'topic': 'clinical distribution shift'},
   {'title': 'chasing your long tails: differentially private prediction in health care settings',
    'paper': 'https://arxiv.org/abs/2010.06667',
    'topic': 'clinical distribution shift'},
   {'title': 'contrastive cross-site learning with redesigned net for covid-19 ct classification',
    'paper': 'https://arxiv.org/abs/2009.07652',
    'topic': 'clinical distribution shift'},
   {'title': '"name that manufacturer". relating image acquisition bias with task complexity when training deep learning models: experiments on head ct',
    'paper': 'https://arxiv.org/abs/2008.08525',
    'topic': 'clinical distribution shift'},
   {'title': 'adapting event extractors to medical data: bridging the covariate shift',
    'paper': 'https://arxiv.org/abs/2008.09266',
    'topic': 'clinical distribution shift'},
   {'title': 'speed-of-sound imaging by differential phase contrast with angular compounding',
    'paper': 'https://arxiv.org/abs/2007.03156',
    'topic': 'clinical distribution shift'},
   {'title': 'domain adaptation for ultrasound beamforming',
    'paper': 'https://arxiv.org/abs/2007.03096',
    'topic': 'clinical distribution shift'},
   {'title': 'shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains',
    'paper': 'https://arxiv.org/abs/2007.02035',
    'topic': 'clinical distribution shift'},
   {'title': 'probabilistic self-learning framework for low-dose ct denoising',
    'paper': 'https://arxiv.org/abs/2006.00327',
    'topic': 'clinical distribution shift'},
   {'title': 'mask: a flexible framework to facilitate de-identification of clinical texts',
    'paper': 'https://arxiv.org/abs/2005.11687',
    'topic': 'clinical distribution shift'},
   {'title': 'risk projection for time-to-event outcome leveraging summary statistics with source individual-level data',
    'paper': 'https://arxiv.org/abs/2003.01850',
    'topic': 'clinical distribution shift'},
   {'title': 'balancing confidentiality and sharing of genomic and phenotypic data in a clinical research system',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3233547.3233641',
    'topic': 'clinical distribution shift'},
   {'title': 'clinical and non-clinical handovers: designing for critical moments',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2998181.2998333',
    'topic': 'clinical distribution shift'},
   {'title': 'scaling up hci research: from clinical trials to deployment in the wild.',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3411763.3443437',
    'topic': 'clinical distribution shift'},
   {'title': 'research on automatic proofreading method of clinical terminology of traditional chinese medicine',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3358695.3360943',
    'topic': 'clinical distribution shift'},
   {'title': 'huge cohorts, genomics, and clinical data to personalize medicine',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3233547.3233608',
    'topic': 'clinical distribution shift'},
   {'title': "the objective structured clinical examination (osce) in high-fidelity simulations for assessing nursing students' clinical judgment",
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3345120.3345127',
    'topic': 'clinical distribution shift'},
   {'title': 'the objective structured clinical examination for assessing nursing student clinical competency in a high-fidelity simulation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3416797.3416826',
    'topic': 'clinical distribution shift'},
   {'title': 'cohort-based clinical trial retrieval',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3503516.3503529',
    'topic': 'clinical distribution shift'},
   {'title': 'text mining in clinical domain: dealing with noise',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2939672.2939720',
    'topic': 'clinical distribution shift'},
   {'title': 'aggregating semantic information nuggets for answering clinical queries',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2851613.2851694',
    'topic': 'clinical distribution shift'},
   {'title': 'on multi-armed bandit designs for dose-finding clinical trials',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3546258.3546272',
    'topic': 'clinical distribution shift'},
   {'title': 'optimizing clinical spatial resources with iot',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3373017.3373047',
    'topic': 'clinical distribution shift'},
   {'title': 'explaining machine learning models for clinical gait analysis',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3474121',
    'topic': 'clinical distribution shift'},
   {'title': 'temporal relation extraction in clinical texts: a systematic review',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3462475',
    'topic': 'clinical distribution shift'},
   {'title': 'ontology-aware clinical abstractive summarization',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3331184.3331319',
    'topic': 'clinical distribution shift'},
   {'title': 'automatic extraction of nested entities in clinical referrals in spanish',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3498324',
    'topic': 'clinical distribution shift'},
   {'title': 'learning to rate clinical concepts using simulated clinician feedback',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3025171.3025232',
    'topic': 'clinical distribution shift'},
   {'title': 'science2cure: a clinical trial search prototype',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3404835.3462797',
    'topic': 'clinical distribution shift'},
   {'title': '“brilliant ai doctor” in rural clinics: challenges in ai-powered clinical decision support system deployment',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3411764.3445432',
    'topic': 'clinical distribution shift'},
   {'title': 'leveraging the cloud for intelligent clinical data registries',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3307339.3343464',
    'topic': 'clinical distribution shift'},
   {'title': 'attention-based clinical note summarization',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3477314.3507256',
    'topic': 'clinical distribution shift'},
   {'title': 'conflict discovery and analysis for clinical trials',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3079452.3079494',
    'topic': 'clinical distribution shift'},
   {'title': 'modeling clinical data from publications',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/2873003.2873011',
    'topic': 'clinical distribution shift'},
   {'title': 'robustness evaluation of computer-aided clinical trials for medical devices',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3302509.3311058',
    'topic': 'clinical distribution shift'},
   {'title': 'the evolutionary development of a serious game for clinical laboratory students',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3306500.3306545',
    'topic': 'clinical distribution shift'},
   {'title': 'multi-disciplinary fairness considerations in machine learning for clinical trials',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3531146.3533154',
    'topic': 'clinical distribution shift'},
   {'title': 'protecting interoperable clinical environment with authentication',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3076125.3076129',
    'topic': 'clinical distribution shift'},
   {'title': 'analysis of differences in clinical index between lung cancer patients with or without metastasis',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3107514.3107529',
    'topic': 'clinical distribution shift'},
   {'title': 'methodology for learning and acquiring clinical skills through simulation with artificial human models',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3486011.3486461',
    'topic': 'clinical distribution shift'},
   {'title': 'exploiting social media to enhance clinical decision support',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3358695.3360899',
    'topic': 'clinical distribution shift'},
   {'title': 'fast learning-based registration of sparse 3d clinical images',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3368555.3384462',
    'topic': 'clinical distribution shift'},
   {'title': 'a frequency-filtering strategy of obtaining phi-free sentences from clinical data repository',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2808719.2808752',
    'topic': 'clinical distribution shift'},
   {'title': 'clinical and genomics data integration using meta-dimensional approach',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2996890.3007896',
    'topic': 'clinical distribution shift'},
   {'title': 'application analysis of artificial intelligence target controlled infusion in clinical anesthesia operation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3495018.3495389',
    'topic': 'clinical distribution shift'},
   {'title': 'clinical decision support system based on knn/ontology extraction method',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3432291.3432305',
    'topic': 'clinical distribution shift'},
   {'title': 'driving time-dependent paths in clinical bpmn processes',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3019612.3019620',
    'topic': 'clinical distribution shift'},
   {'title': 'medical question answering for clinical decision support',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2983323.2983819',
    'topic': 'clinical distribution shift'},
   {'title': 'network analysis and recommendation for infectious disease clinical trial research',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3307339.3342156',
    'topic': 'clinical distribution shift'},
   {'title': 'a test collection for matching patients to clinical trials',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2911451.2914672',
    'topic': 'clinical distribution shift'},
   {'title': 'agile clinical decision support development and implementation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3233547.3233663',
    'topic': 'clinical distribution shift'},
   {'title': 'sonic therapy for anxiety management in clinical settings',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3154862.3154892',
    'topic': 'clinical distribution shift'},
   {'title': 'a framework to design successful clinical decision support systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3056540.3064960',
    'topic': 'clinical distribution shift'},
   {'title': 'dependable integrated clinical system architecture with runtime verification',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3199700.3199831',
    'topic': 'clinical distribution shift'},
   {'title': 'automated encoding of clinical guidelines into computer-interpretable format',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3194480.3194495',
    'topic': 'clinical distribution shift'},
   {'title': 'leveraging word embeddings and semantic enrichment for automatic clinical evidence grading',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3194480.3194492',
    'topic': 'clinical distribution shift'},
   {'title': 'exploring the cultivation mode of critical thinking in clinical-thinking training of diagnostics',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3535756.3535776',
    'topic': 'clinical distribution shift'},
   {'title': 'more text please! understanding and supporting the use of visualization for clinical text overview',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3173574.3173996',
    'topic': 'clinical distribution shift'},
   {'title': 'estimating test performance for ai medical devices under distribution shift with conformal prediction',
    'paper': 'https://arxiv.org/pdf/2207.05796.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'ehr foundation models improve robustness in the presence of temporal distribution shift',
    'paper': 'https://doi.org/10.1101/2022.04.15.22273900',
    'topic': 'clinical distribution shift'},
   {'title': 'study of changing trend in the clinical distribution of candida species in various clinical samples at tertiary care hospital, ahmedabad, gujarat -',
    'paper': 'http://www.njcmindia.org/home/download/993',
    'topic': 'clinical distribution shift'},
   {'title': 'sood: self-supervised out-of-distribution detection under domain shift for multi-class colorectal cancer tissue types',
    'paper': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9607789',
    'topic': 'clinical distribution shift'},
   {'title': 'shift in translations: data work with patient-generated health data in clinical practice',
    'paper': 'https://doi.org/10.1177/1460458219833097',
    'topic': 'clinical distribution shift'},
   {'title': 'evaluating model robustness and stability to dataset shift',
    'paper': 'http://proceedings.mlr.press/v130/subbaswamy21a.html',
    'topic': 'clinical distribution shift'},
   {'title': 'a new look into uveitis in colombia: changes in distribution patterns and clinical characteristics over the last 25 years',
    'paper': 'https://doi.org/10.1007/s00417-022-05796-2',
    'topic': 'clinical distribution shift'},
   {'title': 'muscle pain induces a shift of the spatial distribution of upper trapezius muscle activity during a repetitive task: a mechanism for perpetuation of pain with repetitive activity?',
    'paper': 'https://doi.org/10.1097/AJP.0000000000000513',
    'topic': 'clinical distribution shift'},
   {'title': 'robust multivariate nonparametric tests for detection of two-sample location shift in clinical trials',
    'paper': 'https://pdfs.semanticscholar.org/b5f0/c684be516a4f5801270c0d185b0bef9a0785.pdf',
    'topic': 'clinical distribution shift'},
   {'title': 'an empirical framework for domain generalization in clinical settings',
    'paper': 'http://dl.acm.org/citation.cfm?id=3451878',
    'topic': 'clinical distribution shift'},
   {'title': 'difference between distribution shift and data shift, concept ...',
    'paper': 'https://stats.stackexchange.com/questions/548405/difference-between-distribution-shift-and-data-shift-concept-drift-and-model-dr',
    'topic': 'distribution shift'},
   {'title': 'understanding dataset shift - towards data science',
    'paper': 'https://towardsdatascience.com/understanding-dataset-shift-f2a5a262a766',
    'topic': 'distribution shift'},
   {'title': 'distribution shift framework - deepmind',
    'paper': 'https://www.deepmind.com/open-source/distribution-shift-framework',
    'topic': 'distribution shift'},
   {'title': '4.7. environment and distribution shift',
    'paper': 'https://d2l.ai/chapter_linear-classification/environment-and-distribution-shift.html',
    'topic': 'distribution shift'},
   {'title': 'learning to predict and make decisions under distribution shift',
    'paper': 'https://www.ml.cmu.edu/research/phd-dissertation-pdfs/yw4_phd_ml_2021.pdf',
    'topic': 'distribution shift'},
   {'title': 'dataset shift in machine learning - mit press',
    'paper': 'https://mitpress.mit.edu/9780262545877/dataset-shift-in-machine-learning/',
    'topic': 'distribution shift'},
   {'title': 'mechanical mnist – distribution shift - openbu',
    'paper': 'https://open.bu.edu/handle/2144/44485',
    'topic': 'distribution shift'},
   {'title': 'principles of distribution shift (pods) - icml 2022',
    'paper': 'https://icml.cc/Conferences/2022/ScheduleMultitrack?event=13465',
    'topic': 'distribution shift'},
   {'title': 'microsoft/distribution-shift-latent-representations - github',
    'paper': 'https://github.com/microsoft/distribution-shift-latent-representations',
    'topic': 'distribution shift'},
   {'title': 'neurips distshift workshop 2021 - google sites',
    'paper': 'https://sites.google.com/view/distshift2021',
    'topic': 'distribution shift'},
   {'title': 'types of out-of-distribution texts and how to detect them',
    'paper': 'https://aclanthology.org/2021.emnlp-main.835.pdf',
    'topic': 'distribution shift'},
   {'title': 'shifted label distribution matters in distantly supervised ...',
    'paper': 'https://aclanthology.org/D19-1397.pdf',
    'topic': 'distribution shift'},
   {'title': 'to annotate or not? predicting performance drop under ...',
    'paper': 'https://aclanthology.org/D19-1222.pdf',
    'topic': 'distribution shift'},
   {'title': 'contrastive out-of-distribution detection for pretrained ...',
    'paper': 'https://aclanthology.org/2021.emnlp-main.84.pdf',
    'topic': 'distribution shift'},
   {'title': 'on continual model refinement in out-of-distribution data ...',
    'paper': 'https://aclanthology.org/2022.acl-long.223',
    'topic': 'distribution shift'},
   {'title': 'distributionally robust recurrent decoders with random ...',
    'paper': 'https://aclanthology.org/2022.repl4nlp-1.1',
    'topic': 'distribution shift'},
   {'title': 'estimating the impact of domain shift on parser error',
    'paper': 'https://aclanthology.org/2022.findings-acl.68/',
    'topic': 'distribution shift'},
   {'title': 'social media text classification under negative covariate shift',
    'paper': 'https://aclanthology.org/D15-1282.pdf',
    'topic': 'distribution shift'},
   {'title': 'distributionally robust finetuning bert for covariate drift in ...',
    'paper': 'https://aclanthology.org/2022.acl-long.139.pdf',
    'topic': 'distribution shift'},
   {'title': 'adversarial adaptation of synthetic or stale data',
    'paper': 'https://aclanthology.org/P17-1119',
    'topic': 'distribution shift'},
   {'title': 'semi-supervised domain adaptation for dependency parsing ...',
    'paper': 'https://aclanthology.org/2022.acl-long.74',
    'topic': 'distribution shift'},
   {'title': 'joint and conditional estimation of tagging and parsing models',
    'paper': 'https://aclanthology.org/P01-1042.pdf',
    'topic': 'distribution shift'},
   {'title': 'measure and improve robustness in nlp models: a survey',
    'paper': 'https://aclanthology.org/2022.naacl-main.339.pdf',
    'topic': 'distribution shift'},
   {'title': 'unlearn dataset bias in natural language inference by fitting ...',
    'paper': 'https://aclanthology.org/D19-6115',
    'topic': 'distribution shift'},
   {'title': '2022.findings-naacl.13.pdf - acl anthology',
    'paper': 'https://aclanthology.org/2022.findings-naacl.13.pdf',
    'topic': 'distribution shift'},
   {'title': 'an investigation of the (in)effectiveness of counterfactually ...',
    'paper': 'https://aclanthology.org/2022.acl-long.256',
    'topic': 'distribution shift'},
   {'title': 'methods for estimating and improving robustness of ...',
    'paper': 'https://aclanthology.org/2022.naacl-srw.6.pdf',
    'topic': 'distribution shift'},
   {'title': 'evaluating lottery tickets under distributional shifts',
    'paper': 'https://aclanthology.org/D19-6117.pdf',
    'topic': 'distribution shift'},
   {'title': 'test-time training can close the natural distribution shift ...',
    'paper': 'https://proceedings.mlr.press/v162/darestani22a.html',
    'topic': 'distribution shift'},
   {'title': 'examining and combating spurious features under ...',
    'paper': 'https://proceedings.mlr.press/v139/zhou21g.html',
    'topic': 'distribution shift'},
   {'title': 'on distribution shift in learning-based bug detectors',
    'paper': 'https://proceedings.mlr.press/v162/he22a/he22a.pdf',
    'topic': 'distribution shift'},
   {'title': 'estimating generalization under distribution shifts via domain ...',
    'paper': 'https://proceedings.mlr.press/v119/chuang20a.html',
    'topic': 'distribution shift'},
   {'title': 'a label transformation framework for correcting label shift',
    'paper': 'https://proceedings.mlr.press/v119/guo20d.html',
    'topic': 'distribution shift'},
   {'title': 'bayesian adaptation for covariate shift',
    'paper': 'https://papers.nips.cc/paper/2021/hash/07ac7cd13fd0eb1654ccdbd222b81437-Abstract.html',
    'topic': 'distribution shift'},
   {'title': 'rethinking importance weighting for deep learning under ...',
    'paper': 'https://papers.nips.cc/paper/2020/hash/8b9e7ab295e87570551db122a04c6f7c-Abstract.html',
    'topic': 'distribution shift'},
   {'title': 'characterizing generalization under out-of-distribution shifts ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/d1f255a373a3cef72e03aa9d980c7eca-Paper.pdf',
    'topic': 'distribution shift'},
   {'title': 'a unified view of label shift estimation - nips papers',
    'paper': 'https://papers.nips.cc/paper/2020/file/219e052492f4008818b8adb6366c7ed6-Paper.pdf',
    'topic': 'distribution shift'},
   {'title': 'provably efficient q-learning with function approximation via ...',
    'paper': 'http://papers.nips.cc/paper/9018-provably-efficient-q-learning-with-function-approximation-via-distribution-shift-error-checking-oracle.pdf',
    'topic': 'distribution shift'},
   {'title': 'robust federated learning: the case of affine distribution ...',
    'paper': 'https://papers.nips.cc/paper/2020/file/f5e536083a438cec5b64a4954abc17f1-Paper.pdf',
    'topic': 'distribution shift'},
   {'title': 'domain adaptation by using causal inference to predict ...',
    'paper': 'https://papers.nips.cc/paper/8282-domain-adaptation-by-using-causal-inference-to-predict-invariant-conditional-distributions.pdf',
    'topic': 'distribution shift'},
   {'title': 'domain adaptation with conditional distribution matching and ...',
    'paper': 'https://papers.nips.cc/paper/2020/file/dfbfa7ddcfffeb581f50edcf9a0204bb-Paper.pdf',
    'topic': 'distribution shift'},
   {'title': 'correcting covariate shift with the frank-wolfe algorithm',
    'paper': 'https://www.ijcai.org/Proceedings/15/Papers/147.pdf',
    'topic': 'distribution shift'},
   {'title': 'few-shot adaptation of pre-trained networks for domain shift',
    'paper': 'https://www.ijcai.org/proceedings/2022/0232.pdf',
    'topic': 'distribution shift'},
   {'title': 'distance metric learning under covariate shift - ijcai',
    'paper': 'https://www.ijcai.org/Proceedings/11/Papers/205.pdf',
    'topic': 'distribution shift'},
   {'title': 'domain generalization through the lens of angular invariance',
    'paper': 'https://www.ijcai.org/proceedings/2022/0139.pdf',
    'topic': 'distribution shift'},
   {'title': 'approximate exploitability: learning a best response - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0484.pdf',
    'topic': 'distribution shift'},
   {'title': 'searching for optimal subword tokenization in cross ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/595',
    'topic': 'distribution shift'},
   {'title': 'robust domain adaptation: representations, weights and ...',
    'paper': 'https://www.ijcai.org/proceedings/2021/0644.pdf',
    'topic': 'distribution shift'},
   {'title': 'domain generalization under conditional and label shifts via ...',
    'paper': 'https://www.ijcai.org/proceedings/2021/122',
    'topic': 'distribution shift'},
   {'title': 'identifying instance features for capability-oriented evaluation',
    'paper': 'https://www.ijcai.org/proceedings/2022/0392.pdf',
    'topic': 'distribution shift'},
   {'title': 'adversarial bi-regressor network for domain adaptive ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0501.pdf',
    'topic': 'distribution shift'},
   {'title': 'task-aware lipschitz data augmentation for visual ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0514.pdf',
    'topic': 'distribution shift'},
   {'title': 'topological uncertainty: monitoring trained neural networks ...',
    'paper': 'https://www.ijcai.org/proceedings/2021/0367.pdf',
    'topic': 'distribution shift'},
   {'title': 'test-time fourier style calibration for domain generalization',
    'paper': 'https://www.ijcai.org/proceedings/2022/0240.pdf',
    'topic': 'distribution shift'},
   {'title': 'self-managing associative memory for dynamic acquisition of ...',
    'paper': 'https://www.ijcai.org/Proceedings/09/Papers/169.pdf',
    'topic': 'distribution shift'},
   {'title': 'learning personalization for cross-silo federated learning',
    'paper': 'https://www.ijcai.org/proceedings/2022/301',
    'topic': 'distribution shift'},
   {'title': 'a fine-grained analysis on distribution shift - openreview',
    'paper': 'https://openreview.net/forum?id=Dl4LetuLdyK',
    'topic': 'distribution shift'},
   {'title': 'a benchmark of in-the-wild distribution shift over time',
    'paper': 'https://openreview.net/forum?id=BUQD1tJ2UwK',
    'topic': 'distribution shift'},
   {'title': 'feature shift detection: localizing which ... - nips papers',
    'paper': 'https://openreview.net/pdf?id=k1YfNKf0FZn',
    'topic': 'distribution shift'},
   {'title': 'online adaptation to label distribution shift - openreview',
    'paper': 'https://openreview.net/forum?id=6h14cMLgb5q',
    'topic': 'distribution shift'},
   {'title': 'if your data distribution shifts, use self-learning - openreview',
    'paper': 'https://openreview.net/forum?id=1oEvY1a67c1',
    'topic': 'distribution shift'},
   {'title': 'how robust are pre-trained models to distribution shift?',
    'paper': 'https://openreview.net/forum?id=zKDcZBVVEWm',
    'topic': 'distribution shift'},
   {'title': 'fair predictors under distribution shift - openreview',
    'paper': 'https://openreview.net/forum?id=zgl6DdYHggo',
    'topic': 'distribution shift'},
   {'title': 'an empirical study of methods for detecting dataset shift',
    'paper': 'https://openreview.net/pdf/f9a2ae9ee8021aeb70a8f2deeab247a324b8200e.pdf',
    'topic': 'distribution shift'},
   {'title': 'robust generalization despite distribution shift via minimum ...',
    'paper': 'https://openreview.net/attachment?id=kiWRlrbVzSM&name=supplementary_material',
    'topic': 'distribution shift'},
   {'title': 'tracking the risk of a deployed model - openreview',
    'paper': 'https://openreview.net/pdf?id=Ro_zAjZppv',
    'topic': 'distribution shift'},
   {'title': 'towards explaining image-based distribution shifts',
    'paper': 'https://openreview.net/pdf?id=MpDDnE6_lGC',
    'topic': 'distribution shift'},
   {'title': 'handling distribution shifts on graphs',
    'paper': 'https://openreview.net/pdf?id=FQOC5u-1egI',
    'topic': 'distribution shift'},
   {'title': 'unsupervised attribute alignment for characterizing ...',
    'paper': 'https://openreview.net/forum?id=Bk1hklAuZyh',
    'topic': 'distribution shift'},
   {'title': 'reversible instance normalization for ...',
    'paper': 'https://openreview.net/pdf?id=cGDAkQo1C0p',
    'topic': 'distribution shift'},
   {'title': 'a fine-grained analysis on distribution shift - arxiv',
    'paper': 'https://arxiv.org/abs/2110.11328',
    'topic': 'distribution shift'},
   {'title': 'an empirical study on distribution shift robustness from the ...',
    'paper': 'https://arxiv.org/abs/2205.12753',
    'topic': 'distribution shift'},
   {'title': 'maintaining fairness across distribution shift - arxiv',
    'paper': 'https://arxiv.org/pdf/2202.01034',
    'topic': 'distribution shift'},
   {'title': 'interpretable distribution shift detection using optimal transport',
    'paper': 'https://arxiv.org/abs/2208.02896',
    'topic': 'distribution shift'},
   {'title': 'codes: a distribution shift benchmark dataset for source ...',
    'paper': 'https://arxiv.org/abs/2206.05480',
    'topic': 'distribution shift'},
   {'title': 'how robust are pre-trained models to distribution shift? - arxiv',
    'paper': 'https://arxiv.org/abs/2206.08871',
    'topic': 'distribution shift'},
   {'title': 'calibrated ensembles can mitigate accuracy tradeoffs under ...',
    'paper': 'http://arxiv.org/abs/2207.08977',
    'topic': 'distribution shift'},
   {'title': 'discovering distribution shifts using latent space ... - arxiv',
    'paper': 'https://arxiv.org/abs/2202.02339',
    'topic': 'distribution shift'},
   {'title': 'models out of line: a fourier lens on distribution shift ... - arxiv',
    'paper': 'https://arxiv.org/abs/2207.04075',
    'topic': 'distribution shift'},
   {'title': 'combating distribution shift for accurate time series ... - arxiv',
    'paper': 'https://arxiv.org/abs/2202.10808',
    'topic': 'distribution shift'},
   {'title': 'time series prediction under distribution shift using ... - arxiv',
    'paper': 'http://arxiv.org/abs/2207.11486',
    'topic': 'distribution shift'},
   {'title': 'on distribution shift in learning-based bug detectors - arxiv',
    'paper': 'https://arxiv.org/abs/2204.10049',
    'topic': 'distribution shift'},
   {'title': 'fairness transferability subject to bounded distribution shift',
    'paper': 'https://arxiv.org/abs/2206.00129',
    'topic': 'distribution shift'},
   {'title': 'combating label distribution shift for active domain adaptation',
    'paper': 'https://arxiv.org/abs/2208.06604',
    'topic': 'distribution shift'},
   {'title': 'test: test-time self-training under distribution shift - arxiv',
    'paper': 'https://arxiv.org/abs/2209.11459',
    'topic': 'distribution shift'},
   {'title': '[2202.06523] metashift: a dataset of datasets for evaluating ...',
    'paper': 'https://arxiv.org/abs/2202.06523',
    'topic': 'distribution shift'},
   {'title': 'estimating test performance for ai medical devices under ...',
    'paper': 'https://arxiv.org/abs/2207.05796',
    'topic': 'distribution shift'},
   {'title': 'agreement-on-the-line: predicting the performance of neural ...',
    'paper': 'https://arxiv.org/abs/2206.13089',
    'topic': 'distribution shift'},
   {'title': 'contrastive graph few-shot learning',
    'paper': 'https://arxiv.org/abs/2210.00084',
    'topic': 'distribution shift'},
   {'title': 'learning an invertible output mapping can mitigate simplicity bias in neural networks',
    'paper': 'https://arxiv.org/abs/2210.01360',
    'topic': 'distribution shift'},
   {'title': 'a fixed-point algorithm for the ac power flow problem',
    'paper': 'https://arxiv.org/abs/2210.01310',
    'topic': 'distribution shift'},
   {'title': 'percolation properties of the neutron population in nuclear reactors',
    'paper': 'https://arxiv.org/abs/2210.02413',
    'topic': 'distribution shift'},
   {'title': 'a review of uncertainty calibration in pretrained object detectors',
    'paper': 'https://arxiv.org/abs/2210.02935',
    'topic': 'distribution shift'},
   {'title': 'analysis of irs-assisted downlink wireless networks over generalized fading',
    'paper': 'https://arxiv.org/abs/2210.02717',
    'topic': 'distribution shift'},
   {'title': 'exploring effective knowledge transfer for few-shot object detection',
    'paper': 'https://arxiv.org/abs/2210.02021',
    'topic': 'distribution shift'},
   {'title': 'gapx: generalized autoregressive paraphrase-identification x',
    'paper': 'https://arxiv.org/abs/2210.01979',
    'topic': 'distribution shift'},
   {'title': 'gravitational microlensing by dressed primordial black holes',
    'paper': 'https://arxiv.org/abs/2210.02078',
    'topic': 'distribution shift'},
   {'title': 'data drift correction via time-varying importance weight estimator',
    'paper': 'https://arxiv.org/abs/2210.01422',
    'topic': 'distribution shift'},
   {'title': 'adawac: adaptively weighted augmentation consistency regularization for volumetric medical image segmentation',
    'paper': 'https://arxiv.org/abs/2210.01891',
    'topic': 'distribution shift'},
   {'title': 'on the (un)importance of the transition-dipole phase in the high-harmonic generation from solid state media',
    'paper': 'https://arxiv.org/abs/2210.02500',
    'topic': 'distribution shift'},
   {'title': "satellite-based continuous-variable quantum key distribution under the earth's gravitational field",
    'paper': 'https://arxiv.org/abs/2210.02776',
    'topic': 'distribution shift'},
   {'title': 'env-aware anomaly detection: ignore style changes, stay true to content!',
    'paper': 'https://arxiv.org/abs/2210.03103',
    'topic': 'distribution shift'},
   {'title': 'spectroscopic localization of atomic sample plane for precise digital holography',
    'paper': 'https://arxiv.org/abs/2210.02721',
    'topic': 'distribution shift'},
   {'title': 'benchmarking learnt radio localisation under distribution shift',
    'paper': 'https://arxiv.org/abs/2210.01930',
    'topic': 'distribution shift'},
   {'title': 'generalized solution of the paraxial equation',
    'paper': 'https://arxiv.org/abs/2210.01088',
    'topic': 'distribution shift'},
   {'title': 'on the effects of data normalisation for domain adaptation on eeg data',
    'paper': 'https://arxiv.org/abs/2210.01081',
    'topic': 'distribution shift'},
   {'title': 'spectral-domain method of moments analysis of spatially dispersive graphene patch embedded in planarly layered media',
    'paper': 'https://arxiv.org/abs/2210.00877',
    'topic': 'distribution shift'},
   {'title': 'towards performance portable programming for distributed heterogeneous systems',
    'paper': 'https://arxiv.org/abs/2210.01238',
    'topic': 'distribution shift'},
   {'title': 'simper: simple self-supervised learning of periodic targets',
    'paper': 'https://arxiv.org/abs/2210.03115',
    'topic': 'distribution shift'},
   {'title': 'class-specific channel attention for few-shot learning',
    'paper': 'https://arxiv.org/abs/2209.01332',
    'topic': 'distribution shift'},
   {'title': 'deep stable representation learning on electronic health records',
    'paper': 'https://arxiv.org/abs/2209.01321',
    'topic': 'distribution shift'},
   {'title': 'a demonstration of over-the-air computation for federated edge learning',
    'paper': 'https://arxiv.org/abs/2209.09954',
    'topic': 'distribution shift'},
   {'title': 's2p: state-conditioned image synthesis for data augmentation in offline reinforcement learning',
    'paper': 'https://arxiv.org/abs/2209.15256',
    'topic': 'distribution shift'},
   {'title': 'domain generalization -- a causal perspective',
    'paper': 'https://arxiv.org/abs/2209.15177',
    'topic': 'distribution shift'},
   {'title': 'a domain adaptive deep learning solution for scanpath prediction of paintings',
    'paper': 'https://arxiv.org/abs/2209.11338',
    'topic': 'distribution shift'},
   {'title': 'robust bayesian non-segmental detection of multiple change-points',
    'paper': 'https://arxiv.org/abs/2209.14995',
    'topic': 'distribution shift'},
   {'title': 'modelling the energy distribution in chime/frb catalog-1',
    'paper': 'https://arxiv.org/abs/2209.12961',
    'topic': 'distribution shift'},
   {'title': 'exact and efficient multivariate two-sample tests through generalized linear rank statistics',
    'paper': 'https://arxiv.org/abs/2209.14235',
    'topic': 'distribution shift'},
   {'title': 'black-box audits for group distribution shifts',
    'paper': 'https://arxiv.org/abs/2209.03620',
    'topic': 'distribution shift'},
   {'title': 'semi-supervised triply robust inductive transfer learning',
    'paper': 'https://arxiv.org/abs/2209.04977',
    'topic': 'distribution shift'},
   {'title': 'polito-iit-cini submission to the epic-kitchens-100 unsupervised domain adaptation challenge for action recognition',
    'paper': 'https://arxiv.org/abs/2209.04525',
    'topic': 'distribution shift'},
   {'title': 'non-parametric temporal adaptation for social media topic classification',
    'paper': 'https://arxiv.org/abs/2209.05706',
    'topic': 'distribution shift'},
   {'title': 'test-time adaptation with principal component analysis',
    'paper': 'https://arxiv.org/abs/2209.05779',
    'topic': 'distribution shift'},
   {'title': 'giant overreflection of magnetohydrodynamic waves from inhomogeneous plasmas with nonuniform shear flows',
    'paper': 'https://arxiv.org/abs/2209.08061',
    'topic': 'distribution shift'},
   {'title': 'mitigating both covariate and conditional shift for domain generalization',
    'paper': 'https://arxiv.org/abs/2209.08253',
    'topic': 'distribution shift'},
   {'title': 'visible-infrared person re-identification using privileged intermediate information',
    'paper': 'https://arxiv.org/abs/2209.09348',
    'topic': 'distribution shift'},
   {'title': 'improving replay-based continual semantic segmentation with smart data selection',
    'paper': 'https://arxiv.org/abs/2209.09839',
    'topic': 'distribution shift'},
   {'title': 'towards optimization and model selection for domain generalization: a mixup-guided solution',
    'paper': 'https://arxiv.org/abs/2209.00652',
    'topic': 'distribution shift'},
   {'title': 'future gradient descent for adapting the temporal shifting data distribution in online recommendation systems',
    'paper': 'https://arxiv.org/abs/2209.01143',
    'topic': 'distribution shift'},
   {'title': 'meta-learning with less forgetting on large-scale non-stationary task distributions',
    'paper': 'https://arxiv.org/abs/2209.01501',
    'topic': 'distribution shift'},
   {'title': 'robustness and invariance properties of image classifiers',
    'paper': 'https://arxiv.org/abs/2209.02408',
    'topic': 'distribution shift'},
   {'title': 'importance tempering: group robustness for overparameterized models',
    'paper': 'https://arxiv.org/abs/2209.08745',
    'topic': 'distribution shift'},
   {'title': 'exploiting instance-based mixed sampling via auxiliary source domain supervision for domain-adaptive action detection',
    'paper': 'https://arxiv.org/abs/2209.15439',
    'topic': 'distribution shift'},
   {'title': 'too fine or too coarse? the goldilocks composition of data complexity for robust left-right eye-tracking classifiers',
    'paper': 'https://arxiv.org/abs/2209.03761',
    'topic': 'distribution shift'},
   {'title': 'record: resource constrained semi-supervised learning under distribution shift',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3394486.3403214',
    'topic': 'distribution shift'},
   {'title': 'towards reliable multimodal stress detection under distribution shift',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3461615.3486570',
    'topic': 'distribution shift'},
   {'title': 'confidence may cheat: self-training on graph neural networks under distribution shift',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3485447.3512172',
    'topic': 'distribution shift'},
   {'title': 'active model adaptation under unknown shift',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3534678.3539262',
    'topic': 'distribution shift'},
   {'title': 'balance-subsampled stable prediction across unknown test data',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3477052',
    'topic': 'distribution shift'},
   {'title': 'focused context balancing for robust offline policy evaluation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3292500.3330852',
    'topic': 'distribution shift'},
   {'title': 'an empirical study on data distribution-aware test selection for deep learning enhancement',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3511598',
    'topic': 'distribution shift'},
   {'title': 'a critical reassessment of the saerens-latinne-decaestecker algorithm for posterior probability adjustment',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3433164',
    'topic': 'distribution shift'},
   {'title': 'understanding the effect of out-of-distribution examples and interactive explanations on human-ai decision making',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3479552',
    'topic': 'distribution shift'},
   {'title': 'co-training disentangled domain adaptation network for leveraging popularity bias in recommenders',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3477495.3531952',
    'topic': 'distribution shift'},
   {'title': 'causpref: causal preference learning for out-of-distribution recommendation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3485447.3511969',
    'topic': 'distribution shift'},
   {'title': 'off-policy actor-critic for recommender systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3523227.3546758',
    'topic': 'distribution shift'},
   {'title': 'hybridrepair: towards annotation-efficient repair for deep learning models',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3533767.3534408',
    'topic': 'distribution shift'},
   {'title': 'decoupled reinforcement learning to stabilise intrinsically-motivated exploration',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3535850.3535978',
    'topic': 'distribution shift'},
   {'title': 'neural statistics for click-through rate prediction',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3477495.3531762',
    'topic': 'distribution shift'},
   {'title': 'influence function for unbiased recommendation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3397271.3401321',
    'topic': 'distribution shift'},
   {'title': 'dcaf-bert: a distilled cachable adaptable factorized model for improved ads ctr prediction',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3487553.3524206',
    'topic': 'distribution shift'},
   {'title': 'making adversarially-trained language models forget with model retraining: a case study on hate speech detection',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3487553.3524667',
    'topic': 'distribution shift'},
   {'title': 'causal discovery from heterogeneous/nonstationary data',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3455716.3455805',
    'topic': 'distribution shift'},
   {'title': 'svem: a signal variation elimination model for eeg emotion recognition',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3543081.3543085',
    'topic': 'distribution shift'},
   {'title': 'adarnn: adaptive learning and forecasting of time series',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3459637.3482315',
    'topic': 'distribution shift'},
   {'title': 'transfer string kernel for cross-context dna-protein binding prediction',
    'paper': 'https://dl.acm.org/doi/pdf/10.1109/TCBB.2016.2609918',
    'topic': 'distribution shift'},
   {'title': 'trustworthy graph learning: reliability, explainability, and privacy protection',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3534678.3542597',
    'topic': 'distribution shift'},
   {'title': 'real negatives matter: continuous training with real negatives for delayed feedback modeling',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3447548.3467086',
    'topic': 'distribution shift'},
   {'title': 'a new generation of perspective api: efficient multilingual character-level transformers',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3534678.3539147',
    'topic': 'distribution shift'},
   {'title': 'robust self-supervised structural graph neural network for social network prediction',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3485447.3512182',
    'topic': 'distribution shift'},
   {'title': 'stable prediction across unknown environments',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3219819.3220082',
    'topic': 'distribution shift'},
   {'title': 'learning security classifiers with verified global robustness properties',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3460120.3484776',
    'topic': 'distribution shift'},
   {'title': 'fairness violations and mitigation under covariate shift',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3442188.3445865',
    'topic': 'distribution shift'},
   {'title': 'quantifying the performance of adversarial training on language models with distribution shifts',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3494108.3522764',
    'topic': 'distribution shift'},
   {'title': 'fedrs: federated learning with restricted softmax for label distribution non-iid data',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3447548.3467254',
    'topic': 'distribution shift'},
   {'title': 'case study on distribution strategy through biclustering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3387263.3387271',
    'topic': 'distribution shift'},
   {'title': 'semi-supervised flexible joint distribution adaptation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3375998.3376022',
    'topic': 'distribution shift'},
   {'title': 'analysis of the modified weibull distribution for estimation of wind speed distribution',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2832987.2833059',
    'topic': 'distribution shift'},
   {'title': 'l-shift: encoding and shifting material properties and functionalities with phase-shifting liquid',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2677199.2688807',
    'topic': 'distribution shift'},
   {'title': 'embedded out-of-distribution detection on an autonomous robot platform',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3445034.3460509',
    'topic': 'distribution shift'},
   {'title': 'distribution-matching embedding for visual domain adaptation',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/2946645.3007061',
    'topic': 'distribution shift'},
   {'title': 'transfer learning with dynamic distribution adaptation',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3360309',
    'topic': 'distribution shift'},
   {'title': 'probabilistic modeling for frequency vectors using a flexible shifted-scaled dirichlet distribution prior',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3406242',
    'topic': 'distribution shift'},
   {'title': 'monitoring perception reliability in autonomous driving: distributional shift detection for estimating the impact of input data on prediction accuracy',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3488904.3493382',
    'topic': 'distribution shift'},
   {'title': 'dynamical origins of distribution functions',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3292500.3330842',
    'topic': 'distribution shift'},
   {'title': 'ignis: scaling distribution-oblivious systems with light-touch distribution',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3314221.3314586',
    'topic': 'distribution shift'},
   {'title': 'control of networked traffic flow distribution: a stochastic distribution system perspective',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3109761.3158411',
    'topic': 'distribution shift'},
   {'title': 'modeling neurocognitive reaction time with gamma distribution',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3167918.3167941',
    'topic': 'distribution shift'},
   {'title': 'a feedback shift correction in predicting conversion rates under delayed feedback',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3366423.3380032',
    'topic': 'distribution shift'},
   {'title': 'a crowdsourcing approach for the inference of distribution grids',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3208903.3208927',
    'topic': 'distribution shift'},
   {'title': 'adapting covariate shift for legal ai',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3322640.3326720',
    'topic': 'distribution shift'},
   {'title': 'semi-supervised drifted stream learning with short lookback',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3534678.3539297',
    'topic': 'distribution shift'},
   {'title': 'on the theory of policy gradient methods: optimality, approximation, and distribution shift',
    'paper': 'http://jmlr.org/papers/v22/19-736.html',
    'topic': 'distribution shift'},
   {'title': 'test-time adaptation to distribution shift by confidence maximization and input transformation',
    'paper': 'https://arxiv.org/pdf/2106.14999.pdf',
    'topic': 'distribution shift'},
   {'title': 'mandoline: model evaluation under distribution shift',
    'paper': 'https://arxiv.org/pdf/2107.00643.pdf',
    'topic': 'distribution shift'},
   {'title': 'examining and combating spurious features under distribution shift',
    'paper': 'https://arxiv.org/pdf/2106.07171.pdf',
    'topic': 'distribution shift'},
   {'title': 'stable prediction with model misspecification and agnostic distribution shift',
    'paper': 'https://arxiv.org/pdf/2001.11713.pdf',
    'topic': 'distribution shift'},
   {'title': 'rethinking importance weighting for deep learning under distribution shift',
    'paper': 'https://arxiv.org/pdf/2006.04662.pdf',
    'topic': 'distribution shift'},
   {'title': 'online adaptation to label distribution shift',
    'paper': 'https://arxiv.org/pdf/2107.04520.pdf',
    'topic': 'distribution shift'},
   {'title': 'near-optimal linear regression under distribution shift',
    'paper': 'https://arxiv.org/pdf/2106.12108.pdf',
    'topic': 'distribution shift'},
   {'title': 'closing the closed-loop distribution shift in safe imitation learning',
    'paper': 'no_link_found',
    'topic': 'distribution shift'},
   {'title': 'the effect of natural distribution shift on question answering models ...',
    'paper': 'https://dl.acm.org/doi/abs/10.5555/3524938.3525579',
    'topic': 'distribution shift question answering'},
   {'title': 'the effect of natural distribution shift on ... - researchgate',
    'paper': 'https://www.researchgate.net/publication/341069459_The_Effect_of_Natural_Distribution_Shift_on_Question_Answering_Models',
    'topic': 'distribution shift question answering'},
   {'title': 'the effect of natural distribution shift on ... - karl krauth',
    'paper': 'https://karlk.net/publication/dist_shift/',
    'topic': 'distribution shift question answering'},
   {'title': 'out-of-domain question answering - stanford university',
    'paper': 'https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/reports/final_reports/report163.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'selective question answering under domain shift',
    'paper': 'https://aclanthology.org/2020.acl-main.503.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'topic transferable table question answering - acl anthology',
    'paper': 'https://aclanthology.org/2021.emnlp-main.342.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 're-evaluating conversational question answering',
    'paper': 'https://aclanthology.org/2022.acl-long.555.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'improving calibration in question answering - acl anthology',
    'paper': 'https://aclanthology.org/2021.findings-acl.172.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'improving question answering model robustness with ...',
    'paper': 'https://aclanthology.org/2021.emnlp-main.696.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'contrastive domain adaptation for question answering using ...',
    'paper': 'https://aclanthology.org/2021.emnlp-main.754.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'on the efficacy of adversarial data collection for question ...',
    'paper': 'https://aclanthology.org/2021.acl-long.517.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'entity-based knowledge conflicts in question answering',
    'paper': 'https://aclanthology.org/2021.emnlp-main.565.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'improving unsupervised question answering via ...',
    'paper': 'https://aclanthology.org/2021.emnlp-main.340.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'challenges in generalization in open domain question ...',
    'paper': 'https://aclanthology.org/2022.findings-naacl.155.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'accuracy on the line: on the strong correlation between out ...',
    'paper': 'https://proceedings.mlr.press/v139/miller21b/miller21b.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'wilds: a benchmark of in-the-wild distribution shifts',
    'paper': 'http://proceedings.mlr.press/v139/koh21a/koh21a.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'instabilities of offline rl with pre-trained neural ...',
    'paper': 'http://proceedings.mlr.press/v139/wang21z/wang21z.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'data determines distributional robustness in contrastive ...',
    'paper': 'https://proceedings.mlr.press/v162/fang22a/fang22a.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'lyapunov density models: constraining distribution shift in ...',
    'paper': 'https://proceedings.mlr.press/v162/kang22a/kang22a.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'active learning under label shift',
    'paper': 'http://proceedings.mlr.press/v130/zhao21b/zhao21b.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'predicting out-of-distribution error with the projection norm',
    'paper': 'https://proceedings.mlr.press/v162/yu22i/yu22i.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'can autonomous vehicles identify, recover from,and adapt ...',
    'paper': 'http://proceedings.mlr.press/v119/filos20a/filos20a.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'measuring robustness to natural distribution shifts in image ...',
    'paper': 'https://papers.nips.cc/paper/2020/file/d8330f857a17c53d217014ee776bfd50-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'adaptive conformal inference under distribution shift',
    'paper': 'https://papers.nips.cc/paper/2021/file/0d441de75945e5acbc865406fc9a2559-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'overparameterization improves robustness to covariate shift ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/73fed7fd472e502d8908794430511f4d-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'revisiting the calibration of modern neural networks',
    'paper': 'https://papers.nips.cc/paper/2021/file/8420d359404024567b5aefda1231af24-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'reducing unimodal biases for visual question answering',
    'paper': 'https://papers.nips.cc/paper/8371-rubi-reducing-unimodal-biases-for-visual-question-answering.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'debiased visual question answering from feature and ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/1f4477bad7af3616c1f933a02bfabe4e-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'on the value of out-of-distribution testing: an example of ...',
    'paper': 'https://papers.nips.cc/paper/2020/file/045117b0e0a11a242b9765e79cbf113f-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'mitigating covariate shift in imitation learning via offline data ...',
    'paper': 'https://papers.nips.cc/paper/2021/file/07d5938693cc3903b261e1a3844590ed-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'react: out-of-distribution detection with rectified activations',
    'paper': 'https://papers.nips.cc/paper/2021/file/01894d6f048493d2cacde3c579c315a3-Paper.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'learning imbalanced datasets with label-distribution-aware ...',
    'paper': 'https://papers.nips.cc/paper/8435-learning-imbalanced-datasets-with-label-distribution-aware-margin-loss.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'ai foundations for human visual perception driven cognitive ...',
    'paper': 'http://www.ijcai.org/Proceedings/16/Papers/374.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'k-best: a new method for real-time decision making - ijcai',
    'paper': 'https://www.ijcai.org/Proceedings/95-1/Papers/030.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'provable guarantees on the robustness of decision rules to ...',
    'paper': 'https://www.ijcai.org/proceedings/2021/0585.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'robustifying vision transformer without retraining from ...',
    'paper': 'https://www.ijcai.org/proceedings/2022/0141.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'exploiting the sign of the advantage function to learn ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2019/0625.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'bridging causality and learning: how do they benefit from ...',
    'paper': 'https://www.ijcai.org/proceedings/2020/0725.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'towards robust dense retrieval via local ranking alignment',
    'paper': 'https://www.ijcai.org/proceedings/2022/0275.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'robustness guarantees for credal bayesian networks ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/0677.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'multi-agent concentrative coordination with decentralized ...',
    'paper': 'https://www.ijcai.org/proceedings/2022/0085.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'session no. 13 computer understanding ii (representation)',
    'paper': 'http://www.ijcai.org/Proceedings/71/Papers/048.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'an information-theoretic approach to distribution shifts',
    'paper': 'https://openreview.net/forum?id=GrZmKDYCp6H',
    'topic': 'distribution shift question answering'},
   {'title': 'a closer look at distribution shifts and out-of ... - openreview',
    'paper': 'https://openreview.net/forum?id=2JFVnWuvrvV',
    'topic': 'distribution shift question answering'},
   {'title': 'a fine-grained analysis on distribution shift',
    'paper': 'https://openreview.net/pdf?id=Dl4LetuLdyK',
    'topic': 'distribution shift question answering'},
   {'title': 'a dataset of real distributional shift across multiple large ...',
    'paper': 'https://openreview.net/forum?id=qM45LHaWM6E',
    'topic': 'distribution shift question answering'},
   {'title': 'addressing distribution shift in offline-to ...',
    'paper': 'https://openreview.net/pdf?id=9hgEG-k57Zj',
    'topic': 'distribution shift question answering'},
   {'title': 'anoshift: a distribution shift benchmark for unsupervised ...',
    'paper': 'https://openreview.net/forum?id=rbrouCKPiej',
    'topic': 'distribution shift question answering'},
   {'title': 'addressing distribution shift in online reinforcement ...',
    'paper': 'https://openreview.net/forum?id=9hgEG-k57Zj',
    'topic': 'distribution shift question answering'},
   {'title': 'detecting and adapting to irregular distribution shifts in ...',
    'paper': 'https://openreview.net/forum?id=-440wKL2oJV',
    'topic': 'distribution shift question answering'},
   {'title': 'generative question answering: learning to ...',
    'paper': 'https://openreview.net/pdf?id=Bkx0RjA9tX',
    'topic': 'distribution shift question answering'},
   {'title': 'if your data distribution shifts, use self-learning',
    'paper': 'https://openreview.net/pdf?id=1oEvY1a67c1',
    'topic': 'distribution shift question answering'},
   {'title': 'the effect of natural distribution shift on question answering ...',
    'paper': 'https://arxiv.org/abs/2004.14444',
    'topic': 'distribution shift question answering'},
   {'title': 'improving out-of-distribution robustness via selective ... - arxiv',
    'paper': 'https://arxiv.org/pdf/2201.00299',
    'topic': 'distribution shift question answering'},
   {'title': 'toward a fine-grained analysis of distribution shifts in ... - arxiv',
    'paper': 'https://arxiv.org/pdf/2205.02870',
    'topic': 'distribution shift question answering'},
   {'title': 'arxiv:2006.05121v3 [cs.cv] 7 apr 2021',
    'paper': 'https://arxiv.org/pdf/2006.05121',
    'topic': 'distribution shift question answering'},
   {'title': 'afine-grained analysis on distribution shift - arxiv',
    'paper': 'https://arxiv.org/pdf/2110.11328',
    'topic': 'distribution shift question answering'},
   {'title': 'arxiv:2207.08739v1 [cs.cv] 18 jul 2022',
    'paper': 'https://arxiv.org/pdf/2207.08739',
    'topic': 'distribution shift question answering'},
   {'title': 'x-ggm: graph generative modeling for out-of-distribution ...',
    'paper': 'https://arxiv.org/pdf/2107.11576',
    'topic': 'distribution shift question answering'},
   {'title': 'arxiv:2207.01168v1 [cs.lg] 4 jul 2022',
    'paper': 'https://arxiv.org/pdf/2207.01168',
    'topic': 'distribution shift question answering'},
   {'title': 'how good are deep models in understanding\\\\ the generated ...',
    'paper': 'https://arxiv.org/abs/2208.10760',
    'topic': 'distribution shift question answering'},
   {'title': 'task formulation matters when learning continually: a case study in visual question answering',
    'paper': 'https://arxiv.org/abs/2210.00044',
    'topic': 'distribution shift question answering'},
   {'title': 'complexity-based prompting for multi-step reasoning',
    'paper': 'https://arxiv.org/abs/2210.00720',
    'topic': 'distribution shift question answering'},
   {'title': 'test-time adaptation for visual document understanding',
    'paper': 'https://arxiv.org/abs/2206.07240',
    'topic': 'distribution shift question answering'},
   {'title': 'data determines distributional robustness in contrastive language image pre-training (clip)',
    'paper': 'https://arxiv.org/abs/2205.01397',
    'topic': 'distribution shift question answering'},
   {'title': 'rethinking evaluation practices in visual question answering: a case study on out-of-distribution generalization',
    'paper': 'https://arxiv.org/abs/2205.12191',
    'topic': 'distribution shift question answering'},
   {'title': 'teaching models to express their uncertainty in words',
    'paper': 'https://arxiv.org/abs/2205.14334',
    'topic': 'distribution shift question answering'},
   {'title': 'improving passage retrieval with zero-shot question generation',
    'paper': 'https://arxiv.org/abs/2204.07496',
    'topic': 'distribution shift question answering'},
   {'title': 'data-suite: data-centric identification of in-distribution incongruous examples',
    'paper': 'https://arxiv.org/abs/2202.08836',
    'topic': 'distribution shift question answering'},
   {'title': 'on a class of lacunary almost newman polynomials modulo p and density theorems',
    'paper': 'https://arxiv.org/abs/2201.03233',
    'topic': 'distribution shift question answering'},
   {'title': 'question generation for evaluating cross-dataset shifts in multi-modal grounding',
    'paper': 'https://arxiv.org/abs/2201.09639',
    'topic': 'distribution shift question answering'},
   {'title': 'local distributional chaos',
    'paper': 'https://arxiv.org/abs/2112.01457',
    'topic': 'distribution shift question answering'},
   {'title': 'causal forecasting:generalization bounds for autoregressive models',
    'paper': 'https://arxiv.org/abs/2111.09831',
    'topic': 'distribution shift question answering'},
   {'title': 'dair: data augmented invariant regularization',
    'paper': 'https://arxiv.org/abs/2110.11205',
    'topic': 'distribution shift question answering'},
   {'title': 'topic transferable table question answering',
    'paper': 'https://arxiv.org/abs/2109.07377',
    'topic': 'distribution shift question answering'},
   {'title': 'aggregate or not? exploring where to privatize in dnn based federated learning under different non-iid scenes',
    'paper': 'https://arxiv.org/abs/2107.11954',
    'topic': 'distribution shift question answering'},
   {'title': 'pointer value retrieval: a new benchmark for understanding the limits of neural network generalization',
    'paper': 'https://arxiv.org/abs/2107.12580',
    'topic': 'distribution shift question answering'},
   {'title': 'invariance principle meets information bottleneck for out-of-distribution generalization',
    'paper': 'https://arxiv.org/abs/2106.06607',
    'topic': 'distribution shift question answering'},
   {'title': 'a winning hand: compressing deep networks can improve out-of-distribution robustness',
    'paper': 'https://arxiv.org/abs/2106.09129',
    'topic': 'distribution shift question answering'},
   {'title': 'approximate bayesian computation for an explicit-duration hidden markov model of covid-19 hospital trajectories',
    'paper': 'https://arxiv.org/abs/2105.00773',
    'topic': 'distribution shift question answering'},
   {'title': 'crossnorm and selfnorm for generalization under distribution shifts',
    'paper': 'https://arxiv.org/abs/2102.02811',
    'topic': 'distribution shift question answering'},
   {'title': 'a new tool for precise mapping of local temperature fields in submicrometer aqueous volumes',
    'paper': 'https://arxiv.org/abs/2102.07461',
    'topic': 'distribution shift question answering'},
   {'title': 'leveraging uncertainty from deep learning for trustworthy materials discovery workflows',
    'paper': 'https://arxiv.org/abs/2012.01478',
    'topic': 'distribution shift question answering'},
   {'title': 'coping with label shift via distributionally robust optimisation',
    'paper': 'https://arxiv.org/abs/2010.12230',
    'topic': 'distribution shift question answering'},
   {'title': 'some factors of nonsingular bernoulli shifts',
    'paper': 'https://arxiv.org/abs/2010.04636',
    'topic': 'distribution shift question answering'},
   {'title': 'a tale of two cities: software developers working from home during the covid-19 pandemic',
    'paper': 'https://arxiv.org/abs/2008.11147',
    'topic': 'distribution shift question answering'},
   {'title': 'roses are red, violets are blue... but should vqa expect them to?',
    'paper': 'https://arxiv.org/abs/2006.05121',
    'topic': 'distribution shift question answering'},
   {'title': 'generalized mean shift with triangular kernel profile',
    'paper': 'https://arxiv.org/abs/2001.02165',
    'topic': 'distribution shift question answering'},
   {'title': 'metaci: meta-learning for causal inference in a heterogeneous population',
    'paper': 'https://arxiv.org/abs/1912.03960',
    'topic': 'distribution shift question answering'},
   {'title': 'stationary distributions for the voter model in $d\\geq 3$ are factors of iid',
    'paper': 'https://arxiv.org/abs/1908.09450',
    'topic': 'distribution shift question answering'},
   {'title': 'dark matter haloes and subhaloes',
    'paper': 'https://arxiv.org/abs/1907.11775',
    'topic': 'distribution shift question answering'},
   {'title': 'information-theoretic considerations in batch reinforcement learning',
    'paper': 'https://arxiv.org/abs/1905.00360',
    'topic': 'distribution shift question answering'},
   {'title': 'biobert: a pre-trained biomedical language representation model for biomedical text mining',
    'paper': 'https://arxiv.org/abs/1901.08746',
    'topic': 'distribution shift question answering'},
   {'title': 'maximum of branching brownian motion in a periodic environment',
    'paper': 'https://arxiv.org/abs/1812.04189',
    'topic': 'distribution shift question answering'},
   {'title': 'density estimation for shift-invariant multidimensional distributions',
    'paper': 'https://arxiv.org/abs/1811.03744',
    'topic': 'distribution shift question answering'},
   {'title': 'thick points of random walk and the gaussian free field',
    'paper': 'https://arxiv.org/abs/1809.04369',
    'topic': 'distribution shift question answering'},
   {'title': 'koala: a new paradigm for election coverage',
    'paper': 'https://arxiv.org/abs/1807.09665',
    'topic': 'distribution shift question answering'},
   {'title': 'accounting for phenology in the analysis of animal movement',
    'paper': 'https://arxiv.org/abs/1806.09473',
    'topic': 'distribution shift question answering'},
   {'title': 'when can multi-site datasets be pooled for regression? hypothesis tests, $\\ell_2$-consistency and neuroscience applications',
    'paper': 'https://arxiv.org/abs/1709.00640',
    'topic': 'distribution shift question answering'},
   {'title': 'distributed strong diameter network decomposition',
    'paper': 'https://arxiv.org/abs/1602.05437',
    'topic': 'distribution shift question answering'},
   {'title': 'achieving delay rate-function optimality in ofdm downlink with time-correlated channels',
    'paper': 'https://arxiv.org/abs/1601.06241',
    'topic': 'distribution shift question answering'},
   {'title': 'lyman alpha emitting galaxies in the nearby universe',
    'paper': 'https://arxiv.org/abs/1505.07483',
    'topic': 'distribution shift question answering'},
   {'title': 'experimental round-robin differential phase-shift quantum key distribution',
    'paper': 'https://arxiv.org/abs/1505.08142',
    'topic': 'distribution shift question answering'},
   {'title': 'constraints on planet occurrence around nearby mid-to-late m dwarfs from the mearth project',
    'paper': 'https://arxiv.org/abs/1307.3178',
    'topic': 'distribution shift question answering'},
   {'title': 'x-ggm: graph generative modeling for out-of-distribution generalization in visual question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3474085.3475350',
    'topic': 'distribution shift question answering'},
   {'title': 'question rewriting for conversational question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3437963.3441748',
    'topic': 'distribution shift question answering'},
   {'title': 'passage similarity and diversification in non-factoid question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3471158.3472249',
    'topic': 'distribution shift question answering'},
   {'title': 'conversational question answering over passages by leveraging word proximity networks',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3397271.3401399',
    'topic': 'distribution shift question answering'},
   {'title': 'adapting visual question answering models for enhancing multimodal community q&a platforms',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3357384.3358000',
    'topic': 'distribution shift question answering'},
   {'title': 'select, substitute, search: a new benchmark for knowledge-augmented visual question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3404835.3463259',
    'topic': 'distribution shift question answering'},
   {'title': 'sanitizing synthetic training data generation for question answering over knowledge graphs',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3409256.3409836',
    'topic': 'distribution shift question answering'},
   {'title': 'naranjo question answering using end-to-end multi-task learning model',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3292500.3330770',
    'topic': 'distribution shift question answering'},
   {'title': 'meaningful answer generation of e-commerce question-answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3432689',
    'topic': 'distribution shift question answering'},
   {'title': 'attentive history selection for conversational question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3357384.3357905',
    'topic': 'distribution shift question answering'},
   {'title': 'answer interaction in non-factoid question answering systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3295750.3298946',
    'topic': 'distribution shift question answering'},
   {'title': 'product-aware answer generation in e-commerce question-answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3289600.3290992',
    'topic': 'distribution shift question answering'},
   {'title': 'a discourse-based approach for arabic question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2988238',
    'topic': 'distribution shift question answering'},
   {'title': 'verification of the expected answer type for biomedical question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3184558.3191542',
    'topic': 'distribution shift question answering'},
   {'title': 'spatiotemporal-textual co-attention network for video question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3320061',
    'topic': 'distribution shift question answering'},
   {'title': 'quantifying human-perceived answer utility in non-factoid question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3406522.3446028',
    'topic': 'distribution shift question answering'},
   {'title': 'answer ranking based on named entity types for question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3022227.3022297',
    'topic': 'distribution shift question answering'},
   {'title': 'adversarial learning of answer-related representation for visual question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3269206.3271765',
    'topic': 'distribution shift question answering'},
   {'title': 'video question answering via knowledge-based progressive spatial-temporal attention network',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3321505',
    'topic': 'distribution shift question answering'},
   {'title': 'opinion-aware answer generation for review-driven question answering in e-commerce',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3340531.3411904',
    'topic': 'distribution shift question answering'},
   {'title': 'xalgo: a design probe of explaining algorithms’ internal states via question-answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3397481.3450676',
    'topic': 'distribution shift question answering'},
   {'title': 'scaling up online question answering via similar question retrieval',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2876034.2893428',
    'topic': 'distribution shift question answering'},
   {'title': 'cross-domain knowledge distillation for retrieval-based question answering systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3442381.3449814',
    'topic': 'distribution shift question answering'},
   {'title': 'distributed deep learning for question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2983323.2983377',
    'topic': 'distribution shift question answering'},
   {'title': 'a non-factoid question-answering taxonomy',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3477495.3531926',
    'topic': 'distribution shift question answering'},
   {'title': 'social question answering: textual, user, and network features for best answer prediction',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2948063',
    'topic': 'distribution shift question answering'},
   {'title': 'automatically extracting high-quality negative examples for answer selection in question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3077136.3080645',
    'topic': 'distribution shift question answering'},
   {'title': 'dynamic graph reasoning for conversational open-domain question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3498557',
    'topic': 'distribution shift question answering'},
   {'title': 'conversational question answering on heterogeneous sources',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3477495.3531815',
    'topic': 'distribution shift question answering'},
   {'title': 'open-retrieval conversational question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3397271.3401110',
    'topic': 'distribution shift question answering'},
   {'title': 'fast parameter adaptation for few-shot image captioning and visual question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3240508.3240527',
    'topic': 'distribution shift question answering'},
   {'title': 'a corpus for hybrid question answering systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3184558.3191540',
    'topic': 'distribution shift question answering'},
   {'title': 'explainable conversational question answering over heterogeneous sources',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3477495.3531688',
    'topic': 'distribution shift question answering'},
   {'title': 'temporal question answering in news article collections',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3487553.3526023',
    'topic': 'distribution shift question answering'},
   {'title': 'asking for help in community question-answering: the goal-framing effect of question expression on response networks',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3529372.3533287',
    'topic': 'distribution shift question answering'},
   {'title': 'complex temporal question answering on knowledge graphs',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3459637.3482416',
    'topic': 'distribution shift question answering'},
   {'title': 'qanswer: towards question answering search over websites',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3487553.3524250',
    'topic': 'distribution shift question answering'},
   {'title': 'semantic question answering on big data',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2928294.2928302',
    'topic': 'distribution shift question answering'},
   {'title': 'a chinese knowledge base question answering system',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3459637.3481970',
    'topic': 'distribution shift question answering'},
   {'title': 'knowledge graph embedding based question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3289600.3290956',
    'topic': 'distribution shift question answering'},
   {'title': 'duplicate detection in programming question answering communities',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3169795',
    'topic': 'distribution shift question answering'},
   {'title': 'a factoid question answering system for vietnamese',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3184558.3191535',
    'topic': 'distribution shift question answering'},
   {'title': 'humor detection in product question answering systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3397271.3401077',
    'topic': 'distribution shift question answering'},
   {'title': 'exploring diversification in non-factoid question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3234944.3234973',
    'topic': 'distribution shift question answering'},
   {'title': 'designing a question-answering system for comic contents',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3011549.3011554',
    'topic': 'distribution shift question answering'},
   {'title': 'performance prediction for non-factoid question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3341981.3344249',
    'topic': 'distribution shift question answering'},
   {'title': 'non-factoid question answering in the legal domain',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3331184.3331431',
    'topic': 'distribution shift question answering'},
   {'title': 'natural language question answering in the financial domain',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3291291.3291311',
    'topic': 'distribution shift question answering'},
   {'title': 'more accurate question answering on freebase',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2806416.2806472',
    'topic': 'distribution shift question answering'},
   {'title': 'table cell search for question answering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2872427.2883080',
    'topic': 'distribution shift question answering'},
   {'title': 'the effect of natural distribution shift on question answering models',
    'paper': 'https://arxiv.org/pdf/2004.14444.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'a survey of causality in visual question answering',
    'paper': 'https://gaoxiangluo.github.io/files/A_Survey_of_Causality_in_Visual_Question_Answering.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'learning neural models for natural language processing in the face of distributional shift',
    'paper': 'https://arxiv.org/pdf/2109.01558.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'empirical or invariant risk minimization? a sample complexity perspective',
    'paper': 'https://arxiv.org/pdf/2010.16412.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'l g ] 9 n ov 2 01 8 density estimation for shift-invariant multidimensional distributions',
    'paper': 'http://export.arxiv.org/pdf/1811.03744',
    'topic': 'distribution shift question answering'},
   {'title': 'grit: general robust image task benchmark',
    'paper': 'https://arxiv.org/pdf/2204.13653.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'qagan: adversarial approach to learning domain invariant language features',
    'paper': 'https://arxiv.org/pdf/2206.12388.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'active learning over multiple domains in natural language tasks',
    'paper': 'https://arxiv.org/pdf/2202.00254.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'a sample complexity perspective',
    'paper': 'https://openreview.net/pdf?id=jrA5GAccy_',
    'topic': 'distribution shift question answering'},
   {'title': 'how good are deep models in understanding the generated images?',
    'paper': 'https://arxiv.org/pdf/2208.10760.pdf',
    'topic': 'distribution shift question answering'},
   {'title': 'robustness in machine learning - jerry li',
    'paper': 'https://jerryzli.github.io/robust-ml-fall19.html',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust ml',
    'paper': 'https://www.robust-ml.org/',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning models and their applications',
    'paper': 'https://dspace.mit.edu/handle/1721.1/130760',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning - data analytics and ... - tum',
    'paper': 'https://www.cs.cit.tum.de/daml/forschung/robust-machine-learning/',
    'topic': 'Robust Machine Learning'},
   {'title': 'what is the definition of the robustness of a machine learning ...',
    'paper': 'https://www.researchgate.net/post/What_is_the_definition_of_the_robustness_of_a_machine_learning_algorithm',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust intelligence',
    'paper': 'https://www.robustintelligence.com/',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning | the alan turing institute',
    'paper': 'https://www.turing.ac.uk/research/interest-groups/robust-machine-learning',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning systems: reliability and security for ...',
    'paper': 'https://ieeexplore.ieee.org/document/8474192',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine comprehension models via adversarial ...',
    'paper': 'https://aclanthology.org/N18-2091',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust distant supervision relation extraction via deep ...',
    'paper': 'https://aclanthology.org/P18-1199',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards robust neural machine translation - acl anthology',
    'paper': 'https://aclanthology.org/P18-1163',
    'topic': 'Robust Machine Learning'},
   {'title': 'trainable, scalable summarization using ... - acl anthology',
    'paper': 'https://aclanthology.org/C98-1009.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'learning robust representations of text - acl anthology',
    'paper': 'https://aclanthology.org/D16-1207.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust learning, smoothing, and parameter tying on ...',
    'paper': 'https://aclanthology.org/J95-3002.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine reading comprehension by learning soft ...',
    'paper': 'https://aclanthology.org/2020.coling-main.248',
    'topic': 'Robust Machine Learning'},
   {'title': 'evaluating neural model robustness for machine ...',
    'paper': 'https://aclanthology.org/2021.eacl-main.210.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'improving robustness of neural machine translation with ...',
    'paper': 'https://aclanthology.org/W19-5368',
    'topic': 'Robust Machine Learning'},
   {'title': 'learning to reweight examples for robust deep learning',
    'paper': 'https://proceedings.mlr.press/v80/ren18a/ren18a.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust learning under uncertain test distributions: relating ...',
    'paper': 'http://proceedings.mlr.press/v32/wen14.html',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust reinforcement learning: a constrained game ...',
    'paper': 'https://proceedings.mlr.press/v144/yu21a.html',
    'topic': 'Robust Machine Learning'},
   {'title': 'overfitting in adversarially robust deep learning',
    'paper': 'http://proceedings.mlr.press/v119/rice20a/rice20a.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust deep learning as optimal control: insights and ...',
    'paper': 'http://proceedings.mlr.press/v120/seidman20a/seidman20a.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'selfie: refurbishing unclean samples for robust deep ...',
    'paper': 'https://proceedings.mlr.press/v97/song19b.html',
    'topic': 'Robust Machine Learning'},
   {'title': 'minimax regret optimization for robust machine learning ...',
    'paper': 'https://proceedings.mlr.press/v178/agarwal22b.html',
    'topic': 'Robust Machine Learning'},
   {'title': 'improving robustness of deep-learning-based image ...',
    'paper': 'https://proceedings.mlr.press/v119/raj20a.html',
    'topic': 'Robust Machine Learning'},
   {'title': 'efficient and robust automated machine learning',
    'paper': 'https://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust reinforcement learning',
    'paper': 'https://papers.nips.cc/paper/1841-robust-reinforcement-learning.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'a closer look at accuracy vs. robustness',
    'paper': 'https://papers.nips.cc/paper/2020/file/61d77652c97ef636343742fc3dcf3ba9-Paper.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'provably robust deep learning via adversarially trained ...',
    'paper': 'https://papers.nips.cc/paper/9307-provably-robust-deep-learning-via-adversarially-trained-smoothed-classifiers.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust reinforcement learning via adversarial training with ...',
    'paper': 'https://papers.nips.cc/paper/2020/file/5cb0e249689cd6d8369c4885435a56c2-Paper.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robustness of classifiers: from adversarial to random noise',
    'paper': 'http://papers.nips.cc/paper/6331-robustness-of-classifiers-from-adversarial-to-random-noise.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'boundary thickness and robustness in learning models',
    'paper': 'https://papers.nips.cc/paper/2020/file/44e76e99b5e194377e955b13fb12f630-Paper.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'a causal view on robustness of neural networks',
    'paper': 'https://papers.nips.cc/paper/2020/file/02ed812220b0705fabb868ddbf17ea20-Paper.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust reinforcement learning as a stackelberg game via ...',
    'paper': 'https://www.ijcai.org/proceedings/2022/0430.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'global robustness evaluation of deep neural networks with ...',
    'paper': 'https://www.ijcai.org/proceedings/2019/0824.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'improving the robustness of deep neural networks ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2019/403',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust reinforcement learning as a stackelberg ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2022/430',
    'topic': 'Robust Machine Learning'},
   {'title': 'on guaranteed optimal robust explanations for nlp models',
    'paper': 'https://www.ijcai.org/proceedings/2021/366',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust learning from noisy side-information by semidefinite ...',
    'paper': 'https://www.ijcai.org/proceedings/2019/349',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards accurate and robust domain adaptation under ...',
    'paper': 'https://www.ijcai.org/proceedings/2020/0314.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'high-robustness, low-transferability fingerprinting of neural ...',
    'paper': 'https://www.ijcai.org/proceedings/2021/0080.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'on guaranteed optimal robust explanations for nlp ... - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2021/0366.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards robust resnet: a small step but a giant leap - ijcai',
    'paper': 'https://www.ijcai.org/proceedings/2019/595',
    'topic': 'Robust Machine Learning'},
   {'title': 'learning perturbation sets for robust ma',
    'paper': 'https://openreview.net/pdf?id=MIDckA56aD',
    'topic': 'Robust Machine Learning'},
   {'title': 'analyzing the robustness of open-world machine learning.',
    'paper': 'https://openreview.net/forum?id=laa530q5gUR',
    'topic': 'Robust Machine Learning'},
   {'title': 'card: certifiably robust machine learning pipeline via ...',
    'paper': 'https://openreview.net/forum?id=roaZrQMGsd6&referrer=%5Bthe%20profile%20of%20Bo%20Li%5D(%2Fprofile%3Fid%3D~Bo_Li19)',
    'topic': 'Robust Machine Learning'},
   {'title': 'sample selection for fair and robust training - openreview',
    'paper': 'https://openreview.net/pdf?id=IZNR0RDtGp3',
    'topic': 'Robust Machine Learning'},
   {'title': 'robustness between the worst and average case - nips papers',
    'paper': 'https://openreview.net/pdf?id=Y8YqrYeFftd',
    'topic': 'Robust Machine Learning'},
   {'title': 'machine learning explainability and robustness - openreview',
    'paper': 'https://openreview.net/forum?id=REwtJ_Af00Z',
    'topic': 'Robust Machine Learning'},
   {'title': 'secure byzantine-robust machine learning | openreview',
    'paper': 'https://openreview.net/forum?id=69EFStdgTD2&referrer=%5Bthe%20profile%20of%20Lie%20He%5D(%2Fprofile%3Fid%3D~Lie_He1)',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust deep reinforcement learning through adversarial loss',
    'paper': 'https://openreview.net/forum?id=eaAM_bdW0Q',
    'topic': 'Robust Machine Learning'},
   {'title': '[2101.02559] robust machine learning systems - arxiv',
    'paper': 'https://arxiv.org/abs/2101.02559',
    'topic': 'Robust Machine Learning'},
   {'title': '[2112.00639] robustness in deep learning for computer vision',
    'paper': 'https://arxiv.org/abs/2112.00639',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning approach for predicting kinase ...',
    'paper': 'https://arxiv.org/abs/2111.08008',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards efficient data-centric robust machine learning with ...',
    'paper': 'https://arxiv.org/abs/2203.03810',
    'topic': 'Robust Machine Learning'},
   {'title': 'why robust generalization in deep learning is difficult - arxiv',
    'paper': 'http://arxiv.org/abs/2205.13863',
    'topic': 'Robust Machine Learning'},
   {'title': 'rethinking machine learning robustness via its link with the ...',
    'paper': 'https://arxiv.org/abs/2202.08944',
    'topic': 'Robust Machine Learning'},
   {'title': 'sample-efficient training of robust deep learning models',
    'paper': 'https://arxiv.org/abs/2112.02542',
    'topic': 'Robust Machine Learning'},
   {'title': 'when doubly robust methods meet machine learning ... - arxiv',
    'paper': 'https://arxiv.org/abs/2204.10969',
    'topic': 'Robust Machine Learning'},
   {'title': '[2202.05395] robust, deep, and reinforcement learning for ...',
    'paper': 'https://arxiv.org/abs/2202.05395',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust learning from observation with model misspecification',
    'paper': 'https://arxiv.org/abs/2202.06003',
    'topic': 'Robust Machine Learning'},
   {'title': 'neural network for determining an asteroid mineral composition from reflectance spectra',
    'paper': 'https://arxiv.org/abs/2210.01006',
    'topic': 'Robust Machine Learning'},
   {'title': 'understanding adversarial robustness against on-manifold adversarial examples',
    'paper': 'https://arxiv.org/abs/2210.00430',
    'topic': 'Robust Machine Learning'},
   {'title': 'learning-based design of luenberger observers for autonomous nonlinear systems',
    'paper': 'https://arxiv.org/abs/2210.01476',
    'topic': 'Robust Machine Learning'},
   {'title': 'interpretable option discovery using deep q-learning and variational autoencoders',
    'paper': 'https://arxiv.org/abs/2210.01231',
    'topic': 'Robust Machine Learning'},
   {'title': 'secoe: alleviating sensors failure in machine learning-coupled iot systems',
    'paper': 'https://arxiv.org/abs/2210.02144',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust fair clustering: a novel fairness attack and defense framework',
    'paper': 'https://arxiv.org/abs/2210.01953',
    'topic': 'Robust Machine Learning'},
   {'title': 'a closer look at robustness to l-infinity and spatial perturbations and their composition',
    'paper': 'https://arxiv.org/abs/2210.02577',
    'topic': 'Robust Machine Learning'},
   {'title': 'anomaly detection using data depth: multivariate case',
    'paper': 'https://arxiv.org/abs/2210.02851',
    'topic': 'Robust Machine Learning'},
   {'title': 'flow matching for generative modeling',
    'paper': 'https://arxiv.org/abs/2210.02747',
    'topic': 'Robust Machine Learning'},
   {'title': 'subspace learning for feature selection via rank revealing qr factorization: unsupervised and hybrid approaches with non-negative matrix factorization and evolutionary algorithm',
    'paper': 'https://arxiv.org/abs/2210.00418',
    'topic': 'Robust Machine Learning'},
   {'title': 'evaluation of physics constrained data-driven methods for turbulence model uncertainty quantification',
    'paper': 'https://arxiv.org/abs/2210.00002',
    'topic': 'Robust Machine Learning'},
   {'title': 'latent state marginalization as a low-cost approach for improving exploration',
    'paper': 'https://arxiv.org/abs/2210.00999',
    'topic': 'Robust Machine Learning'},
   {'title': 'differentiable parsing and visual grounding of verbal instructions for object placement',
    'paper': 'https://arxiv.org/abs/2210.00215',
    'topic': 'Robust Machine Learning'},
   {'title': 'random data augmentation based enhancement: a generalized enhancement approach for medical datasets',
    'paper': 'https://arxiv.org/abs/2210.00824',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust self-healing prediction model for high dimensional data',
    'paper': 'https://arxiv.org/abs/2210.01788',
    'topic': 'Robust Machine Learning'},
   {'title': 'strength-adaptive adversarial training',
    'paper': 'https://arxiv.org/abs/2210.01288',
    'topic': 'Robust Machine Learning'},
   {'title': 'feddig: robust federated learning using data digest to represent absent clients',
    'paper': 'https://arxiv.org/abs/2210.00737',
    'topic': 'Robust Machine Learning'},
   {'title': 'distributionally adaptive meta reinforcement learning',
    'paper': 'https://arxiv.org/abs/2210.03104',
    'topic': 'Robust Machine Learning'},
   {'title': 'blockchain-based monitoring for poison attack detection in decentralized federated learning',
    'paper': 'https://arxiv.org/abs/2210.02873',
    'topic': 'Robust Machine Learning'},
   {'title': 'ncvx: a general-purpose optimization solver for constrained machine and deep learning',
    'paper': 'https://arxiv.org/abs/2210.00973',
    'topic': 'Robust Machine Learning'},
   {'title': 'force-aware interface via electromyography for natural vr/ar interaction',
    'paper': 'https://arxiv.org/abs/2210.01225',
    'topic': 'Robust Machine Learning'},
   {'title': 'tikhonov regularization is optimal transport robust under martingale constraints',
    'paper': 'https://arxiv.org/abs/2210.01413',
    'topic': 'Robust Machine Learning'},
   {'title': 'multiguard: provably robust multi-label classification against adversarial examples',
    'paper': 'https://arxiv.org/abs/2210.01111',
    'topic': 'Robust Machine Learning'},
   {'title': 'unsupervised model selection for time-series anomaly detection',
    'paper': 'https://arxiv.org/abs/2210.01078',
    'topic': 'Robust Machine Learning'},
   {'title': 'perceptual attacks of no-reference image quality models with human-in-the-loop',
    'paper': 'https://arxiv.org/abs/2210.00933',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust $q$-learning algorithm for markov decision processes under wasserstein uncertainty',
    'paper': 'https://arxiv.org/abs/2210.00898',
    'topic': 'Robust Machine Learning'},
   {'title': 'stability via adversarial training of neural network stochastic control of mean-field type',
    'paper': 'https://arxiv.org/abs/2210.00874',
    'topic': 'Robust Machine Learning'},
   {'title': 'comparison of data representations and machine learning architectures for user identification on arbitrary motion sequences',
    'paper': 'https://arxiv.org/abs/2210.00527',
    'topic': 'Robust Machine Learning'},
   {'title': 'spectral augmentation for self-supervised learning on graphs',
    'paper': 'https://arxiv.org/abs/2210.00643',
    'topic': 'Robust Machine Learning'},
   {'title': 'causal estimation for text data with (apparent) overlap violations',
    'paper': 'https://arxiv.org/abs/2210.00079',
    'topic': 'Robust Machine Learning'},
   {'title': 'codedsi: differentiable code search',
    'paper': 'https://arxiv.org/abs/2210.00328',
    'topic': 'Robust Machine Learning'},
   {'title': 'solving practical multi-body dynamics problems using a single neural operator',
    'paper': 'https://arxiv.org/abs/2210.00222',
    'topic': 'Robust Machine Learning'},
   {'title': 'on attacking out-domain uncertainty estimation in deep neural networks',
    'paper': 'https://arxiv.org/abs/2210.02191',
    'topic': 'Robust Machine Learning'},
   {'title': 'stock volatility prediction using time series and deep learning approach',
    'paper': 'https://arxiv.org/abs/2210.02126',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust estimation of loss-based measures of model performance under covariate shift',
    'paper': 'https://arxiv.org/abs/2210.01980',
    'topic': 'Robust Machine Learning'},
   {'title': 'meta-ensemble parameter learning',
    'paper': 'https://arxiv.org/abs/2210.01973',
    'topic': 'Robust Machine Learning'},
   {'title': "tree mover's distance: bridging graph metrics and stability of graph neural networks",
    'paper': 'https://arxiv.org/abs/2210.01906',
    'topic': 'Robust Machine Learning'},
   {'title': 'bayesft: bayesian optimization for fault tolerant neural network architecture',
    'paper': 'https://arxiv.org/abs/2210.01795',
    'topic': 'Robust Machine Learning'},
   {'title': 'paging with succinct predictions',
    'paper': 'https://arxiv.org/abs/2210.02775',
    'topic': 'Robust Machine Learning'},
   {'title': "dynamical systems' based neural networks",
    'paper': 'https://arxiv.org/abs/2210.02373',
    'topic': 'Robust Machine Learning'},
   {'title': 'practical adversarial attacks on spatiotemporal traffic forecasting models',
    'paper': 'https://arxiv.org/abs/2210.02447',
    'topic': 'Robust Machine Learning'},
   {'title': 'chemalgebra: algebraic reasoning on chemical reactions',
    'paper': 'https://arxiv.org/abs/2210.02095',
    'topic': 'Robust Machine Learning'},
   {'title': 'null hypothesis test for anomaly detection',
    'paper': 'https://arxiv.org/abs/2210.02226',
    'topic': 'Robust Machine Learning'},
   {'title': 'rethinking lipschitz neural networks for certified l-infinity robustness',
    'paper': 'https://arxiv.org/abs/2210.01787',
    'topic': 'Robust Machine Learning'},
   {'title': 'learning robust kernel ensembles with kernel average pooling',
    'paper': 'https://arxiv.org/abs/2210.00062',
    'topic': 'Robust Machine Learning'},
   {'title': 'rap: risk-aware prediction for robust planning',
    'paper': 'https://arxiv.org/abs/2210.01368',
    'topic': 'Robust Machine Learning'},
   {'title': 'adaptive weight decay: on the fly weight decay tuning for improving robustness',
    'paper': 'https://arxiv.org/abs/2210.00094',
    'topic': 'Robust Machine Learning'},
   {'title': 'hip fracture prediction using the first principal component derived from fea-computed fracture loads',
    'paper': 'https://arxiv.org/abs/2210.01032',
    'topic': 'Robust Machine Learning'},
   {'title': 'uncertainty-aware predictions of molecular x-ray absorption spectra using neural network ensembles',
    'paper': 'https://arxiv.org/abs/2210.00336',
    'topic': 'Robust Machine Learning'},
   {'title': 'adversarial robustness of representation learning for knowledge graphs',
    'paper': 'https://arxiv.org/abs/2210.00122',
    'topic': 'Robust Machine Learning'},
   {'title': 'building robust machine learning systems: current progress, research challenges, and opportunities',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3316781.3323472',
    'topic': 'Robust Machine Learning'},
   {'title': 'building reproducible, reusable, and robust machine learning software',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3401025.3407941',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards lightweight and robust machine learning for cdn caching',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3286062.3286082',
    'topic': 'Robust Machine Learning'},
   {'title': 'a robust machine learning technique to predict low-performing students',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3277569',
    'topic': 'Robust Machine Learning'},
   {'title': 'energy-efficient and adversarially robust machine learning with selective dynamic band filtering',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3453688.3461756',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning-enabled routing for highly mobile vehicular networks with parrot in ns-3',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3460797.3460810',
    'topic': 'Robust Machine Learning'},
   {'title': 'the raise of machine learning hyperparameter constraints in python code',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3533767.3534400',
    'topic': 'Robust Machine Learning'},
   {'title': 'adversarial scrutiny of evidentiary statistical software',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3531146.3533228',
    'topic': 'Robust Machine Learning'},
   {'title': 'continuous lwe',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3406325.3451000',
    'topic': 'Robust Machine Learning'},
   {'title': 'rgrecsys: a toolkit for robustness evaluation of recommender systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3488560.3502192',
    'topic': 'Robust Machine Learning'},
   {'title': 'sentiment analysis using xlm-r transformer and zero-shot transfer learning on resource-poor indian language',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3461764',
    'topic': 'Robust Machine Learning'},
   {'title': 'power-attack: a comprehensive tool-chain for modeling and simulating attacks in power systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3470481.3472705',
    'topic': 'Robust Machine Learning'},
   {'title': 'discovering invariant and changing mechanisms from data',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3534678.3539479',
    'topic': 'Robust Machine Learning'},
   {'title': 'the road to explainability is paved with bias: measuring the fairness of explanations',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3531146.3533179',
    'topic': 'Robust Machine Learning'},
   {'title': 'predicting cognitive load in an emergency simulation based on behavioral and physiological measures',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3340555.3353735',
    'topic': 'Robust Machine Learning'},
   {'title': 'structack: structure-based adversarial attacks on graph neural networks',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3465336.3475110',
    'topic': 'Robust Machine Learning'},
   {'title': 'learning on the rings: self-supervised 3d finger motion tracking using wearable sensors',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3534587',
    'topic': 'Robust Machine Learning'},
   {'title': 'ensemble learning for effective run-time hardware-based malware detection: a comprehensive analysis and classification',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3195970.3196047',
    'topic': 'Robust Machine Learning'},
   {'title': 'web-based startup success prediction',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3269206.3272011',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust federated learning based on metrics learning and unsupervised clustering for malicious data detection',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3476883.3520221',
    'topic': 'Robust Machine Learning'},
   {'title': 'when video meets inertial sensors: zero-shot domain adaptation for finger motion analytics with inertial sensors',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3450268.3453537',
    'topic': 'Robust Machine Learning'},
   {'title': 'analyzing hardware based malware detectors',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3061639.3062202',
    'topic': 'Robust Machine Learning'},
   {'title': 'third workshop on adversarial learning methods for machine learning and data mining (advml 2021)',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3447548.3469455',
    'topic': 'Robust Machine Learning'},
   {'title': 'the fourth workshop on adversarial learning methods for machine learning and data mining (advml 2022)',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3534678.3542897',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust large-scale machine learning in the cloud',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2939672.2939790',
    'topic': 'Robust Machine Learning'},
   {'title': 'adversarial robustness in deep learning: from practices to theories',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3447548.3470812',
    'topic': 'Robust Machine Learning'},
   {'title': 'machine learning and data cleaning: which serves the other?',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3506712',
    'topic': 'Robust Machine Learning'},
   {'title': 'a robust mature tomato detection in greenhouse scenes using machine learning and color analysis',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3318299.3318338',
    'topic': 'Robust Machine Learning'},
   {'title': 'privacy risks of securing machine learning models against adversarial examples',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3319535.3354211',
    'topic': 'Robust Machine Learning'},
   {'title': 'fair, robust, and data-efficient machine learning in healthcare',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3514094.3539552',
    'topic': 'Robust Machine Learning'},
   {'title': 'machine learning @ amazon',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2778865.2778867',
    'topic': 'Robust Machine Learning'},
   {'title': 'debiased-cam to mitigate image perturbations with faithful visual explanations of machine learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3491102.3517522',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust high dimensional learning for lipschitz and convex losses.',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3455716.3455949',
    'topic': 'Robust Machine Learning'},
   {'title': 'constructivist design for interactive machine learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/2851581.2892547',
    'topic': 'Robust Machine Learning'},
   {'title': 'machine learning robustness, fairness, and their convergence',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3447548.3470799',
    'topic': 'Robust Machine Learning'},
   {'title': 'machine learning explainability and robustness: connected at the hip',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3447548.3470806',
    'topic': 'Robust Machine Learning'},
   {'title': 'using machine learning to detect cancer early',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3394486.3409553',
    'topic': 'Robust Machine Learning'},
   {'title': 'security engineering for machine learning (keynote)',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3416507.3428118',
    'topic': 'Robust Machine Learning'},
   {'title': 'trustworthy machine learning: fairness and robustness',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3488560.3502211',
    'topic': 'Robust Machine Learning'},
   {'title': 'hidden stratification causes clinically meaningful failures in machine learning for medical imaging',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3368555.3384468',
    'topic': 'Robust Machine Learning'},
   {'title': 'making machine learning robust against adversarial inputs',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3134599',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards a framework for validating machine learning results in medical imaging: opening the black box',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3332186.3332193',
    'topic': 'Robust Machine Learning'},
   {'title': 'a robust learning approach for regression models based on distributionally robust optimization',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3291125.3291138',
    'topic': 'Robust Machine Learning'},
   {'title': 'set-to-sequence methods in machine learning: a review',
    'paper': 'https://dl.acm.org/doi/pdf/10.1613/jair.1.12839',
    'topic': 'Robust Machine Learning'},
   {'title': 'machine learning in tourism',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3426826.3426837',
    'topic': 'Robust Machine Learning'},
   {'title': 'incorporating unlabeled data into distributionally-robust learning',
    'paper': 'https://dl.acm.org/doi/pdf/10.5555/3546258.3546314',
    'topic': 'Robust Machine Learning'},
   {'title': 'attacks and defenses towards machine learning based systems',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3207677.3277988',
    'topic': 'Robust Machine Learning'},
   {'title': 'appflow: using machine learning to synthesize robust, reusable ui tests',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3236024.3236055',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards robust production machine learning systems: managing dataset shift',
    'paper': 'https://dl.acm.org/doi/pdf/10.1145/3324884.3415281',
    'topic': 'Robust Machine Learning'},
   {'title': 'secure and robust machine learning for healthcare: a survey',
    'paper': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9153891',
    'topic': 'Robust Machine Learning'},
   {'title': 'learning perturbation sets for robust machine learning',
    'paper': 'https://arxiv.org/pdf/2007.08450.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning systems: challenges,current trends, perspectives, and the road ahead',
    'paper': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8979377',
    'topic': 'Robust Machine Learning'},
   {'title': 'secure byzantine-robust machine learning',
    'paper': 'https://arxiv.org/pdf/2006.04747.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'adversarially robust machine learning with guarantees',
    'paper': 'https://searchworks.stanford.edu/view/13974182',
    'topic': 'Robust Machine Learning'},
   {'title': 'towards deploying robust machine learning systems',
    'paper': 'https://doi.org/10.7936/P1G4-5433',
    'topic': 'Robust Machine Learning'},
   {'title': 'a robust machine learning framework for diabetes prediction',
    'paper': 'https://doi.org/10.1007/978-3-030-89880-9_58',
    'topic': 'Robust Machine Learning'},
   {'title': 'impact-learning: a robust machine learning algorithm',
    'paper': 'http://dl.acm.org/citation.cfm?id=3411185',
    'topic': 'Robust Machine Learning'},
   {'title': 'regularization helps with mitigating poisoning attacks: distributionally-robust machine learning using the wasserstein distance',
    'paper': 'https://arxiv.org/pdf/2001.10655.pdf',
    'topic': 'Robust Machine Learning'},
   {'title': 'robust machine learning for colorectal cancer risk prediction and stratification',
    'paper': 'https://www.ncbi.nlm.nih.gov/pubmed/33693381',
    'topic': 'Robust Machine Learning'}]}}