Update references.bib

MLLM_latex/chapter10/references.bib

@@ -112,4 +112,246 @@ @incollection{rosenstrauch2023artificial
   pages={225--239},
   year={2023},
   publisher={Springer}
-}
+}
+
+
+@article{xu2024survey,
+  title={A Survey on Multilingual Large Language Models: Corpora, Alignment, and Bias},
+  author={Xu, Yuemei and Hu, Ling and Zhao, Jiayi and Qiu, Zihan and Ye, Yuqi and Gu, Hanwen},
+  journal={arXiv preprint arXiv:2404.00929},
+  year={2024}
+}
+
+@article{basta2022gender,
+  title={Gender bias in natural language processing},
+  author={Basta, Christine Raouf Saad},
+  year={2022},
+  publisher={Universitat Polit{\`e}cnica de Catalunya}
+}
+
+
+@article{magesh2024hallucination,
+  title={Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools},
+  author={Magesh, Varun and Surani, Faiz and Dahl, Matthew and Suzgun, Mirac and Manning, Christopher D and Ho, Daniel E},
+  journal={arXiv preprint arXiv:2405.20362},
+  year={2024}
+}
+
+@article{cegin2024effects,
+  title={Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation},
+  author={Cegin, Jan and Pecher, Branislav and Simko, Jakub and Srba, Ivan and Bielikova, Maria and Brusilovsky, Peter},
+  journal={arXiv preprint arXiv:2401.06643},
+  year={2024}
+}
+
+@article{lin2024investigating,
+  title={Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception},
+  author={Lin, Luyang and Wang, Lingzhi and Guo, Jinsong and Wong, Kam-Fai},
+  journal={arXiv preprint arXiv:2403.14896},
+  year={2024}
+}
+
+@article{owens2024multi,
+  title={A Multi-LLM Debiasing Framework},
+  author={Owens, Deonna M and Rossi, Ryan A and Kim, Sungchul and Yu, Tong and Dernoncourt, Franck and Chen, Xiang and Zhang, Ruiyi and Gu, Jiuxiang and Deilamsalehy, Hanieh and Lipka, Nedim},
+  journal={arXiv preprint arXiv:2409.13884},
+  year={2024}
+}
+
+@article{patil2024review,
+  title={A review of current trends, techniques, and challenges in large language models (llms)},
+  author={Patil, Rajvardhan and Gudivada, Venkat},
+  journal={Applied Sciences},
+  volume={14},
+  number={5},
+  pages={2074},
+  year={2024},
+  publisher={MDPI}
+}
+
+@article{jiao2024navigating,
+  title={Navigating llm ethics: Advancements, challenges, and future directions},
+  author={Jiao, Junfeng and Afroogh, Saleh and Xu, Yiming and Phillips, Connor},
+  journal={arXiv preprint arXiv:2406.18841},
+  year={2024}
+}
+
+@article{poulain2024bias,
+  title={Bias patterns in the application of LLMs for clinical decision support: A comprehensive study},
+  author={Poulain, Raphael and Fayyaz, Hamed and Beheshti, Rahmatollah},
+  journal={arXiv preprint arXiv:2404.15149},
+  year={2024}
+}
+
+@article{chen2023ai,
+  title={AI fairness in data management and analytics: A review on challenges, methodologies and applications},
+  author={Chen, Pu and Wu, Linna and Wang, Lei},
+  journal={Applied Sciences},
+  volume={13},
+  number={18},
+  pages={10258},
+  year={2023},
+  publisher={MDPI}
+}
+
+@article{mehrabi2021survey,
+  title={A survey on bias and fairness in machine learning},
+  author={Mehrabi, Ninareh and Morstatter, Fred and Saxena, Nripsuta and Lerman, Kristina and Galstyan, Aram},
+  journal={ACM computing surveys (CSUR)},
+  volume={54},
+  number={6},
+  pages={1--35},
+  year={2021},
+  publisher={ACM New York, NY, USA}
+}
+
+@article{tripathi2024insaaf,
+  title={InSaAF: Incorporating Safety through Accuracy and Fairness| Are LLMs ready for the Indian Legal Domain?},
+  author={Tripathi, Yogesh and Donakanti, Raghav and Girhepuje, Sahil and Kavathekar, Ishan and Vedula, Bhaskara Hanuma and Krishnan, Gokul S and Goyal, Shreya and Goel, Anmol and Ravindran, Balaraman and Kumaraguru, Ponnurangam},
+  journal={arXiv preprint arXiv:2402.10567},
+  year={2024}
+}
+
+@article{lee2024life,
+  title={The Life Cycle of Large Language Models: A Review of Biases in Education},
+  author={Lee, Jinsook and Hicke, Yann and Yu, Renzhe and Brooks, Christopher and Kizilcec, Ren{\'e} F},
+  journal={arXiv preprint arXiv:2407.11203},
+  year={2024}
+}
+
+@inproceedings{brown2022does,
+  title={What does it mean for a language model to preserve privacy?},
+  author={Brown, Hannah and Lee, Katherine and Mireshghallah, Fatemehsadat and Shokri, Reza and Tram{\`e}r, Florian},
+  booktitle={Proceedings of the 2022 ACM conference on fairness, accountability, and transparency},
+  pages={2280--2292},
+  year={2022}
+}
+
+@article{yao2024survey,
+  title={A survey on large language model (llm) security and privacy: The good, the bad, and the ugly},
+  author={Yao, Yifan and Duan, Jinhao and Xu, Kaidi and Cai, Yuanfang and Sun, Zhibo and Zhang, Yue},
+  journal={High-Confidence Computing},
+  pages={100211},
+  year={2024},
+  publisher={Elsevier}
+}
+
+@inproceedings{pan2020privacy,
+  title={Privacy risks of general-purpose language models},
+  author={Pan, Xudong and Zhang, Mi and Ji, Shouling and Yang, Min},
+  booktitle={2020 IEEE Symposium on Security and Privacy (SP)},
+  pages={1314--1331},
+  year={2020},
+  organization={IEEE}
+}
+
+@article{weidinger2021ethical,
+  title={Ethical and social risks of harm from language models},
+  author={Weidinger, Laura and Mellor, John and Rauh, Maribeth and Griffin, Conor and Uesato, Jonathan and Huang, Po-Sen and Cheng, Myra and Glaese, Mia and Balle, Borja and Kasirzadeh, Atoosa and others},
+  journal={arXiv preprint arXiv:2112.04359},
+  year={2021}
+}
+
+@inproceedings{brown2022does,
+  title={What does it mean for a language model to preserve privacy?},
+  author={Brown, Hannah and Lee, Katherine and Mireshghallah, Fatemehsadat and Shokri, Reza and Tram{\`e}r, Florian},
+  booktitle={Proceedings of the 2022 ACM conference on fairness, accountability, and transparency},
+  pages={2280--2292},
+  year={2022}
+}
+
+@article{zhang2024right,
+  title={Right to be forgotten in the era of large language models: Implications, challenges, and solutions},
+  author={Zhang, Dawen and Finckenberg-Broman, Pamela and Hoang, Thong and Pan, Shidong and Xing, Zhenchang and Staples, Mark and Xu, Xiwei},
+  journal={AI and Ethics},
+  pages={1--10},
+  year={2024},
+  publisher={Springer}
+}
+
+@inproceedings{weidinger2022taxonomy,
+  title={Taxonomy of risks posed by language models},
+  author={Weidinger, Laura and Uesato, Jonathan and Rauh, Maribeth and Griffin, Conor and Huang, Po-Sen and Mellor, John and Glaese, Amelia and Cheng, Myra and Balle, Borja and Kasirzadeh, Atoosa and others},
+  booktitle={Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency},
+  pages={214--229},
+  year={2022}
+}
+
+@article{weidinger2021ethical,
+  title={Ethical and social risks of harm from language models},
+  author={Weidinger, Laura and Mellor, John and Rauh, Maribeth and Griffin, Conor and Uesato, Jonathan and Huang, Po-Sen and Cheng, Myra and Glaese, Mia and Balle, Borja and Kasirzadeh, Atoosa and others},
+  journal={arXiv preprint arXiv:2112.04359},
+  year={2021}
+}
+
+@article{kibriya2024privacy,
+  title={Privacy issues in Large Language Models: A survey},
+  author={Kibriya, Hareem and Khan, Wazir Zada and Siddiqa, Ayesha and Khan, Muhammad Khurrum},
+  journal={Computers and Electrical Engineering},
+  volume={120},
+  pages={109698},
+  year={2024},
+  publisher={Elsevier}
+}
+
+@incollection{phattanaviroj2024data,
+  title={Data Ethics and Privacy},
+  author={Phattanaviroj, Thanaporn and Moslehpour, Massoud and Walawalkar, Ankita Manohar},
+  booktitle={Challenges in Large Language Model Development and AI Ethics},
+  pages={321--353},
+  year={2024},
+  publisher={IGI Global}
+}
+
+@article{sanderson2023ai,
+  title={AI ethics principles in practice: Perspectives of designers and developers},
+  author={Sanderson, Conrad and Douglas, David and Lu, Qinghua and Schleiger, Emma and Whittle, Jon and Lacey, Justine and Newnham, Glenn and Hajkowicz, Stefan and Robinson, Cathy and Hansen, David},
+  journal={IEEE Transactions on Technology and Society},
+  volume={4},
+  number={2},
+  pages={171--187},
+  year={2023},
+  publisher={IEEE}
+}
+
+@article{singh2024whispered,
+  title={Whispered tuning: Data privacy preservation in fine-tuning llms through differential privacy},
+  author={Singh, Tanmay and Aditya, Harshvardhan and Madisetti, Vijay K and Bahga, Arshdeep},
+  journal={Journal of Software Engineering and Applications},
+  volume={17},
+  number={1},
+  pages={1--22},
+  year={2024},
+  publisher={Scientific Research Publishing}
+}
+
+@article{charles2024fine,
+  title={Fine-Tuning Large Language Models with User-Level Differential Privacy},
+  author={Charles, Zachary and Ganesh, Arun and McKenna, Ryan and McMahan, H Brendan and Mitchell, Nicole and Pillutla, Krishna and Rush, Keith},
+  journal={arXiv preprint arXiv:2407.07737},
+  year={2024}
+}
+
+@inproceedings{kuang2024federatedscope,
+  title={Federatedscope-llm: A comprehensive package for fine-tuning large language models in federated learning},
+  author={Kuang, Weirui and Qian, Bingchen and Li, Zitao and Chen, Daoyuan and Gao, Dawei and Pan, Xuchen and Xie, Yuexiang and Li, Yaliang and Ding, Bolin and Zhou, Jingren},
+  booktitle={Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
+  pages={5260--5271},
+  year={2024}
+}
+
+@article{wiest2024anonymizing,
+  title={Anonymizing medical documents with local, privacy preserving large language models: The LLM-Anonymizer},
+  author={Wiest, Isabella C and Lessmann, Marie-Elisabeth and Wolf, Fabian and Ferber, Dyke and Van Treeck, Marko and Zhu, Jiefu and Ebert, Matthias P and Westphalen, Christoph Benedikt and Wermke, Martin and Kather, Jakob Nikolas},
+  journal={medRxiv},
+  pages={2024--06},
+  year={2024},
+  publisher={Cold Spring Harbor Laboratory Press}
+}
+
+@article{li2024llm,
+  title={LLM-PBE: Assessing Data Privacy in Large Language Models},
+  author={Li, Qinbin and Hong, Junyuan and Xie, Chulin and Tan, Jeffrey and Xin, Rachel and Hou, Junyi and Yin, Xavier and Wang, Zhun and Hendrycks, Dan and Wang, Zhangyang and others},
+  journal={arXiv preprint arXiv:2408.12787},
+  year={2024}
+}