Who cites Tom Schaul
- PyTorch: An Imperative Style, High-Performance Deep Learning LibraryarXiv:1912.01703Adam Paszke, Sam Gross, Francisco Massa, et al.2019 · 18,645 citations
- Continual Lifelong Learning with Neural Networks: A ReviewNeural NetworksGerman I. Parisi, Ronald Kemker, Jose L. Part, et al.2018 · 3,224 citations
- PathNet: Evolution Channels Gradient Descent in Super Neural NetworksarXiv:1701.08734Chrisantha Fernando, Dylan Banarse, Charles Blundell, et al.2017 · 667 citations
- AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent ConversationarXiv:2308.08155Qingyun Wu, Gagan Bansal, Jieyu Zhang, et al.2023 · 606 citations
- Semi-Supervised Sequence Modeling with Cross-View TrainingConference on Empirical Methods in Natural Language Processing (EMNLP)Kevin Clark, Minh-Thang Luong, Christopher D. Manning, et al.2018 · 494 citations
- Deep Communicating Agents for Abstractive SummarizationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, et al.2018 · 440 citations
- Hindsight Experience ReplayarXiv:1707.01495Marcin Andrychowicz, Filip Wolski, Alex Ray, et al.2017 · 421 citations
- 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
- Exploration by Random Network DistillationarXiv:1810.12894Yuri Burda, Harrison Edwards, Amos Storkey, et al.2018 · 302 citations
- xLSTM: Extended Long Short-Term MemoryConference on Neural Information Processing Systems (NeurIPS)Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.2024 · 296 citations
- 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
- Agent57: Outperforming the Atari Human BenchmarkarXiv:2003.13350Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, et al.2020 · 235 citations
- Scalable agent alignment via reward modeling: a research directionarXiv:1811.07871Jan Leike, David Krueger, Tom Everitt, et al.2018 · 227 citations
- Unsupervised Question Decomposition for Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.2020 · 222 citations
- Grounded Language Learning in a Simulated 3D WorldarXiv:1706.06551Karl Moritz Hermann, Felix Hill, Simon Green, et al.2017 · 190 citations
- Automatic Goal Generation for Reinforcement Learning AgentsarXiv:1705.06366Carlos Florensa, David Held, Xinyang Geng, et al.2017 · 181 citations
- BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex InstructionsarXiv:2406.15877Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.2024 · 176 citations
- Promptbreeder: Self-Referential Self-Improvement Via Prompt EvolutionarXiv:2309.16797Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.2023 · 174 citations
- Diversity is All You Need: Learning Skills without a Reward FunctionarXiv:1802.06070Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, et al.2018 · 145 citations
- DeepMind LabarXiv:1612.03801Charles Beattie, Joel Z. Leibo, Denis Teplyashin, et al.2016 · 134 citations
- Reinforcement Learning on Web Interfaces Using Workflow-Guided ExplorationarXiv:1802.08802Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, et al.2018 · 119 citations
- 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
- Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
- Deep Reinforcement Learning at the Edge of the Statistical PrecipicearXiv:2108.13264Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.2021 · 90 citations
- Absolute Zero: Reinforced Self-play Reasoning with Zero DataConference on Neural Information Processing Systems (NeurIPS)Andrew Zhao, Yiran Wu, Yang Yue, et al.2025 · 57 citations
- Darwin Godel Machine: Open-Ended Evolution of Self-Improving AgentsarXiv:2505.22954Jenny Zhang, Shengran Hu, Cong Lu, et al.2025 · 47 citations
- Learning Formal Mathematics From Intrinsic MotivationConference on Neural Information Processing Systems (NeurIPS)Gabriel Poesia, David Broman, Nick Haber, et al.2024 · 23 citations
- 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
- GameGPT: Multi-agent Collaborative Framework for Game DevelopmentarXiv:2310.08067Dake Chen, Haoyang Zhang, Hanbin Wang, et al.2023 · 16 citations
- Outcome-based Exploration for LLM ReasoningarXiv:2509.06941Yuda Song, Julia Kempe, Remi Munos2025 · 15 citations
- Open-Endedness is Essential for Artificial Superhuman IntelligencearXiv:2406.04268Edward Hughes, Michael Dennis, Jack Parker-Holder, et al.2024 · 14 citations
- Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive SearcharXiv:2502.02508Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.2025 · 13 citations
- CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving ChallengesFindings of the Association for Computational LinguisticsZihan Wang, Lam Nguyen, Zhengyang Zhao, et al.2026 · 6 citations
- On Safety Risks in Experience-Driven Self-Evolving AgentsFindings of the Association for Computational LinguisticsWeixiang Zhao, Yichen Zhang, Yingshuo Wang, et al.2026 · 1 citation
- PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMsFindings of the Association for Computational LinguisticsJiacheng Wang, Weiyan Zhang, Guangya Yu2026
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