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Who cites David Silver

4,581 citations of their works from 4,140 papers of our library (of the 149,439 whose bibliographies we read) · 895 with a page here, the most cited first · page 1 of 9 · 1–100 · ← David Silver

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  1. PyTorch: An Imperative Style, High-Performance Deep Learning LibraryarXiv:1912.01703Adam Paszke, Sam Gross, Francisco Massa, et al.2019 · 18,645 citations
  2. TensorFlow: A system for large-scale machine learningarXiv:1605.08695Martin Abadi, Paul Barham, Jianmin Chen, et al.2016 · 12,711 citations
  3. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed SystemsarXiv:1603.04467Martín Abadi, Ashish Agarwal, Paul Barham, et al.2016 · 9,512 citations
  4. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  5. Representation Learning with Contrastive Predictive CodingarXiv:1807.03748Aaron van den Oord, Yazhe Li, Oriol Vinyals2018 · 7,022 citations
  6. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
  7. Towards A Rigorous Science of Interpretable Machine LearningarXiv:1702.08608Finale Doshi-Velez, Been Kim2017 · 3,226 citations
  8. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  9. Language Models as Knowledge Bases?Conference on Empirical Methods in Natural Language Processing (EMNLP)Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, et al.2019 · 3,028 citations
  10. Relational inductive biases, deep learning, and graph networksarXiv:1806.01261Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.2018 · 2,335 citations
  11. Semantic Parsing on Freebase from Question-Answer PairsConference on Empirical Methods in Natural Language Processing (EMNLP)Jonathan Berant, Andrew Chou, Roy Frostig, et al.2013 · 2,331 citations
  12. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
  13. DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsarXiv:2402.03300Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.2024 · 2,115 citations
  14. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
  15. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextarXiv:2403.05530Gemini Team, Petko Georgiev, Ving Ian Lei, et al.2024 · 1,589 citations
  16. Deep Reinforcement Learning for Dialogue GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Jiwei Li, Will Monroe, Alan Ritter, et al.2016 · 1,502 citations
  17. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  18. 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
  19. Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhonearXiv:2404.14219Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.2024 · 1,134 citations
  20. Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 1,031 citations
  21. BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply ChainarXiv:1708.06733Tianyu Gu, Brendan Dolan-Gavitt, Siddharth Garg2017 · 1,024 citations
  22. MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIIEEE Computer Society Conference on Computer Vision and Pattern RecognitionXiang Yue, Yuansheng Ni, Kai Zhang, et al.2023 · 1,005 citations
  23. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic CapabilitiesarXiv:2507.06261Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.2025 · 974 citations
  24. Interpretable Machine Learning: Fundamental Principles and 10 Grand ChallengesarXiv:2103.11251 · Statistics Surveys, 2021Cynthia Rudin; Chaofan Chen; Zhi Chen; Haiyang Huang; Lesia Semenova;, Chudi Zhong2021 · 974 citations
  25. MMBench: Is Your Multi-modal Model an All-around Player?Lecture notes in computer scienceYuan Liu, Haodong Duan, Yuanhan Zhang, et al.2023 · 942 citations
  26. Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any ResolutionarXiv:2409.12191Peng Wang, Shuai Bai, Sinan Tan, et al.2024 · 860 citations
  27. Fast Abstractive Summarization with Reinforce-Selected Sentence RewritingAnnual Meeting of the Association for Computational Linguistics (ACL)Yen-Chun Chen, Mohit Bansal2018 · 826 citations
  28. MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding BenchmarkConference on Neural Information Processing Systems (NeurIPS)Yubo Wang, Xueguang Ma, Ge Zhang, et al.2024 · 761 citations
  29. SGLang: Efficient Execution of Structured Language Model ProgramsConference on Neural Information Processing Systems (NeurIPS)Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.2023 · 729 citations
  30. Red Teaming Language Models with Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Saffron Huang, Francis Song, et al.2022 · 700 citations
  31. ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All ToolsarXiv:2406.12793Team GLM, Aohan Zeng, Bin Xu, et al.2024 · 691 citations
  32. PathNet: Evolution Channels Gradient Descent in Super Neural NetworksarXiv:1701.08734Chrisantha Fernando, Dylan Banarse, Charles Blundell, et al.2017 · 667 citations
  33. AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent ConversationarXiv:2308.08155Qingyun Wu, Gagan Bansal, Jieyu Zhang, et al.2023 · 606 citations
  34. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
  35. Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model ParametersarXiv:2408.03314Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.2024 · 567 citations
  36. Jailbreaking Black Box Large Language Models in Twenty QueriesarXiv:2310.08419Patrick Chao, Alexander Robey, Edgar Dobriban, et al.2023 · 553 citations
  37. Chatbot Arena: An Open Platform for Evaluating LLMs by Human PreferencearXiv:2403.04132Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.2024 · 546 citations
  38. How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source SuitesScience China Information SciencesZhe Chen, Weiyun Wang, Hao Tian, et al.2024 · 541 citations
  39. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
  40. Regularizing Neural Networks by Penalizing Confident Output DistributionsarXiv:1701.06548Gabriel Pereyra, George Tucker, Jan Chorowski, et al.2017 · 496 citations
  41. 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
  42. Deep Exploration via Bootstrapped DQNarXiv:1602.04621Ian Osband, Charles Blundell, Alexander Pritzel, et al.2016 · 490 citations
  43. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
  44. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 468 citations
  45. Action-Conditional Video Prediction using Deep Networks in Atari GamesarXiv:1507.08750Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, et al.2015 · 467 citations
  46. OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific ProblemsAnnual Meeting of the Association for Computational Linguistics (ACL)Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.2024 · 456 citations
  47. FinGPT: Open-Source Financial Large Language ModelsarXiv:2306.06031Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang2023 · 445 citations
  48. 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
  49. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  50. Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video AnalysisIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChaoyou Fu, Yuhan Dai, Yongdong Luo, et al.2024 · 427 citations
  51. Massively Parallel Methods for Deep Reinforcement LearningarXiv:1507.04296Arun Nair, Praveen Srinivasan, Sam Blackwell, et al.2015 · 427 citations
  52. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  53. Hindsight Experience ReplayarXiv:1707.01495Marcin Andrychowicz, Filip Wolski, Alex Ray, et al.2017 · 421 citations
  54. WebShop: Towards Scalable Real-World Web Interaction with Grounded Language AgentsConference on Neural Information Processing Systems (NeurIPS)Shunyu Yao, Howard Chen, John Yang, et al.2022 · 420 citations
  55. BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical DomainsFindings of the Association for Computational LinguisticsYanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.2024 · 409 citations
  56. Yi: Open Foundation Models by 01.AIarXiv:2403.04652Alex Young, Bei Chen, Chao Li, et al.2024 · 408 citations
  57. RULER: What's the Real Context Size of Your Long-Context Language Models?arXiv:2404.06654Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.2024 · 400 citations
  58. Learning Latent Dynamics for Planning from PixelsarXiv:1811.04551Danijar Hafner, Timothy Lillicrap, Ian Fischer, et al.2018 · 394 citations
  59. 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
  60. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  61. VILA: On Pre-training for Visual Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJi Lin, Hongxu Yin, Wei Ping, et al.2023 · 381 citations
  62. Language Understanding for Text-based Games Using Deep Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Karthik Narasimhan, Tejas Kulkarni, Regina Barzilay2015 · 380 citations
  63. The AI Scientist: Towards Fully Automated Open-Ended Scientific DiscoveryarXiv:2408.06292Chris Lu, Cong Lu, Robert Tjarko Lange, et al.2024 · 372 citations
  64. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
  65. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  66. Learning to Navigate Unseen Environments: Back Translation with Environmental DropoutConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hao Tan, Licheng Yu, Mohit Bansal2019 · 358 citations
  67. SnapKV: LLM Knows What You are Looking for Before GenerationConference on Neural Information Processing Systems (NeurIPS)Yuhong Li, Yingbing Huang, Bowen Yang, et al.2024 · 355 citations
  68. Progress & Compress: A scalable framework for continual learningarXiv:1805.06370Jonathan Schwarz, Jelena Luketina, Wojciech M. Czarnecki, et al.2018 · 338 citations
  69. HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianrui Guan, Fuxiao Liu, Xiyang Wu, et al.2023 · 335 citations
  70. The Next Decade in AI: Four Steps Towards Robust Artificial IntelligencearXiv:2002.06177Gary Marcus2020 · 332 citations
  71. HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust RefusalarXiv:2402.04249Mantas Mazeika, Long Phan, Xuwang Yin, et al.2024 · 330 citations
  72. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 322 citations
  73. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
  74. Reinforcement Learning with Unsupervised Auxiliary TasksarXiv:1611.05397Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, et al.2016 · 319 citations
  75. Multimodal Chain-of-Thought Reasoning in Language ModelsarXiv:2302.00923Zhuosheng Zhang, Aston Zhang, Mu Li, et al.2023 · 308 citations
  76. OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsScience China Information SciencesYuliang Liu, Zhang Li, Mingxin Huang, et al.2023 · 306 citations
  77. Exploration by Random Network DistillationarXiv:1810.12894Yuri Burda, Harrison Edwards, Amos Storkey, et al.2018 · 302 citations
  78. Robust Distant Supervision Relation Extraction via Deep Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Pengda Qin, Weiran Xu, William Yang Wang2018 · 298 citations
  79. xLSTM: Extended Long Short-Term MemoryConference on Neural Information Processing Systems (NeurIPS)Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.2024 · 296 citations
  80. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
  81. An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language ModelsLecture notes in computer scienceLiang Chen, Haozhe Zhao, Tianyu Liu, et al.2024 · 279 citations
  82. Are We on the Right Way for Evaluating Large Vision-Language Models?Conference on Neural Information Processing Systems (NeurIPS)Lin Chen, Jinsong Li, Xiaoyi Dong, et al.2024 · 277 citations
  83. Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency AnalysisACM Computing Surveys 2019Tal Ben-Nun, Torsten Hoefler2018 · 275 citations
  84. GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language ModelsarXiv:2410.05229Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.2024 · 273 citations
  85. MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 269 citations
  86. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
  87. HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.2024 · 268 citations
  88. OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer EnvironmentsConference on Neural Information Processing Systems (NeurIPS)Tianbao Xie, Danyang Zhang, Jixuan Chen, et al.2024 · 264 citations
  89. The Effect of Sampling Temperature on Problem Solving in Large Language ModelsFindings of the Association for Computational LinguisticsMatthew Renze2024 · 263 citations
  90. Large Language Models for Data Annotation and Synthesis: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Tan, Dawei Li, Song Wang, et al.2024 · 262 citations
  91. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  92. Mapping Instructions and Visual Observations to Actions with Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Dipendra Misra, John Langford, Yoav Artzi2017 · 255 citations
  93. InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingLecture notes in computer scienceYi Wang, Kunchang Li, Xinhao Li, et al.2024 · 253 citations
  94. KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV CachearXiv:2402.02750Zirui Liu, Jiayi Yuan, Hongye Jin, et al.2024 · 244 citations
  95. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
  96. Qwen2-Audio Technical ReportarXiv:2407.10759Yunfei Chu, Jin Xu, Qian Yang, et al.2024 · 238 citations
  97. A Study of Reinforcement Learning for Neural Machine TranslationConference on Empirical Methods in Natural Language Processing (EMNLP)Lijun Wu, Fei Tian, Tao Qin, et al.2018 · 234 citations
  98. MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?Lecture notes in computer scienceRenrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.2024 · 232 citations
  99. A Survey of Reinforcement Learning Informed by Natural LanguageInternational Joint Conference on Artificial IntelligenceJelena Luketina, Nantas Nardelli, Gregory Farquhar, et al.2019 · 231 citations
  100. Qwen2.5-Omni Technical ReportarXiv:2503.20215Jin Xu, Zhifang Guo, Jinzheng He, et al.2025 · 227 citations

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