🧑‍🔬 Who cites Marc G. Bellemare

405 citations of their works from 337 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · ← Marc G. Bellemare

1. Measuring Massive Multitask Language UnderstandingarXiv:2009.03300Dan Hendrycks, Collin Burns, Steven Basart, et al.2020 · 3,620 citations
2. Continual Lifelong Learning with Neural Networks: A ReviewarXiv:1802.07569German I. Parisi, Ronald Kemker, Jose L. Part, et al.2018 · 3,224 citations
3. Large Language Models Are Human-Level Prompt EngineersarXiv:2211.01910Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.2022 · 701 citations
4. Massively Multilingual Neural Machine Translation in the Wild: Findings and ChallengesarXiv:1907.05019Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.2019 · 564 citations
5. Deep Exploration via Bootstrapped DQNarXiv:1602.04621Ian Osband, Charles Blundell, Alexander Pritzel, et al.2016 · 490 citations
6. Action-Conditional Video Prediction using Deep Networks in Atari GamesarXiv:1507.08750Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, et al.2015 · 467 citations
7. Massively Parallel Methods for Deep Reinforcement LearningarXiv:1507.04296Arun Nair, Praveen Srinivasan, Sam Blackwell, et al.2015 · 427 citations
8. Hindsight Experience ReplayarXiv:1707.01495Marcin Andrychowicz, Filip Wolski, Alex Ray, et al.2017 · 421 citations
9. 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
10. TextWorld: A Learning Environment for Text-based GamesCommunications in computer and information scienceMarc-Alexandre Cote, Akos Kadar, Xingdi Yuan, et al.2018 · 339 citations
11. Reinforcement Learning with Unsupervised Auxiliary TasksarXiv:1611.05397Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, et al.2016 · 319 citations
12. Exploration by Random Network DistillationarXiv:1810.12894Yuri Burda, Harrison Edwards, Amos Storkey, et al.2018 · 302 citations
13. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
14. 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
15. 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
16. Overview of the TREC 2019 deep learning trackarXiv:2003.07820Nick Craswell, Bhaskar Mitra, Emine Yilmaz, et al.2020 · 228 citations
17. Automatic Goal Generation for Reinforcement Learning AgentsarXiv:1705.06366Carlos Florensa, David Held, Xinyang Geng, et al.2017 · 181 citations
18. Quark: Controllable Text Generation with Reinforced UnlearningConference on Neural Information Processing Systems (NeurIPS)Ximing Lu, Sean Welleck, Jack Hessel, et al.2022 · 170 citations
19. 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
20. Efficient Methods for Natural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.2023 · 145 citations
21. Diversity is All You Need: Learning Skills without a Reward FunctionarXiv:1802.06070Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, et al.2018 · 145 citations
22. Eureka: Human-Level Reward Design via Coding Large Language ModelsarXiv:2310.12931Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.2023 · 142 citations
23. DeepMind LabarXiv:1612.03801Charles Beattie, Joel Z. Leibo, Denis Teplyashin, et al.2016 · 134 citations
24. 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
25. Reinforcement Learning on Web Interfaces Using Workflow-Guided ExplorationarXiv:1802.08802Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, et al.2018 · 119 citations
26. 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
27. Gymnasium: A Standard Interface for Reinforcement Learning EnvironmentsarXiv:2407.17032Mark Towers, Ariel Kwiatkowski, Jordan Terry, et al.2024 · 113 citations
28. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
29. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
30. 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
31. Deep Reinforcement Learning at the Edge of the Statistical PrecipicearXiv:2108.13264Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.2021 · 90 citations
32. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
33. MixEval: Deriving Wisdom of the Crowd from LLM Benchmark MixturesConference on Neural Information Processing Systems (NeurIPS)Jinjie Ni, Fuzhao Xue, Xiang Yue, et al.2024 · 47 citations
34. UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement LearningarXiv:2509.02544Haoming Wang, Haoyang Zou, Huatong Song, et al.2025 · 26 citations
35. Reinforced Efficient Reasoning via Semantically Diverse ExplorationAnnual Meeting of the Association for Computational Linguistics (ACL)Ziqi Zhao, Zhaochun Ren, Jiahong Zou, et al.2026 · 9 citations
36. From Answers to Arguments: Toward Trustworthy Clinical Diagnostic Reasoning with Toulmin-Guided Curriculum Goal-Conditioned LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Chen Zhan, Xiaoyu Tan, Gengchen Ma, et al.2026
37. Revisiting Self-Play Preference Optimization: On the Role of Prompt DifficultyFindings of the Association for Computational LinguisticsYao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.2026
38. VRPO: Rethinking Value Modeling for Robust RL under Noisy Supervision in LLM Post-TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Dingwei Zhu, Shihan Dou, Zhiheng Xi, et al.2026

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