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Who cites Tom Conerly

2,945 citations of their works from 2,604 papers of our library (of the 149,439 whose bibliographies we read) · 729 with a page here, the most cited first · page 3 of 8 · 201–300 · ← Tom Conerly

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  1. Fundamental Limitations of Alignment in Large Language ModelsarXiv:2304.11082Yotam Wolf, Noam Wies, Oshri Avnery, et al.2023 · 114 citations
  2. ExpertQA: Expert-Curated Questions and Attributed AnswersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chaitanya Malaviya, Subin Lee, Sihao Chen, et al.2024 · 113 citations
  3. Skywork-Reward: Bag of Tricks for Reward Modeling in LLMsarXiv:2410.18451Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.2024 · 112 citations
  4. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
  5. INSIDE: LLMs' Internal States Retain the Power of Hallucination DetectionarXiv:2402.03744Chao Chen, Kai Liu, Ze Chen, et al.2024 · 108 citations
  6. Mechanistic Interpretability for AI Safety — A ReviewarXiv:2404.14082Leonard Bereska, Efstratios Gavves2024 · 108 citations
  7. Can LLM-Generated Misinformation Be Detected?arXiv:2309.13788Canyu Chen, Kai Shu2023 · 108 citations
  8. Nemotron-4 340B Technical ReportarXiv:2406.11704Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.2024 · 107 citations
  9. R-Judge: Benchmarking Safety Risk Awareness for LLM AgentsFindings of the Association for Computational LinguisticsTongxin Yuan, Zhiwei He, Lingzhong Dong, et al.2024 · 106 citations
  10. Disentangling Length from Quality in Direct Preference OptimizationFindings of the Association for Computational LinguisticsRyan Park, Rafael Rafailov, Stefano Ermon, et al.2024 · 105 citations
  11. Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 105 citations
  12. Statistical Rejection Sampling Improves Preference OptimizationarXiv:2309.06657Tianqi Liu, Yao Zhao, Rishabh Joshi, et al.2023 · 105 citations
  13. Studying Large Language Model Generalization with Influence FunctionsarXiv:2308.03296Roger Grosse, Juhan Bae, Cem Anil, et al.2023 · 105 citations
  14. REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage NormalizationarXiv:2501.03262Jian Hu, Jason Klein Liu, Haotian Xu, et al.2025 · 104 citations
  15. Model evaluation for extreme risksarXiv:2305.15324Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, et al.2023 · 104 citations
  16. Towards Measuring and Modeling “Culture” in LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.2024 · 102 citations
  17. Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter MergingarXiv:2310.11564Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.2023 · 102 citations
  18. What In-Context Learning “Learns” In-Context: Disentangling Task Recognition and Task LearningFindings of the Association for Computational LinguisticsJane Pan, Tianyu Gao, Howard Chen, et al.2023 · 102 citations
  19. The Entropy Mechanism of Reinforcement Learning for Reasoning Language ModelsarXiv:2505.22617Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.2025 · 101 citations
  20. JudgeBench: A Benchmark for Evaluating LLM-based JudgesarXiv:2410.12784Sijun Tan, Siyuan Zhuang, Kyle Montgomery, et al.2024 · 101 citations
  21. CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data AnnotationConference on Empirical Methods in Natural Language Processing (EMNLP)Minzhi Li, Taiwei Shi, Caleb Ziems, et al.2023 · 101 citations
  22. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
  23. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  24. Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-ConstraintarXiv:2312.11456Wei Xiong, Hanze Dong, Chenlu Ye, et al.2023 · 100 citations
  25. R-Tuning: Instructing Large Language Models to Say ‘I Don't Know'Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hanning Zhang, Shizhe Diao, Yong Lin, et al.2024 · 99 citations
  26. Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language ModelsFindings of the Association for Computational LinguisticsWeihang Su, Changyue Wang, Qingyao Ai, et al.2024 · 99 citations
  27. A Long Way to Go: Investigating Length Correlations in RLHFarXiv:2310.03716Prasann Singhal, Tanya Goyal, Jiacheng Xu, et al.2023 · 99 citations
  28. Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtConference on Empirical Methods in Natural Language Processing (EMNLP)Ori Yoran, Tomer Wolfson, Ben Bogin, et al.2023 · 99 citations
  29. Make Your LLM Fully Utilize the ContextConference on Neural Information Processing Systems (NeurIPS)Shengnan An, Zexiong Ma, Zeqi Lin, et al.2024 · 97 citations
  30. Safety Alignment Should Be Made More Than Just a Few Tokens DeeparXiv:2406.05946Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.2024 · 97 citations
  31. A Survey of Confidence Estimation and Calibration in Large Language ModelsarXiv:2311.08298Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.2023 · 97 citations
  32. Towards Best Practices of Activation Patching in Language Models: Metrics and MethodsarXiv:2309.16042Fred Zhang, Neel Nanda2023 · 97 citations
  33. Fact-Checking the Output of Large Language Models via Token-Level Uncertainty QuantificationFindings of the Association for Computational LinguisticsEkaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.2024 · 96 citations
  34. Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Wenxuan Wang, Wenxiang Jiao, Jingyuan Huang, et al.2024 · 96 citations
  35. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  36. Identifying the Risks of LM Agents with an LM-Emulated SandboxarXiv:2309.15817Yangjun Ruan, Honghua Dong, Andrew Wang, et al.2023 · 96 citations
  37. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
  38. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  39. Advancing LLM Reasoning Generalists with Preference TreesarXiv:2404.02078Lifan Yuan, Ganqu Cui, Hanbin Wang, et al.2024 · 94 citations
  40. Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
  41. Retrieval Head Mechanistically Explains Long-Context FactualityarXiv:2404.15574Wenhao Wu, Yizhong Wang, Guangxuan Xiao, et al.2024 · 94 citations
  42. Do-Not-Answer: Evaluating Safeguards in LLMsFindings of the Association for Computational LinguisticsYuxia Wang, Haonan Li, Xudong Han, et al.2024 · 93 citations
  43. WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 92 citations
  44. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
  45. Do Language Models Know When They're Hallucinating References?Findings of the Association for Computational LinguisticsAyush Agrawal; Mirac Suzgun; Lester Mackey;, Adam Tauman Kalai2023 · 92 citations
  46. Proving Test Set Contamination in Black Box Language ModelsarXiv:2310.17623Yonatan Oren, Nicole Meister, Niladri Chatterji, et al.2023 · 92 citations
  47. Skywork: A More Open Bilingual Foundation ModelarXiv:2310.19341Tianwen Wei, Liang Zhao, Lichang Zhang, et al.2023 · 91 citations
  48. Scaling Laws and Interpretability of Learning from Repeated DataarXiv:2205.10487Danny Hernandez, Tom Brown, Tom Conerly, et al.2022 · 91 citations
  49. Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the ArtTransactions of the Association for Computational Linguistics (TACL)Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen2025 · 90 citations
  50. Better & Faster Large Language Models via Multi-token PredictionarXiv:2404.19737Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere, et al.2024 · 90 citations
  51. Alignment for HonestyConference on Neural Information Processing Systems (NeurIPS)Yuqing Yang, Ethan Chern, Xipeng Qiu, et al.2023 · 90 citations
  52. Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable SurveyConference of the European Chapter of the Association for Computational Linguistics (EACL)Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.2023 · 90 citations
  53. 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
  54. ADaPT: As-Needed Decomposition and Planning with Language ModelsFindings of the Association for Computational LinguisticsArchiki Prasad, Alexander Koller, Mareike Hartmann, et al.2024 · 89 citations
  55. Automatically Auditing Large Language Models via Discrete OptimizationarXiv:2303.04381Erik Jones, Anca Dragan, Aditi Raghunathan, et al.2023 · 89 citations
  56. Massive Activations in Large Language ModelsarXiv:2402.17762Mingjie Sun, Xinlei Chen, J. Zico Kolter, et al.2024 · 88 citations
  57. The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual ContextsFindings of the Association for Computational LinguisticsLingfeng Shen, Weiting Tan, Sihao Chen, et al.2024 · 88 citations
  58. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  59. Rethinking Interpretability in the Era of Large Language ModelsarXiv:2402.01761Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.2024 · 87 citations
  60. SORRY-Bench: Systematically Evaluating Large Language Model Safety RefusalarXiv:2406.14598Tinghao Xie, Xiangyu Qi, Yi Zeng, et al.2024 · 87 citations
  61. FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxin Jiang, Yufei Wang, Xingshan Zeng, et al.2024 · 86 citations
  62. Machine Unlearning of Pre-trained Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Yao, Eli Chien, Minxin Du, et al.2024 · 86 citations
  63. PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language ModelsarXiv:2404.02948Fanxu Meng, Zhaohui Wang, Muhan Zhang2024 · 86 citations
  64. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMsConference on Neural Information Processing Systems (NeurIPS)Laura Ruis, Akbir Khan, Stella Biderman, et al.2022 · 86 citations
  65. Benchmark Data Contamination of Large Language Models: A SurveyarXiv:2406.04244Cheng Xu, Shuhao Guan, Derek Greene, et al.2024 · 85 citations
  66. LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations
  67. On Prompt-Driven Safeguarding for Large Language ModelsarXiv:2401.18018Chujie Zheng, Fan Yin, Hao Zhou, et al.2024 · 85 citations
  68. A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models EasilyarXiv:2311.08268Peng Ding, Jun Kuang, Dan Ma, et al.2023 · 85 citations
  69. Detoxifying Large Language Models via Knowledge EditingAnnual Meeting of the Association for Computational Linguistics (ACL)Mengru Wang, Ningyu Zhang, Ziwen Xu, et al.2024 · 84 citations
  70. Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationTransactions of the Association for Computational Linguistics (TACL)Patrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 citations
  71. Selectively Answering Ambiguous QuestionsConference on Empirical Methods in Natural Language Processing (EMNLP)Jeremy Cole, Michael Zhang, Daniel Gillick, et al.2023 · 84 citations
  72. Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Gangwoo Kim, Sungdong Kim, Byeongguk Jeon, et al.2023 · 84 citations
  73. PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human PreferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Jiaming Ji, Donghai Hong, Borong Zhang, et al.2025 · 83 citations
  74. ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMsarXiv:2402.11753Fengqing Jiang, Zhangchen Xu, Luyao Niu, et al.2024 · 83 citations
  75. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 83 citations
  76. The Instruction Hierarchy: Training LLMs to Prioritize Privileged InstructionsarXiv:2404.13208Eric Wallace, Kai Xiao, Reimar Leike, et al.2024 · 83 citations
  77. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial AttacksarXiv:2310.10844Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.2023 · 83 citations
  78. HelpSteer2: Open-source dataset for training top-performing reward modelsarXiv:2406.08673Zhilin Wang, Yi Dong, Olivier Delalleau, et al.2024 · 82 citations
  79. MART: Improving LLM Safety with Multi-round Automatic Red-TeamingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Suyu Ge, Chunting Zhou, Rui Hou, et al.2024 · 82 citations
  80. Smaug: Fixing Failure Modes of Preference Optimisation with DPO-PositivearXiv:2402.13228Arka Pal, Deep Karkhanis, Samuel Dooley, et al.2024 · 82 citations
  81. Does Writing with Language Models Reduce Content Diversity?arXiv:2309.05196Vishakh Padmakumar, He He2023 · 82 citations
  82. Style Over Substance: Evaluation Biases for Large Language ModelsInternational Conference on Computational Linguistics (COLING)Minghao Wu, Alham Fikri Aji2025 · 81 citations
  83. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-SolvingarXiv:2407.13690Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.2024 · 81 citations
  84. D4: Improving LLM Pretraining via Document De-Duplication and DiversificationConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.2023 · 81 citations
  85. Finding Alignments Between Interpretable Causal Variables and Distributed Neural RepresentationsarXiv:2303.02536Atticus Geiger, Zhengxuan Wu, Christopher Potts, et al.2023 · 81 citations
  86. Interpretability at Scale: Identifying Causal Mechanisms in AlpacaConference on Neural Information Processing Systems (NeurIPS)Zhengxuan Wu, Atticus Geiger, Thomas Icard, et al.2023 · 81 citations
  87. Common 7B Language Models Already Possess Strong Math CapabilitiesarXiv:2403.04706Chen Li, Weiqi Wang, Jingcheng Hu, et al.2024 · 79 citations
  88. Multilingual Instruction Tuning With Just a Pinch of MultilingualityFindings of the Association for Computational LinguisticsUri Shaham, Jonathan Herzig, Roee Aharoni, et al.2024 · 78 citations
  89. Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMsarXiv:2308.13387Yuxia Wang, Haonan Li, Xudong Han, et al.2023 · 78 citations
  90. LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Haitao Li, You Chen, Qingyao Ai, et al.2024 · 77 citations
  91. Measuring Political Bias in Large Language Models: What Is Said and How It Is SaidAnnual Meeting of the Association for Computational Linguistics (ACL)Yejin Bang, Delong Chen, Nayeon Lee, et al.2024 · 76 citations
  92. OR-Bench: An Over-Refusal Benchmark for Large Language ModelsarXiv:2405.20947Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.2024 · 76 citations
  93. G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language ModelarXiv:2312.11370Jiahui Gao, Renjie Pi, Jipeng Zhang, et al.2023 · 76 citations
  94. Localizing Model Behavior with Path PatchingarXiv:2304.05969Nicholas Goldowsky-Dill, Chris MacLeod, Lucas Sato, et al.2023 · 76 citations
  95. Self-Contrast: Better Reflection Through Inconsistent Solving PerspectivesAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Yongliang Shen, Linjuan Wu, et al.2024 · 75 citations
  96. Wider and Deeper LLM Networks are Fairer LLM EvaluatorsarXiv:2308.01862Xinghua Zhang, Bowen Yu, Haiyang Yu, et al.2023 · 75 citations
  97. Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural DimensionsInternational Conference on Computational Linguistics (COLING)Reem I. Masoud, Ziquan Liu, Martin Ferianc, et al.2025 · 74 citations
  98. Dynamic Early Exit in Reasoning ModelsarXiv:2504.15895Chenxu Yang, Qingyi Si, Yongjie Duan, et al.2025 · 74 citations
  99. QuRating: Selecting High-Quality Data for Training Language ModelsarXiv:2402.09739Alexander Wettig, Aatmik Gupta, Saumya Malik, et al.2024 · 74 citations
  100. ReCEval: Evaluating Reasoning Chains via Correctness and InformativenessConference on Empirical Methods in Natural Language Processing (EMNLP)Archiki Prasad, Swarnadeep Saha, Xiang Zhou, et al.2023 · 73 citations

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