 Self-Play Fine-Tuning Converts Weak Language Models to Strong Language
ModelsInternational Conference on Machine Learning (ICML), 2024 |
 Direct Preference Optimization: Your Language Model is Secretly a Reward
ModelNeural Information Processing Systems (NeurIPS), 2023 |
 Tab-CoT: Zero-shot Tabular Chain of ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 Ziqi Jin Wei Lu |
 Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP), 2022 |
 Language Models are Multilingual Chain-of-Thought ReasonersInternational Conference on Learning Representations (ICLR), 2022 |
 Large Language Models are Zero-Shot ReasonersNeural Information Processing Systems (NeurIPS), 2022 |
 Self-Consistency Improves Chain of Thought Reasoning in Language ModelsInternational Conference on Learning Representations (ICLR), 2022 |
 Training language models to follow instructions with human feedbackNeural Information Processing Systems (NeurIPS), 2022 |
 GLM: General Language Model Pretraining with Autoregressive Blank
InfillingAnnual Meeting of the Association for Computational Linguistics (ACL), 2021 |
 Are NLP Models really able to Solve Simple Math Word Problems?North American Chapter of the Association for Computational Linguistics (NAACL), 2021 |
 Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit
Reasoning StrategiesTransactions of the Association for Computational Linguistics (TACL), 2021 |
 Language Models are Few-Shot LearnersNeural Information Processing Systems (NeurIPS), 2020 |
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