🔗 Who cites «Scalable agent alignment via reward modeling: a research direction»

109 papers of our library cite it (of the 149,439 whose bibliographies we read) · 47 with a page here, the most cited first · ← back to «Scalable agent alignment via reward modeling: a research direction»

1. Training language models to follow instructions with human feedbackarXiv:2203.02155Long Ouyang, Jeff Wu, Xu Jiang, et al.2022 · 10,224 citations
2. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
3. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
4. GPQA: A Graduate-Level Google-Proof Q&A BenchmarkarXiv:2311.12022David Rein, Betty Li Hou, Asa Cooper Stickland, et al.2023 · 1,018 citations
5. Universal and Transferable Adversarial Attacks on Aligned Language ModelsarXiv:2307.15043Andy Zou, Zifan Wang, Nicholas Carlini, et al.2023 · 1,005 citations
6. WebGPT: Browser-assisted question-answering with human feedbackarXiv:2112.09332Reiichiro Nakano, Jacob Hilton, Suchir Balaji, et al.2021 · 721 citations
7. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
8. Towards Understanding Sycophancy in Language ModelsarXiv:2310.13548Mrinank Sharma, Meg Tong, Tomasz Korbak, et al.2023 · 384 citations
9. Improving alignment of dialogue agents via targeted human judgementsarXiv:2209.14375Amelia Glaese, Nat McAleese, Maja Trębacz, et al.2022 · 362 citations
10. Scaling Laws for Reward Model OveroptimizationarXiv:2210.10760Leo Gao, John Schulman, Jacob Hilton2022 · 323 citations
11. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 252 citations
12. Teaching language models to support answers with verified quotesarXiv:2203.11147Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.2022 · 218 citations
13. RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human FeedbackIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianyu Yu, Yuan Yao, Haoye Zhang, et al.2023 · 217 citations
14. Recursively Summarizing Books with Human FeedbackarXiv:2109.10862Jeff Wu, Long Ouyang, Daniel M. Ziegler, et al.2021 · 208 citations
15. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
16. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
17. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
18. Unsolved Problems in ML SafetyarXiv:2109.13916Dan Hendrycks, Nicholas Carlini, John Schulman, et al.2021 · 151 citations
19. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
20. Humans or LLMs as the Judge? A Study on Judgement BiasConference on Empirical Methods in Natural Language Processing (EMNLP)Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.2024 · 133 citations
21. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
22. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
23. Measuring Progress on Scalable Oversight for Large Language ModelsarXiv:2211.03540Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, et al.2022 · 117 citations
24. Safety Alignment Should Be Made More Than Just a Few Tokens DeeparXiv:2406.05946Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.2024 · 97 citations
25. Training Socially Aligned Language Models on Simulated Social InteractionsarXiv:2305.16960Ruibo Liu, Ruixin Yang, Chenyan Jia, et al.2023 · 94 citations
26. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
27. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
28. Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationTransactions of the Association for Computational Linguistics (TACL)Patrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 citations
29. Humans or LLMs as the Judge? A Study on Judgement BiasesarXiv:2402.10669Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.2024 · 78 citations
30. Secrets of RLHF in Large Language Models Part II: Reward ModelingarXiv:2401.06080Binghai Wang, Rui Zheng, Lu Chen, et al.2024 · 72 citations
31. Modular Pluralism: Pluralistic Alignment via Multi-LLM CollaborationConference on Empirical Methods in Natural Language Processing (EMNLP)Shangbin Feng, Taylor Sorensen, Yuhan Liu, et al.2024 · 68 citations
32. MLLM-Protector: Ensuring MLLM's Safety without Hurting PerformanceConference on Empirical Methods in Natural Language Processing (EMNLP)Renjie Pi, Tianyang Han, Jianshu Zhang, et al.2024 · 58 citations
33. Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackarXiv:2303.05453Hannah Rose Kirk, Bertie Vidgen, Paul Rottger, et al.2023 · 57 citations
34. The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce HarmConference on Empirical Methods in Natural Language Processing (EMNLP)Aakanksha, Arash Ahmadian, Beyza Ermis, et al.2024 · 49 citations
35. HyperCLOVA X Technical ReportarXiv:2404.01954Kang Min Yoo, Jaegeun Han, Sookyo In, et al.2024 · 44 citations
36. When does In-context Learning Fall Short and Why? A Study on Specification-Heavy TasksarXiv:2311.08993Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.2023 · 42 citations
37. SALMON: Self-Alignment with Instructable Reward ModelsarXiv:2310.05910Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.2023 · 41 citations
38. Aligning LLMs with Individual Preferences via InteractionInternational Conference on Computational Linguistics (COLING)Shujin Wu, Yi R. Fung, Cheng Qian, et al.2025 · 24 citations
39. Rewarding Chatbots for Real-World Engagement with Millions of UsersarXiv:2303.06135Robert Irvine, Douglas Boubert, Vyas Raina, et al.2023 · 22 citations
40. CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and AugmentationTransactions of the Association for Computational Linguistics (TACL)Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.2025 · 20 citations
41. The Dark Side of Function Calling: Pathways to Jailbreaking Large Language ModelsInternational Conference on Computational Linguistics (COLING)Zihui Wu, Haichang Gao, Jianping He, et al.2025 · 8 citations
42. CoAct: Co-Active LLM Preference Learning with Human-AI SynergyAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.2026 · 1 citation
43. Incentivizing Strong Reasoning from Weak SupervisionConference of the European Chapter of the Association for Computational Linguistics (EACL)Yige Yuan, Teng Xiao, Shuchang Tao, et al.2026 · 1 citation
44. When Do Large Language Models Exhibit Unsolicited Deception?Transactions of the Association for Computational Linguistics (TACL)Samuel M. Taylor, Benjamin K. Bergen2026 · 1 citation
45. Entity-Level Sentiment Analysis with Sentence Relevance DetectionLanguage Resources and Evaluation Conference (LREC)Egil Rønningstad, Roman Klinger, Lilja Øvrelid, et al.2026
46. PubMed Reasoner: Dynamic Reasoning-based Retrieval for Evidence-Grounded Biomedical Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Yiqing Zhang, Xiaozhong Liu, Fabricio Murai2026
47. Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social SimulationConference of the European Chapter of the Association for Computational Linguistics (EACL)Bolei Ma, Yong Cao, Indira Sen, et al.2026

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