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Who cites Arnaud Doucet

293 citations of their works from 292 papers of our library (of the 149,439 whose bibliographies we read) · 69 with a page here, the most cited first · ← Arnaud Doucet

  1. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  2. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paperYang Yue, Zhiqi Chen, Rui Lu, et al.2025 · 216 citations
  3. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  4. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  5. Simple and Effective Masked Diffusion Language ModelsConference on Neural Information Processing Systems (NeurIPS)Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, et al.2024 · 152 citations
  6. 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
  7. Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 142 citations
  8. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
  9. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
  10. Demystifying Long Chain-of-Thought Reasoning in LLMsarXiv:2502.03373Edward Yeo, Yuxuan Tong, Morry Niu, et al.2025 · 119 citations
  11. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 114 citations
  12. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
  13. Statistical Rejection Sampling Improves Preference OptimizationarXiv:2309.06657Tianqi Liu, Yao Zhao, Rishabh Joshi, et al.2023 · 105 citations
  14. Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-ConstraintarXiv:2312.11456Wei Xiong, Hanze Dong, Chenlu Ye, et al.2023 · 100 citations
  15. Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language ModelsarXiv:2601.18734Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.2026 · 97 citations
  16. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
  17. Dream 7B: Diffusion Large Language ModelsarXiv:2508.15487Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong2025 · 89 citations
  18. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-SolvingarXiv:2407.13690Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.2024 · 81 citations
  19. Agent Q: Advanced Reasoning and Learning for Autonomous AI AgentsarXiv:2408.07199Pranav Putta, Edmund Mills, Naman Garg, et al.2024 · 68 citations
  20. Teaching Large Language Models to Reason with Reinforcement LearningarXiv:2403.04642Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.2024 · 61 citations
  21. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  22. SALMON: Self-Alignment with Instructable Reward ModelsarXiv:2310.05910Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.2023 · 41 citations
  23. MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding MethodsarXiv:2309.10966Mara Finkelstein; Subhajit Naskar; Mehdi Mirzazadeh; Apurva Shah;, Markus Freitag2023 · 32 citations
  24. Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed InferencearXiv:2508.02193Yuxuan Song, Zheng Zhang, Cheng Luo, et al.2025 · 28 citations
  25. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 27 citations
  26. West-of-N: Synthetic Preferences for Self-Improving Reward ModelsarXiv:2401.12086Alizee Pace, Jonathan Mallinson, Eric Malmi, et al.2024 · 22 citations
  27. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language ModelsarXiv:2503.24377Rui Wang, Hongru Wang, Boyang Xue, et al.2025 · 16 citations
  28. A Survey on Latent ReasoningarXiv:2507.06203Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.2025 · 15 citations
  29. Beyond Correlation: Interpretable Evaluation of Machine Translation MetricsStefano Perrella, Lorenzo Proietti, Pere-Lluís Huguet Cabot, et al.2024 · 15 citations

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