* update 2023-06-18 08:52:51

LLMs-papers.md

@@ -1,48 +1,48 @@
-1. [Cedille: A large autoregressive French language model](http://arxiv.org/abs/2202.03371v1)
-2. [How Good are Commercial Large Language Models on African Languages?](http://arxiv.org/abs/2305.06530v1)
-3. [A Precis of Language Models are not Models of Language](http://arxiv.org/abs/2205.07634v1)
-4. [Using large language models for (de-)formalization and natural
+1. [Lost in Translation: Large Language Models in Non-English Content
+  Analysis](http://arxiv.org/abs/2306.07377v1)
+2. [Cedille: A large autoregressive French language model](http://arxiv.org/abs/2202.03371v1)
+3. [How Good are Commercial Large Language Models on African Languages?](http://arxiv.org/abs/2305.06530v1)
+4. [A Precis of Language Models are not Models of Language](http://arxiv.org/abs/2205.07634v1)
+5. [Using large language models for (de-)formalization and natural
   argumentation exercises for beginner's students](http://arxiv.org/abs/2304.06186v1)
-5. [Should we Stop Training More Monolingual Models, and Simply Use Machine
+6. [Should we Stop Training More Monolingual Models, and Simply Use Machine
   Translation Instead?](http://arxiv.org/abs/2104.10441v1)
-6. [Beyond the limitations of any imaginable mechanism: large language
+7. [Beyond the limitations of any imaginable mechanism: large language
   models and psycholinguistics](http://arxiv.org/abs/2303.00077v1)
-7. [Enhance Reasoning Ability of Visual-Language Models via Large Language
+8. [Enhance Reasoning Ability of Visual-Language Models via Large Language
   Models](http://arxiv.org/abs/2305.13267v1)
-8. [Images in Language Space: Exploring the Suitability of Large Language
+9. [Images in Language Space: Exploring the Suitability of Large Language
   Models for Vision & Language Tasks](http://arxiv.org/abs/2305.13782v1)
-9. [When Being Unseen from mBERT is just the Beginning: Handling New
+10. [When Being Unseen from mBERT is just the Beginning: Handling New
   Languages With Multilingual Language Models](http://arxiv.org/abs/2010.12858v2)
-10. [Dynamic Fusion: Attentional Language Model for Neural Machine
+11. [Dynamic Fusion: Attentional Language Model for Neural Machine
   Translation](http://arxiv.org/abs/1909.04879v1)
-11. [Large Language Models are not Models of Natural Language: they are
+12. [Large Language Models are not Models of Natural Language: they are
   Corpus Models](http://arxiv.org/abs/2112.07055v2)
-12. [BigTrans: Augmenting Large Language Models with Multilingual Translation
+13. [BigTrans: Augmenting Large Language Models with Multilingual Translation
   Capability over 100 Languages](http://arxiv.org/abs/2305.18098v1)
-13. [Re-visiting Automated Topic Model Evaluation with Large Language Models](http://arxiv.org/abs/2305.12152v1)
-14. [Unsupervised Improvement of Factual Knowledge in Language Models](http://arxiv.org/abs/2304.01597v1)
-15. [UIO at SemEval-2023 Task 12: Multilingual fine-tuning for sentiment
+14. [Re-visiting Automated Topic Model Evaluation with Large Language Models](http://arxiv.org/abs/2305.12152v1)
+15. [Unsupervised Improvement of Factual Knowledge in Language Models](http://arxiv.org/abs/2304.01597v1)
+16. [UIO at SemEval-2023 Task 12: Multilingual fine-tuning for sentiment
   classification in low-resource languages](http://arxiv.org/abs/2304.14189v1)
-16. [Multilingual Text Classification for Dravidian Languages](http://arxiv.org/abs/2112.01705v1)
-17. [Can Large Language Models design a Robot?](http://arxiv.org/abs/2303.15324v1)
-18. [Jigsaw: Large Language Models meet Program Synthesis](http://arxiv.org/abs/2112.02969v1)
-19. [HinFlair: pre-trained contextual string embeddings for pos tagging and
+17. [Multilingual Text Classification for Dravidian Languages](http://arxiv.org/abs/2112.01705v1)
+18. [Can Large Language Models design a Robot?](http://arxiv.org/abs/2303.15324v1)
+19. [Jigsaw: Large Language Models meet Program Synthesis](http://arxiv.org/abs/2112.02969v1)
+20. [HinFlair: pre-trained contextual string embeddings for pos tagging and
   text classification in the Hindi language](http://arxiv.org/abs/2101.06949v1)
-20. [Larger-Scale Transformers for Multilingual Masked Language Modeling](http://arxiv.org/abs/2105.00572v1)
-21. [Exploring Cross-lingual Textual Style Transfer with Large Multilingual
+21. [Larger-Scale Transformers for Multilingual Masked Language Modeling](http://arxiv.org/abs/2105.00572v1)
+22. [Exploring Cross-lingual Textual Style Transfer with Large Multilingual
   Language Models](http://arxiv.org/abs/2206.02252v1)
-22. [Low-Resource Language Modelling of South African Languages](http://arxiv.org/abs/2104.00772v1)
-23. [In What Languages are Generative Language Models the Most Formal?
+23. [Low-Resource Language Modelling of South African Languages](http://arxiv.org/abs/2104.00772v1)
+24. [In What Languages are Generative Language Models the Most Formal?
   Analyzing Formality Distribution across Languages](http://arxiv.org/abs/2302.12299v1)
-24. [LEALLA: Learning Lightweight Language-agnostic Sentence Embeddings with
+25. [LEALLA: Learning Lightweight Language-agnostic Sentence Embeddings with
   Knowledge Distillation](http://arxiv.org/abs/2302.08387v1)
-25. [Reimagining Retrieval Augmented Language Models for Answering Queries](http://arxiv.org/abs/2306.01061v1)
-26. [Benchmarking Language Models for Code Syntax Understanding](http://arxiv.org/abs/2210.14473v1)
-27. [Can Character-based Language Models Improve Downstream Task Performance
+26. [Reimagining Retrieval Augmented Language Models for Answering Queries](http://arxiv.org/abs/2306.01061v1)
+27. [Benchmarking Language Models for Code Syntax Understanding](http://arxiv.org/abs/2210.14473v1)
+28. [Can Character-based Language Models Improve Downstream Task Performance
   in Low-Resource and Noisy Language Scenarios?](http://arxiv.org/abs/2110.13658v1)
-28. [Learning Translation Quality Evaluation on Low Resource Languages from
+29. [Learning Translation Quality Evaluation on Low Resource Languages from
   Large Language Models](http://arxiv.org/abs/2302.03491v1)
-29. [Investigating the Translation Performance of a Large Multilingual
+30. [Investigating the Translation Performance of a Large Multilingual
   Language Model: the Case of BLOOM](http://arxiv.org/abs/2303.01911v2)
-30. [Investigating Robustness of Dialog Models to Popular Figurative Language
-  Constructs](http://arxiv.org/abs/2110.00687v1)