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Who cites Rémi Munos

990 citations of their works from 898 papers of our library (of the 149,439 whose bibliographies we read) · 138 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Rémi Munos

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  1. Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020Alec Radford, Jong Wook Kim, Chris Hallacy, et al.2021 · 8,767 citations
  2. Representation Learning with Contrastive Predictive CodingarXiv:1807.03748Aaron van den Oord, Yazhe Li, Oriol Vinyals2018 · 7,022 citations
  3. Emerging Properties in Self-Supervised Vision TransformersIEEE/CVF International Conference on Computer Vision (ICCV)Mathilde Caron, Hugo Touvron, Ishan Misra, et al.2021 · 6,046 citations
  4. HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden UnitsIEEE/ACM Transactions on Audio Speech and Language ProcessingWei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, et al.2021 · 3,458 citations
  5. Continual Lifelong Learning with Neural Networks: A ReviewNeural NetworksGerman I. Parisi, Ronald Kemker, Jose L. Part, et al.2018 · 3,224 citations
  6. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  7. Relational inductive biases, deep learning, and graph networksarXiv:1806.01261Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.2018 · 2,335 citations
  8. Scaling Up Visual and Vision-Language Representation Learning With Noisy Text SupervisionInternational Conference on Machine Learning (ICML)Chao Jia, Yinfei Yang, Ye Xia, et al.2021 · 1,615 citations
  9. DINOv2: Learning Robust Visual Features without SupervisionarXiv:2304.07193Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.2023 · 1,513 citations
  10. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  11. Generating Long Sequences with Sparse TransformersarXiv:1904.10509Rewon Child, Scott Gray, Alec Radford, et al.2019 · 967 citations
  12. Masked Autoencoders Are Scalable Vision LearnersarXiv:2111.06377Kaiming He, Xinlei Chen, Saining Xie, et al.2021 · 596 citations
  13. Massively Multilingual Neural Machine Translation in the Wild: Findings and ChallengesarXiv:1907.05019Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.2019 · 564 citations
  14. CogView: Mastering Text-to-Image Generation via TransformersarXiv:2105.13290Ming Ding, Zhuoyi Yang, Wenyi Hong, et al.2021 · 469 citations
  15. OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning FrameworkarXiv:2202.03052Peng Wang, An Yang, Rui Men, et al.2022 · 467 citations
  16. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  17. Hindsight Experience ReplayarXiv:1707.01495Marcin Andrychowicz, Filip Wolski, Alex Ray, et al.2017 · 421 citations
  18. Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General AgentsJournal of Artificial Intelligence ResearchMarlos C. Machado, Marc G. Bellemare, Erik Talvitie, et al.2017 · 393 citations
  19. Compressive Transformers for Long-Range Sequence ModellingarXiv:1911.05507Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.2019 · 340 citations
  20. Scaling Laws for Reward Model OveroptimizationarXiv:2210.10760Leo Gao, John Schulman, Jacob Hilton2022 · 323 citations
  21. Exploration by Random Network DistillationarXiv:1810.12894Yuri Burda, Harrison Edwards, Amos Storkey, et al.2018 · 302 citations
  22. Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency AnalysisACM Computing Surveys 2019Tal Ben-Nun, Torsten Hoefler2018 · 275 citations
  23. DiffCSE: Difference-based Contrastive Learning for Sentence EmbeddingsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, et al.2022 · 269 citations
  24. Curriculum Learning for Natural Language UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Benfeng Xu, Licheng Zhang, Zhendong Mao, et al.2020 · 240 citations
  25. From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal LikelihoodAnnual Meeting of the Association for Computational Linguistics (ACL)Kelvin Guu, Panupong Pasupat, Evan Liu, et al.2017 · 236 citations
  26. Agent57: Outperforming the Atari Human BenchmarkarXiv:2003.13350Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, et al.2020 · 235 citations
  27. Gradient Surgery for Multi-Task LearningarXiv:2001.06782Tianhe Yu, Saurabh Kumar, Abhishek Gupta, et al.2020 · 233 citations
  28. Scalable agent alignment via reward modeling: a research directionarXiv:1811.07871Jan Leike, David Krueger, Tom Everitt, et al.2018 · 227 citations
  29. Reinforced Self-Training (ReST) for Language ModelingarXiv:2308.08998Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.2023 · 224 citations
  30. Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement LearningarXiv:1910.00177Xue Bin Peng, Aviral Kumar, Grace Zhang, et al.2019 · 223 citations
  31. Automatic Goal Generation for Reinforcement Learning AgentsarXiv:1705.06366Carlos Florensa, David Held, Xinyang Geng, et al.2017 · 181 citations
  32. Curriculum Learning for Domain Adaptation in Neural Machine TranslationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xuan Zhang, Pamela Shapiro, Gaurav Kumar, et al.2019 · 169 citations
  33. Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their SolutionsarXiv:1901.01753Rui Wang, Joel Lehman, Jeff Clune, et al.2019 · 154 citations
  34. Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-ExpertsFindings of the Association for Computational LinguisticsHaoxiang Wang, Wei Xiong, Tengyang Xie, et al.2024 · 153 citations
  35. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  36. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  37. Diversity is All You Need: Learning Skills without a Reward FunctionarXiv:1802.06070Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, et al.2018 · 145 citations
  38. InternVideo: General Video Foundation Models via Generative and Discriminative LearningarXiv:2212.03191Yi Wang, Kunchang Li, Yizhuo Li, et al.2022 · 144 citations
  39. 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
  40. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  41. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
  42. BabyAI: A Platform to Study the Sample Efficiency of Grounded Language LearningarXiv:1810.08272Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, et al.2018 · 123 citations
  43. SaulLM-7B: A pioneering Large Language Model for LawarXiv:2403.03883Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.2024 · 119 citations
  44. DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree SearcharXiv:2408.08152Huajian Xin, Z. Z. Ren, Junxiao Song, et al.2024 · 116 citations
  45. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
  46. Orca-Math: Unlocking the potential of SLMs in Grade School MatharXiv:2402.14830Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.2024 · 111 citations
  47. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
  48. Nemotron-4 340B Technical ReportarXiv:2406.11704Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.2024 · 107 citations
  49. AnglE-optimized Text EmbeddingsarXiv:2309.12871Xianming Li, Jing Li2023 · 103 citations
  50. 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
  51. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  52. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
  53. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
  54. Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewardsConference on Neural Information Processing Systems (NeurIPS)Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.2023 · 90 citations
  55. Deep Reinforcement Learning at the Edge of the Statistical PrecipicearXiv:2108.13264Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.2021 · 90 citations
  56. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 83 citations
  57. Smaug: Fixing Failure Modes of Preference Optimisation with DPO-PositivearXiv:2402.13228Arka Pal, Deep Karkhanis, Samuel Dooley, et al.2024 · 82 citations
  58. AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language ReasoningConference on Neural Information Processing Systems (NeurIPS)Wei Fu, Jiaxuan Gao, Xujie Shen, et al.2025 · 80 citations
  59. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
  60. From r to Q*: Your Language Model is Secretly a Q-FunctionarXiv:2404.12358Rafael Rafailov, Joey Hejna, Ryan Park, et al.2024 · 72 citations
  61. Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Wang, Yong Lin, Wei Xiong, et al.2024 · 68 citations
  62. Towards Understanding Grokking: An Effective Theory of Representation LearningConference on Neural Information Processing Systems (NeurIPS)Ziming Liu, Ouail Kitouni, Niklas Nolte, et al.2022 · 65 citations
  63. The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-DeterminismConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yifan Song, Guoyin Wang, Sujian Li, et al.2025 · 64 citations
  64. Reasoning with Exploration: An Entropy PerspectivearXiv:2506.14758Daixuan Cheng, Shaohan Huang, Xuekai Zhu, et al.2025 · 63 citations
  65. Free Process Rewards without Process LabelsarXiv:2412.01981Lifan Yuan, Wendi Li, Huayu Chen, et al.2024 · 58 citations
  66. Generative Reward ModelsarXiv:2410.12832Dakota Mahan, Duy Van Phung, Rafael Rafailov, et al.2024 · 58 citations
  67. RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-FoldConference on Neural Information Processing Systems (NeurIPS)Amrith Setlur, Saurabh Garg, Xinyang Geng, et al.2024 · 56 citations
  68. Pedagogical Alignment of Large Language ModelsFindings of the Association for Computational Linguistics: EMNLP 2024Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, et al.2024 · 54 citations
  69. Critique-out-Loud Reward ModelsarXiv:2408.11791Zachary Ankner, Mansheej Paul, Brandon Cui, et al.2024 · 52 citations
  70. Easy-to-Hard Generalization: Scalable Alignment Beyond Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Longhui Yu, Yikang Shen, et al.2024 · 51 citations
  71. mDPO: Conditional Preference Optimization for Multimodal Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Fei Wang, Wenxuan Zhou, James Y. Huang, et al.2024 · 50 citations
  72. Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference FeedbackConference on Neural Information Processing Systems (NeurIPS)Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.2024 · 50 citations
  73. Direct Nash Optimization: Teaching Language Models to Self-Improve with General PreferencesarXiv:2404.03715Corby Rosset, Ching-An Cheng, Arindam Mitra, et al.2024 · 44 citations
  74. Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference OptimizationarXiv:2411.10442Weiyun Wang, Zhe Chen, Wenhai Wang, et al.2024 · 44 citations
  75. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
  76. ODIN: Disentangled Reward Mitigates Hacking in RLHFarXiv:2402.07319Lichang Chen, Chen Zhu, Davit Soselia, et al.2024 · 38 citations
  77. Data Distillation: A SurveyarXiv:2301.04272Noveen Sachdeva, Julian McAuley2023 · 37 citations
  78. Collaborating with language models for embodied reasoningarXiv:2302.00763Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino, et al.2023 · 36 citations
  79. Self-Refine Instruction-Tuning for Aligning Reasoning in Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Leonardo Ranaldi, Andre Freitas2024 · 35 citations
  80. Nash Learning from Human FeedbackarXiv:2312.00886Remi Munos, Michal Valko, Daniele Calandriello, et al.2023 · 32 citations
  81. LiPO: Listwise Preference Optimization through Learning-to-RankConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Tianqi Liu, Zhen Qin, Junru Wu, et al.2025 · 31 citations
  82. Learning Planning-based Reasoning by Trajectories Collection and Process Reward SynthesizingConference on Empirical Methods in Natural Language Processing (EMNLP)Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.2024 · 31 citations
  83. LLM-as-a-Judge & Reward Model: What They Can and Cannot DoarXiv:2409.11239Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.2024 · 27 citations
  84. Binary Classifier Optimization for Large Language Model AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Seungjae Jung, Gunsoo Han, Daniel Wontae Nam, et al.2025 · 26 citations
  85. Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM ReasoningarXiv:2506.06632Shubham Parashar, Shurui Gui, Xiner Li, et al.2025 · 23 citations
  86. BOND: Aligning LLMs with Best-of-N DistillationarXiv:2407.14622Pier Giuseppe Sessa, Robert Dadashi, Leonard Hussenot, et al.2024 · 23 citations
  87. Learning Formal Mathematics From Intrinsic MotivationConference on Neural Information Processing Systems (NeurIPS)Gabriel Poesia, David Broman, Nick Haber, et al.2024 · 23 citations
  88. Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical ReasoningarXiv:2407.00782Zimu Lu, Aojun Zhou, Ke Wang, et al.2024 · 23 citations
  89. Rethinking Entropy Interventions in RLVR: An Entropy Change PerspectiveAnnual Meeting of the Association for Computational Linguistics (ACL)Zhezheng Hao, Hong Wang, Haoyang Liu, et al.2026 · 22 citations
  90. Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-GenerationarXiv:2410.02725Rohin Manvi, Anikait Singh, Stefano Ermon2024 · 22 citations
  91. Personality Alignment of Large Language ModelsarXiv:2408.11779Minjun Zhu, Yixuan Weng, Linyi Yang, et al.2024 · 21 citations
  92. Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in AlignmentTransactions of the Association for Computational Linguistics (TACL)Karel D'Oosterlinck, Winnie Xu, Chris Develder, et al.2025 · 20 citations
  93. Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language ModelsarXiv:2412.02980Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.2024 · 17 citations
  94. Weak-to-Strong Search: Align Large Language Models via Searching over Small Language ModelsConference on Neural Information Processing Systems (NeurIPS)Zhanhui Zhou, Zhixuan Liu, Jie Liu, et al.2024 · 17 citations
  95. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
  96. 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
  97. Outcome-based Exploration for LLM ReasoningarXiv:2509.06941Yuda Song, Julia Kempe, Remi Munos2025 · 15 citations
  98. MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teamingAnnual Meeting of the Association for Computational Linguistics (ACL)Weiyang Guo, Jing Li, Wenya Wang, et al.2025 · 14 citations
  99. Discovering Preference Optimization Algorithms with and for Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Chris Lu, Samuel Holt, Claudio Fanconi, et al.2024 · 14 citations
  100. Open-Endedness is Essential for Artificial Superhuman IntelligencearXiv:2406.04268Edward Hughes, Michael Dennis, Jack Parker-Holder, et al.2024 · 14 citations

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