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Who cites Yuri Burda

2,946 citations of their works from 2,916 papers of our library (of the 149,439 whose bibliographies we read) · 794 with a page here, the most cited first · page 2 of 8 · 101–200 · ← Yuri Burda

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  1. The AI Scientist: Towards Fully Automated Open-Ended Scientific DiscoveryarXiv:2408.06292Chris Lu, Cong Lu, Robert Tjarko Lange, et al.2024 · 372 citations
  2. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
  3. Augmented Language Models: a SurveyarXiv:2302.07842Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.2023 · 369 citations
  4. Orca: Progressive Learning from Complex Explanation Traces of GPT-4arXiv:2306.02707Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al.2023 · 369 citations
  5. 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
  6. Solving math word problems with process- and outcome-based feedbackarXiv:2211.14275Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.2022 · 355 citations
  7. Faithful Chain-of-Thought ReasoningInternational Joint Conference on Natural Language Processing (IJCNLP)Qing Lyu, Shreya Havaldar, Adam Stein, et al.2023 · 353 citations
  8. Kimi K2: Open Agentic IntelligencearXiv:2507.20534Kimi Team, Yifan Bai, Yiping Bao, et al.2025 · 347 citations
  9. Complexity-Based Prompting for Multi-Step ReasoningarXiv:2210.00720Yao Fu, Hao Peng, Ashish Sabharwal, et al.2022 · 345 citations
  10. Textbooks Are All You Need II: phi-1.5 technical reportarXiv:2309.05463Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, et al.2023 · 336 citations
  11. HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust RefusalarXiv:2402.04249Mantas Mazeika, Long Phan, Xuwang Yin, et al.2024 · 330 citations
  12. Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 328 citations
  13. Chameleon: Plug-and-Play Compositional Reasoning with Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Pan Lu, Baolin Peng, Hao Cheng, et al.2023 · 327 citations
  14. Faith and Fate: Limits of Transformers on CompositionalityConference on Neural Information Processing Systems (NeurIPS)Nouha Dziri, Ximing Lu, Melanie Sclar, et al.2023 · 327 citations
  15. CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingarXiv:2305.11738Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 326 citations
  16. Text and Code Embeddings by Contrastive Pre-TrainingarXiv:2201.10005Arvind Neelakantan, Tao Xu, Raul Puri, et al.2022 · 323 citations
  17. Self-collaboration Code Generation via ChatGPTACM Transactions on Software Engineering and MethodologyYihong Dong; Xue Jiang; Zhi Jin;, Ge Li2023 · 319 citations
  18. How Far Can Camels Go? Exploring the State of Instruction Tuning on Open ResourcesConference on Neural Information Processing Systems (NeurIPS)Yizhong Wang, Hamish Ivison, Pradeep Dasigi, et al.2023 · 317 citations
  19. MEDITRON-70B: Scaling Medical Pretraining for Large Language ModelsarXiv:2311.16079Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.2023 · 315 citations
  20. From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Shangbin Feng, Chan Young Park, Yuhan Liu, et al.2023 · 311 citations
  21. Large Language Models are Better Reasoners with Self-VerificationFindings of the Association for Computational LinguisticsYixuan Weng, Minjun Zhu, Fei Xia, et al.2023 · 304 citations
  22. Multi-step Jailbreaking Privacy Attacks on ChatGPTFindings of the Association for Computational LinguisticsHaoran Li, Dadi Guo, Wei Fan, et al.2023 · 304 citations
  23. Socratic Models: Composing Zero-Shot Multimodal Reasoning with LanguagearXiv:2204.00598Andy Zeng, Maria Attarian, Brian Ichter, et al.2022 · 302 citations
  24. Exploration by Random Network DistillationarXiv:1810.12894Yuri Burda, Harrison Edwards, Amos Storkey, et al.2018 · 302 citations
  25. InternLM2 Technical ReportarXiv:2403.17297Zheng Cai, Maosong Cao, Haojiong Chen, et al.2024 · 301 citations
  26. Retrieval-Augmented Generation for AI-Generated Content: A SurveyarXiv:2402.19473Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.2024 · 301 citations
  27. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  28. Document-Level Machine Translation with Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.2023 · 297 citations
  29. CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.2022 · 297 citations
  30. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 295 citations
  31. A Review of Large Language Models and Autonomous Agents in ChemistryarXiv:2407.01603Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White2024 · 288 citations
  32. 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
  33. API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Minghao Li, Yingxiu Zhao, Bowen Yu, et al.2023 · 286 citations
  34. An Explanation of In-context Learning as Implicit Bayesian InferencearXiv:2111.02080Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.2021 · 286 citations
  35. Larger language models do in-context learning differentlyarXiv:2303.03846Jerry Wei, Jason Wei, Yi Tay, et al.2023 · 285 citations
  36. A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series ModelsarXiv:2303.10420Junjie Ye, Xuanting Chen, Nuo Xu, et al.2023 · 283 citations
  37. Large Language Models for Mathematical Reasoning: Progresses and ChallengesConference of the European Chapter of the Association for Computational Linguistics (EACL)Janice Ahn, Rishu Verma, Renze Lou, et al.2024 · 280 citations
  38. Large Language Monkeys: Scaling Inference Compute with Repeated SamplingarXiv:2407.21787Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.2024 · 270 citations
  39. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
  40. Predictability and Surprise in Large Generative ModelsACM Conference on Fairness, Accountability, and Transparency (FAccT)Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.2022 · 268 citations
  41. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  42. LeanDojo: Theorem Proving with Retrieval-Augmented Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.2023 · 253 citations
  43. Personality Traits in Large Language ModelsarXiv:2307.00184Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.2023 · 252 citations
  44. NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each BenchmarkFindings of the Association for Computational LinguisticsOscar Sainz, Jon Campos, Iker García-Ferrero, et al.2023 · 250 citations
  45. Transformers learn in-context by gradient descentarXiv:2212.07677Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.2022 · 247 citations
  46. LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation DatasetarXiv:2309.11998Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 242 citations
  47. Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical StudyACM International Conference on Web Search and Data Mining (WSDM)Yuan Sui, Mengyu Zhou, Mingjie Zhou, et al.2023 · 235 citations
  48. Progress measures for grokking via mechanistic interpretabilityarXiv:2301.05217Neel Nanda, Lawrence Chan, Tom Lieberum, et al.2023 · 228 citations
  49. Qwen2.5-Omni Technical ReportarXiv:2503.20215Jin Xu, Zhifang Guo, Jinzheng He, et al.2025 · 227 citations
  50. Specializing Smaller Language Models towards Multi-Step ReasoningarXiv:2301.12726Yao Fu, Hao Peng, Litu Ou, et al.2023 · 224 citations
  51. GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical InformationBioinformaticsQiao Jin, Yifan Yang, Qingyu Chen, et al.2023 · 223 citations
  52. Self-planning Code Generation with Large Language ModelsACM Transactions on Software Engineering and MethodologyXue Jiang, Yihong Dong, Lecheng Wang, et al.2023 · 223 citations
  53. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
  54. OpenHands: An Open Platform for AI Software Developers as Generalist AgentsarXiv:2407.16741Xingyao Wang, Boxuan Li, Yufan Song, et al.2024 · 221 citations
  55. AlpaGasus: Training A Better Alpaca with Fewer DataarXiv:2307.08701Lichang Chen, Shiyang Li, Jun Yan, et al.2023 · 220 citations
  56. Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language ModelsarXiv:2308.16149Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.2023 · 218 citations
  57. FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative FlowConference on Empirical Methods in Natural Language Processing (EMNLP)Xuezhe Ma, Chunting Zhou, Xian Li, et al.2019 · 218 citations
  58. AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent BehaviorsarXiv:2308.10848Weize Chen, Yusheng Su, Jingwei Zuo, et al.2023 · 217 citations
  59. Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LuncharXiv:2311.03099Le Yu, Bowen Yu, Haiyang Yu, et al.2023 · 217 citations
  60. Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 217 citations
  61. 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
  62. InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal ModelsarXiv:2504.10479Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.2025 · 216 citations
  63. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
  64. LLM+P: Empowering Large Language Models with Optimal Planning ProficiencyarXiv:2304.11477Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.2023 · 216 citations
  65. Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!Findings of the Association for Computational LinguisticsYubo Ma, Yixin Cao, Yong Hong, et al.2023 · 212 citations
  66. Language Models of Code are Few-Shot Commonsense LearnersConference on Empirical Methods in Natural Language Processing (EMNLP)Aman Madaan, Shuyan Zhou, Uri Alon, et al.2022 · 212 citations
  67. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder PipelinearXiv:2406.11939Tianle Li, Wei-Lin Chiang, Evan Frick, et al.2024 · 210 citations
  68. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  69. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  70. EAGLE: Speculative Sampling Requires Rethinking Feature UncertaintyarXiv:2401.15077Yuhui Li, Fangyun Wei, Chao Zhang, et al.2024 · 208 citations
  71. Optimus: Organizing Sentences via Pre-trained Modeling of a Latent SpaceConference on Empirical Methods in Natural Language Processing (EMNLP)Chunyuan Li, Xiang Gao, Yuan Li, et al.2020 · 208 citations
  72. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  73. Language Model Tokenizers Introduce Unfairness Between LanguagesConference on Neural Information Processing Systems (NeurIPS)Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.2023 · 206 citations
  74. Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
  75. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
  76. Model Tells You What to Discard: Adaptive KV Cache Compression for LLMsarXiv:2310.01801Suyu Ge, Yunan Zhang, Liyuan Liu, et al.2023 · 202 citations
  77. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree SearchConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.2024 · 200 citations
  78. A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsFindings of the Association for Computational LinguisticsMd Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.2023 · 200 citations
  79. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
  80. DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code IntelligencearXiv:2406.11931DeepSeek-AI, Qihao Zhu, Daya Guo, et al.2024 · 196 citations
  81. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
  82. Tool Learning with Large Language Models: A SurveyFrontiers of Computer ScienceChangle Qu, Sunhao Dai, Xiaochi Wei, et al.2024 · 195 citations
  83. Making Retrieval-Augmented Language Models Robust to Irrelevant ContextarXiv:2310.01558Ori Yoran, Tomer Wolfson, Ori Ram, et al.2023 · 195 citations
  84. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
  85. WebVoyager: Building an End-to-End Web Agent with Large Multimodal ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hongliang He, Wenlin Yao, Kaixin Ma, et al.2024 · 191 citations
  86. CodeS: Towards Building Open-source Language Models for Text-to-SQLarXiv:2402.16347Haoyang Li, Jing Zhang, Hanbing Liu, et al.2024 · 190 citations
  87. LawBench: Benchmarking Legal Knowledge of Large Language ModelsarXiv:2309.16289Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.2023 · 188 citations
  88. Effective Long-Context Scaling of Foundation ModelsarXiv:2309.16039Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.2023 · 184 citations
  89. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  90. Large Language Models are few(1)-shot Table ReasonersFindings of the Association for Computational LinguisticsWenhu Chen2023 · 182 citations
  91. The False Promise of Imitating Proprietary LLMsarXiv:2305.15717Arnav Gudibande, Eric Wallace, Charlie Snell, et al.2023 · 182 citations
  92. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
  93. InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and EfficiencyarXiv:2508.18265Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.2025 · 179 citations
  94. LILA: A Unified Benchmark for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.2022 · 179 citations
  95. KernelBench: Can LLMs Write Efficient GPU Kernels?arXiv:2502.10517Anne Ouyang, Simon Guo, Simran Arora, et al.2025 · 178 citations
  96. Large Language Diffusion ModelsConference on Neural Information Processing Systems (NeurIPS)Shen Nie, Fengqi Zhu, Zebin You, et al.2025 · 178 citations
  97. Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal ProofsarXiv:2210.12283Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.2022 · 178 citations
  98. 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
  99. Baldur: Whole-Proof Generation and Repair with Large Language ModelsarXiv:2303.04910Emily First, Markus N. Rabe, Talia Ringer, et al.2023 · 175 citations
  100. Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task AgentsarXiv:2302.01560Zihao Wang, Shaofei Cai, Guanzhou Chen, et al.2023 · 174 citations

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