🔗 Who cites «Reliability and Learnability of Human Bandit Feedback for Sequence-to-Sequence Reinforcement Learning»

35 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · ← back to «Reliability and Learnability of Human Bandit Feedback for Sequence-to-Sequence Reinforcement Learning»

1. Direct Preference Optimization: Your Language Model is Secretly a Reward ModelarXiv:2305.18290Rafael Rafailov, Archit Sharma, Eric Mitchell, et al.2023 · 2,896 citations
2. Better Rewards Yield Better Summaries: Learning to Summarise Without ReferencesConference on Empirical Methods in Natural Language Processing (EMNLP)Florian Böhm, Yang Gao, Christian M. Meyer, et al.2019 · 127 citations
3. Aligning Large Language Models with Human Preferences through Representation EngineeringAnnual Meeting of the Association for Computational Linguistics (ACL)Wenhao Liu, Xiaohua Wang, Muling Wu, et al.2024 · 37 citations
4. Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical ReasoningarXiv:2407.00782Zimu Lu, Aojun Zhou, Ke Wang, et al.2024 · 23 citations
5. Suri: Multi-constraint Instruction Following in Long-form Text GenerationFindings of the Association for Computational LinguisticsChau Minh Pham, Simeng Sun, Mohit Iyyer2024 · 19 citations

30 more papers of our library cite it; they have no page here yet.

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