🔗 Who cites «Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback»

43 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · ← back to «Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback»

1. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
2. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
3. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
4. Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the ArtTransactions of the Association for Computational Linguistics (TACL)Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen2025 · 90 citations
5. RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and StylearXiv:2410.16184Yantao Liu, Zijun Yao, Rui Min, et al.2024 · 53 citations
6. RM-R1: Reward Modeling as ReasoningarXiv:2505.02387Xiusi Chen, Gaotang Li, Ziqi Wang, et al.2025 · 49 citations
7. Do Large Language Models have an English Accent? Evaluating and Improving the Naturalness of Multilingual LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yanzhu Guo, Simone Conia, Zelin Zhou, et al.2025 · 25 citations
8. Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhe Yang, Yichang Zhang, Yudong Wang, et al.2025 · 11 citations
9. TESS 2: A Large-Scale Generalist Diffusion Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Jaesung Tae, Hamish Ivison, Sachin Kumar, et al.2025 · 9 citations
10. Evaluating the Effectiveness of Direct Preference Optimization for Personalizing German Automatic Text Simplifications for Persons with Intellectual DisabilitiesarXiv:2507.01479Yingqiang Gao, Kaede Johnson, David Froehlich, et al.2025 · 4 citations
11. MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Huang, Jiaheng Liu, Yancheng He, et al.2025 · 4 citations
12. Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Kailai Yang, Xiao Liu, Lei Ji, et al.2026 · 1 citation
13. Exploiting Tree Structure for Credit Assignment in Reinforcement Learning with Large Language ModelsFindings of the Association for Computational LinguisticsHieu Tran, Zonghai Yao, Hong yu2026

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

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