🔗 Who cites «Thinking Fast and Slow with Deep Learning and Tree Search»

95 papers of our library cite it (of the 149,439 whose bibliographies we read) · 27 with a page here, the most cited first · ← back to «Thinking Fast and Slow with Deep Learning and Tree Search»

1. Training language models to follow instructions with human feedbackarXiv:2203.02155Long Ouyang, Jeff Wu, Xu Jiang, et al.2022 · 10,224 citations
2. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
3. Mastering chess and shogi by self-play with a general reinforcement learning algorithm2017 · 1,186 citations
4. STaR: Bootstrapping Reasoning With ReasoningEric Zelikman, Yuhuai Wu, Jesse Mu, et al.2022 · 777 citations
5. AlpacaFarm: A Simulation Framework for Methods that Learn from Human FeedbackConference on Neural Information Processing Systems (NeurIPS)Yann Dubois, Xuechen Li, Rohan Taori, et al.2023 · 456 citations
6. Solving math word problems with process- and outcome-based feedbackarXiv:2211.14275Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.2022 · 355 citations
7. Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
8. Scalable agent alignment via reward modeling: a research directionarXiv:1811.07871Jan Leike, David Krueger, Tom Everitt, et al.2018 · 227 citations
9. Recursively Summarizing Books with Human FeedbackarXiv:2109.10862Jeff Wu, Long Ouyang, Daniel M. Ziegler, et al.2021 · 208 citations
10. Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
11. 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
12. TALM: Tool Augmented Language ModelsarXiv:2205.12255Aaron Parisi, Yao Zhao, Noah Fiedel2022 · 149 citations
13. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsarXiv:2312.06585Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023 · 147 citations
14. ReFT: Reasoning with Reinforced Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Luong Trung, Xinbo Zhang, Zhanming Jie, et al.2024 · 134 citations
15. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
16. SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive TasksConference on Neural Information Processing Systems (NeurIPS)Bill Yuchen Lin, Yicheng Fu, Karina Yang, et al.2023 · 110 citations
17. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
18. Goedel-Prover: A Frontier Model for Open-Source Automated Theorem ProvingarXiv:2502.07640Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 84 citations
19. Lean Workbook: A large-scale Lean problem set formalized from natural language math problemsConference on Neural Information Processing Systems (NeurIPS)Huaiyuan Ying, Zijian Wu, Yihan Geng, et al.2024 · 80 citations
20. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
21. Teaching Large Language Models to Reason with Reinforcement LearningarXiv:2403.04642Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.2024 · 61 citations
22. InternLM2.5-StepProver: Advancing Automated Theorem Proving via Critic-Guided SearcharXiv:2410.15700Zijian Wu, Suozhi Huang, Zhejian Zhou, et al.2024 · 59 citations
23. Parsel: Algorithmic Reasoning with Language Models by Composing DecompositionsConference on Neural Information Processing Systems (NeurIPS)Eric Zelikman, Qian Huang, Gabriel Poesia, et al.2023 · 56 citations
24. Rewarding Chatbots for Real-World Engagement with Millions of UsersarXiv:2303.06135Robert Irvine, Douglas Boubert, Vyas Raina, et al.2023 · 22 citations
25. Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference LabelsConference on Neural Information Processing Systems (NeurIPS)Jan-Philipp Franken, Eric Zelikman, Rafael Rafailov, et al.2024 · 16 citations
26. Rewarding the Unlikely: Lifting GRPO Beyond Distribution SharpeningConference on Empirical Methods in Natural Language Processing (EMNLP)Andre Wang He, Daniel Fried, Sean Welleck2025 · 15 citations
27. Language Models are Bounded Pragmatic Speakers: Understanding RLHF from a Bayesian Cognitive Modeling PerspectivearXiv:2305.17760Khanh Nguyen2023 · 1 citation

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

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