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Who cites Daniel Selsam

11,840 citations of their works from 11,531 papers of our library (of the 149,439 whose bibliographies we read) · 2,589 with a page here, the most cited first · page 3 of 26 · 201–300 · ← Daniel Selsam

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  1. DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT ModelsConference on Neural Information Processing Systems (NeurIPS)Boxin Wang, Weixin Chen, Hengzhi Pei, et al.2023 · 259 citations
  2. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  3. The Curse of Recursion: Training on Generated Data Makes Models ForgetarXiv:2305.17493Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, et al.2023 · 255 citations
  4. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
  5. InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingLecture notes in computer scienceYi Wang, Kunchang Li, Xinhao Li, et al.2024 · 253 citations
  6. 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
  7. Personality Traits in Large Language ModelsarXiv:2307.00184Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.2023 · 252 citations
  8. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 252 citations
  9. Tree of Attacks: Jailbreaking Black-Box LLMs AutomaticallyConference on Neural Information Processing Systems (NeurIPS)Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.2023 · 251 citations
  10. 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
  11. Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
  12. Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts ArchitecturearXiv:2306.16092Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan2023 · 248 citations
  13. LaMP: When Large Language Models Meet PersonalizationAnnual Meeting of the Association for Computational Linguistics (ACL)Alireza Salemi, Sheshera Mysore, Michael Bendersky, et al.2024 · 246 citations
  14. MedAgents: Large Language Models as Collaborators for Zero-shot Medical ReasoningFindings of the Association for Computational LinguisticsXiangru Tang, Anni Zou, Zhuosheng Zhang, et al.2024 · 246 citations
  15. Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Myra Cheng, Esin Durmus, Dan Jurafsky2023 · 246 citations
  16. XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language ModelsarXiv:2308.01263Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.2023 · 244 citations
  17. Factuality Challenges in the Era of Large Language ModelsNature Machine IntelligenceIsabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.2023 · 243 citations
  18. LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation DatasetarXiv:2309.11998Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 242 citations
  19. Synthetic Data Generation with Large Language Models for Text Classification: Potential and LimitationsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, et al.2023 · 242 citations
  20. FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving PerformancearXiv:2305.05176Lingjiao Chen, Matei Zaharia, James Zou2023 · 241 citations
  21. Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
  22. Visual Adversarial Examples Jailbreak Aligned Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceXiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.2023 · 240 citations
  23. WildChat: 1M ChatGPT Interaction Logs in the WildarXiv:2405.01470Wenting Zhao, Xiang Ren, Jack Hessel, et al.2024 · 239 citations
  24. Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionarXiv:2302.12173Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, et al.2023 · 239 citations
  25. Qwen2-Audio Technical ReportarXiv:2407.10759Yunfei Chu, Jin Xu, Qian Yang, et al.2024 · 238 citations
  26. Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video UnderstandingarXiv:2306.02858Hang Zhang, Xin Li, Lidong Bing2023 · 238 citations
  27. Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Yikang Shen, Qinhong Zhou, et al.2023 · 236 citations
  28. Detecting and Preventing Hallucinations in Large Vision Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceAnisha Gunjal, Jihan Yin, Erhan Bas2023 · 235 citations
  29. 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
  30. Evaluating Open-Domain Question Answering in the Era of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ehsan Kamalloo, Nouha Dziri, Charles Clarke, et al.2023 · 233 citations
  31. 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
  32. GAIA: a benchmark for General AI AssistantsarXiv:2311.12983Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.2023 · 232 citations
  33. LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelarXiv:2304.15010Peng Gao, Jiaming Han, Renrui Zhang, et al.2023 · 229 citations
  34. Qwen2.5-Omni Technical ReportarXiv:2503.20215Jin Xu, Zhifang Guo, Jinzheng He, et al.2025 · 227 citations
  35. How Language Model Hallucinations Can SnowballarXiv:2305.13534Muru Zhang, Ofir Press, William Merrill, et al.2023 · 226 citations
  36. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingarXiv:2309.17452Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 225 citations
  37. Accelerating scientific discovery with Co-ScientistNatureJuraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.2025 · 224 citations
  38. DataComp: In search of the next generation of multimodal datasetsConference on Neural Information Processing Systems (NeurIPS)Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, et al.2023 · 224 citations
  39. Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought PromptingarXiv:2305.07004Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.2023 · 224 citations
  40. Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingarXiv:2306.01693Zeqiu Wu, Yushi Hu, Weijia Shi, et al.2023 · 223 citations
  41. GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical InformationBioinformaticsQiao Jin, Yifan Yang, Qingyu Chen, et al.2023 · 223 citations
  42. Self-planning Code Generation with Large Language ModelsACM Transactions on Software Engineering and MethodologyXue Jiang, Yihong Dong, Lecheng Wang, et al.2023 · 223 citations
  43. Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionZhang Li, Biao Yang, Qiang Liu, et al.2023 · 222 citations
  44. PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeConference on Neural Information Processing Systems (NeurIPS)Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.2022 · 222 citations
  45. OpenHands: An Open Platform for AI Software Developers as Generalist AgentsarXiv:2407.16741Xingyao Wang, Boxuan Li, Yufan Song, et al.2024 · 221 citations
  46. AlpaGasus: Training A Better Alpaca with Fewer DataarXiv:2307.08701Lichang Chen, Shiyang Li, Jun Yan, et al.2023 · 220 citations
  47. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
  48. 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
  49. Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mosh Levy, Alon Jacoby, Yoav Goldberg2024 · 217 citations
  50. AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent BehaviorsarXiv:2308.10848Weize Chen, Yusheng Su, Jingwei Zuo, et al.2023 · 217 citations
  51. Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4arXiv:2304.03439Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.2023 · 217 citations
  52. RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human FeedbackIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianyu Yu, Yuan Yao, Haoye Zhang, et al.2023 · 217 citations
  53. Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 217 citations
  54. 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
  55. 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
  56. 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
  57. LLM+P: Empowering Large Language Models with Optimal Planning ProficiencyarXiv:2304.11477Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.2023 · 216 citations
  58. TinyStories: How Small Can Language Models Be and Still Speak Coherent English?Ronen Eldan, Yuanzhi Li2023 · 213 citations
  59. Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine TranslationarXiv:2401.08417Haoran Xu, Amr Sharaf, Yunmo Chen, et al.2024 · 212 citations
  60. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
  61. Ring Attention with Blockwise Transformers for Near-Infinite ContextarXiv:2310.01889Hao Liu, Matei Zaharia, Pieter Abbeel2023 · 212 citations
  62. Sources of Hallucination by Large Language Models on Inference TasksFindings of the Association for Computational LinguisticsNick McKenna, Tianyi Li, Liang Cheng, et al.2023 · 212 citations
  63. Search-o1: Agentic Search-Enhanced Large Reasoning ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 211 citations
  64. ChemCrow: Augmenting large-language models with chemistry toolsarXiv:2304.05376Andres M Bran, Sam Cox, Oliver Schilter, et al.2023 · 211 citations
  65. Scalable Extraction of Training Data from (Production) Language ModelsarXiv:2311.17035Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.2023 · 211 citations
  66. 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
  67. Shikra: Unleashing Multimodal LLM's Referential Dialogue MagicarXiv:2306.15195Keqin Chen, Zhao Zhang, Weili Zeng, et al.2023 · 210 citations
  68. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  69. SALMONN: Towards Generic Hearing Abilities for Large Language ModelsarXiv:2310.13289Changli Tang, Wenyi Yu, Guangzhi Sun, et al.2023 · 209 citations
  70. What Can Transformers Learn In-Context? A Case Study of Simple Function ClassesConference on Neural Information Processing Systems (NeurIPS)Shivam Garg, Dimitris Tsipras, Percy Liang, et al.2022 · 209 citations
  71. DeepSeek-VL: Towards Real-World Vision-Language UnderstandingarXiv:2403.05525Haoyu Lu, Wen Liu, Bo Zhang, et al.2024 · 208 citations
  72. RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Cheng Niu, Yuanhao Wu, Juno Zhu, et al.2024 · 207 citations
  73. LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language ModelsarXiv:2305.13711Yen-Ting Lin, Yun-Nung Chen2023 · 207 citations
  74. NExT-GPT: Any-to-Any Multimodal LLMarXiv:2309.05519Shengqiong Wu, Hao Fei, Leigang Qu, et al.2023 · 207 citations
  75. BLINK: Multimodal Large Language Models Can See but Not PerceiveLecture notes in computer scienceXingyu Fu, Yushi Hu, Bangzheng Li, et al.2024 · 206 citations
  76. Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Oded Ovadia, Menachem Brief, Moshik Mishaeli, et al.2024 · 206 citations
  77. 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
  78. Woodpecker: Hallucination Correction for Multimodal Large Language ModelsScience China Information SciencesShukang Yin, Chaoyou Fu, Sirui Zhao, et al.2023 · 206 citations
  79. Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetConference on Neural Information Processing Systems (NeurIPS)Ke Wang, Junting Pan, Weikang Shi, et al.2024 · 203 citations
  80. How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yi Zeng, Hongpeng Lin, Jingwen Zhang, et al.2024 · 202 citations
  81. Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasConference on Neural Information Processing Systems (NeurIPS)Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.2023 · 202 citations
  82. Model Tells You What to Discard: Adaptive KV Cache Compression for LLMsarXiv:2310.01801Suyu Ge, Yunan Zhang, Liyuan Liu, et al.2023 · 202 citations
  83. RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 201 citations
  84. 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
  85. 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
  86. IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian LanguagesarXiv:2305.16307Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.2023 · 200 citations
  87. 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
  88. Will we run out of data? Limits of LLM scaling based on human-generated dataarXiv:2211.04325Pablo Villalobos, Anson Ho, Jaime Sevilla, et al.2022 · 198 citations
  89. Towards Faithful Model Explanation in NLP: A SurveyComputational LinguisticsQing Lyu, Marianna Apidianaki, Chris Callison-Burch2024 · 197 citations
  90. 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
  91. MM-REACT: Prompting ChatGPT for Multimodal Reasoning and ActionarXiv:2303.11381Zhengyuan Yang, Linjie Li, Jianfeng Wang, et al.2023 · 196 citations
  92. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
  93. Tool Learning with Large Language Models: A SurveyFrontiers of Computer ScienceChangle Qu, Sunhao Dai, Xiaochi Wei, et al.2024 · 195 citations
  94. EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language UnderstandingConference on Neural Information Processing Systems (NeurIPS)Karttikeya Mangalam, Raiymbek Akshulakov, Jitendra Malik2023 · 195 citations
  95. InstructUIE: Multi-task Instruction Tuning for Unified Information ExtractionarXiv:2304.08085Xiao Wang, Weikang Zhou, Can Zu, et al.2023 · 194 citations
  96. PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning OptimizationarXiv:2306.05087Yidong Wang, Zhuohao Yu, Zhengran Zeng, et al.2023 · 194 citations
  97. InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model AgentsFindings of the Association for Computational LinguisticsQiusi Zhan, Zhixiang Liang, Zifan Ying, et al.2024 · 193 citations
  98. RAPTOR: Recursive Abstractive Processing for Tree-Organized RetrievalarXiv:2401.18059Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.2024 · 193 citations
  99. GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4Conference on Machine Translation (WMT)Tom Kocmi, Christian Federmann2023 · 192 citations
  100. Multilingual Jailbreak Challenges in Large Language ModelsarXiv:2310.06474Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.2023 · 192 citations

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