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 GRATH: Gradual Self-Truthifying for Large Language ModelsInternational Conference on Machine Learning (ICML), 2024 |
 WARM: On the Benefits of Weight Averaged Reward ModelsInternational Conference on Machine Learning (ICML), 2024 Alexandre Ramé Nino Vieillard Léonard Hussenot Robert Dadashi Geoffrey Cideron Olivier Bachem Johan Ferret |
 ReFT: Reasoning with Reinforced Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL), 2024 |
 A Minimaximalist Approach to Reinforcement Learning from Human FeedbackInternational Conference on Machine Learning (ICML), 2024 |
 On Diversified Preferences of Large Language Model AlignmentConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
 Nash Learning from Human FeedbackInternational Conference on Machine Learning (ICML), 2023 Rémi Munos Michal Valko Daniele Calandriello M. G. Azar Mark Rowland ...Nikola Momchev Olivier Bachem D. Mankowitz Doina Precup Bilal Piot |
 Adversarial Preference Optimization: Enhancing Your Alignment via RM-LLM
GameAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 |
 Controlled Decoding from Language ModelsInternational Conference on Machine Learning (ICML), 2023 |
 Chat Vector: A Simple Approach to Equip LLMs with Instruction Following
and Model Alignment in New LanguagesAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 |
 Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
 Let Me Teach You: Pedagogical Foundations of Feedback for Language
ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
