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Who cites Craig Pettit

358 citations of their works from 328 papers of our library (of the 149,439 whose bibliographies we read) · 122 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Craig Pettit

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  1. GPT-4 Technical ReportarXiv:2303.08774OpenAI, Josh Achiam, Steven Adler, et al.2023 · 13,036 citations
  2. 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
  3. Constitutional AI: Harmlessness from AI FeedbackarXiv:2212.08073Yuntao Bai, Saurav Kadavath, Sandipan Kundu, et al.2022 · 1,028 citations
  4. GPQA: A Graduate-Level Google-Proof Q&A BenchmarkarXiv:2311.12022David Rein, Betty Li Hou, Asa Cooper Stickland, et al.2023 · 1,018 citations
  5. Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
  6. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
  7. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingConference on Neural Information Processing Systems (NeurIPS)Miles Turpin, Julian Michael, Ethan Perez, et al.2023 · 586 citations
  8. OpenAssistant Conversations — Democratizing Large Language Model AlignmentarXiv:2304.07327Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, et al.2023 · 518 citations
  9. Inference-Time Intervention: Eliciting Truthful Answers from a Language ModelConference on Neural Information Processing Systems (NeurIPS)Kenneth Li, Oam Patel, Fernanda Viegas, et al.2023 · 492 citations
  10. AlpacaFarm: A Simulation Framework for Methods that Learn from Human FeedbackConference on Neural Information Processing Systems (NeurIPS)Yann Dubois, Xuechen Li, Rohan Taori, et al.2023 · 456 citations
  11. Whose Opinions Do Language Models Reflect?arXiv:2303.17548Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al.2023 · 414 citations
  12. Representation Engineering: A Top-Down Approach to AI TransparencyarXiv:2310.01405Andy Zou, Long Phan, Sarah Chen, et al.2023 · 397 citations
  13. Towards Understanding Sycophancy in Language ModelsarXiv:2310.13548Mrinank Sharma, Meg Tong, Tomasz Korbak, et al.2023 · 384 citations
  14. Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 328 citations
  15. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  16. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
  17. Towards Measuring the Representation of Subjective Global Opinions in Language ModelsarXiv:2306.16388Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 270 citations
  18. Measuring Faithfulness in Chain-of-Thought ReasoningarXiv:2307.13702Tamera Lanham, Anna Chen, Ansh Radhakrishnan, et al.2023 · 262 citations
  19. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  20. 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
  21. 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
  22. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  23. 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
  24. Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
  25. ELEPHANT: Measuring and understanding social sycophancy in LLMsScienceMyra Cheng, Sunny Yu, Cinoo Lee, et al.2025 · 188 citations
  26. Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 182 citations
  27. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  28. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
  29. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
  30. The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False DatasetsarXiv:2310.06824Samuel Marks, Max Tegmark2023 · 169 citations
  31. GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherarXiv:2308.06463Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2023 · 168 citations
  32. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
  33. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  34. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
  35. Simple synthetic data reduces sycophancy in large language modelsarXiv:2308.03958Jerry Wei, Da Huang, Yifeng Lu, et al.2023 · 134 citations
  36. Improving Language Model Negotiation with Self-Play and In-Context Learning from AI FeedbackarXiv:2305.10142Yao Fu, Hao Peng, Tushar Khot, et al.2023 · 132 citations
  37. Evaluating the Moral Beliefs Encoded in LLMsConference on Neural Information Processing Systems (NeurIPS)Nino Scherrer, Claudia Shi, Amir Feder, et al.2023 · 129 citations
  38. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  39. Sleeper Agents: Training Deceptive LLMs that Persist Through Safety TrainingarXiv:2401.05566Evan Hubinger, Carson Denison, Jesse Mu, et al.2024 · 123 citations
  40. The Alignment Problem from a Deep Learning PerspectivearXiv:2209.00626Richard Ngo, Lawrence Chan, Soren Mindermann2022 · 121 citations
  41. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
  42. ProcessBench: Identifying Process Errors in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Chujie Zheng, Zhenru Zhang, Beichen Zhang, et al.2025 · 116 citations
  43. Fundamental Limitations of Alignment in Large Language ModelsarXiv:2304.11082Yotam Wolf, Noam Wies, Oshri Avnery, et al.2023 · 114 citations
  44. 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
  45. Studying Large Language Model Generalization with Influence FunctionsarXiv:2308.03296Roger Grosse, Juhan Bae, Cem Anil, et al.2023 · 105 citations
  46. Model evaluation for extreme risksarXiv:2305.15324Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, et al.2023 · 104 citations
  47. Debating with More Persuasive LLMs Leads to More Truthful AnswersarXiv:2402.06782Akbir Khan, John Hughes, Dan Valentine, et al.2024 · 101 citations
  48. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  49. 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
  50. Moral Foundations of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Marwa Abdulhai, Gregory Serapio-García, Clement Crepy, et al.2024 · 94 citations
  51. 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
  52. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  53. 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
  54. 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
  55. Generating Benchmarks for Factuality Evaluation of Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Dor Muhlgay, Ori Ram, Inbal Magar, et al.2024 · 81 citations
  56. Toward Self-Improvement of LLMs via Imagination, Searching, and CriticizingConference on Neural Information Processing Systems (NeurIPS)Ye Tian, Baolin Peng, Linfeng Song, et al.2024 · 80 citations
  57. 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
  58. ARB: Advanced Reasoning Benchmark for Large Language ModelsarXiv:2307.13692Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, et al.2023 · 66 citations
  59. Monitoring Reasoning Models for Misbehavior and the Risks of Promoting ObfuscationarXiv:2503.11926Bowen Baker, Joost Huizinga, Leo Gao, et al.2025 · 63 citations
  60. Unintended Impacts of LLM Alignment on Global RepresentationAnnual Meeting of the Association for Computational Linguistics (ACL)Michael J Ryan, William Held, Diyi Yang2024 · 57 citations
  61. Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackarXiv:2303.05453Hannah Rose Kirk, Bertie Vidgen, Paul Rottger, et al.2023 · 57 citations
  62. Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
  63. NormAd: A Framework for Measuring the Cultural Adaptability of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Abhinav Rao, Akhila Yerukola, Vishwa Shah, et al.2025 · 46 citations
  64. SALMON: Self-Alignment with Instructable Reward ModelsarXiv:2310.05910Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.2023 · 41 citations
  65. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
  66. Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and ParaphrasingarXiv:2305.16635Jaehun Jung, Peter West, Liwei Jiang, et al.2023 · 36 citations
  67. Benchmarking Distributional Alignment of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto2025 · 35 citations
  68. Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge EvaluationarXiv:2306.05783Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.2023 · 34 citations
  69. SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model SafetyarXiv:2404.05399Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.2024 · 33 citations
  70. Language Models as Science TutorsarXiv:2402.11111Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.2024 · 30 citations
  71. Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the AboveAnnual Meeting of the Association for Computational Linguistics (ACL)Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber2025 · 28 citations
  72. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 27 citations
  73. Language Models in Dialogue: Conversational Maxims for Human-AI InteractionsFindings of the Association for Computational LinguisticsErik Miehling, Manish Nagireddy, Prasanna Sattigeri, et al.2024 · 23 citations
  74. Quality-Diversity through AI FeedbackarXiv:2310.13032Herbie Bradley, Andrew Dai, Hannah Teufel, et al.2023 · 19 citations
  75. Conformity in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaochen Zhu, Caiqi Zhang, Tom Stafford, et al.2025 · 18 citations
  76. DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning GraphConference on Neural Information Processing Systems (NeurIPS)Zhehao Zhang, Jiaao Chen, Diyi Yang2024 · 17 citations
  77. Measuring Chain of Thought Faithfulness by Unlearning Reasoning StepsConference on Empirical Methods in Natural Language Processing (EMNLP)Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, et al.2025 · 15 citations
  78. Evaluating Large Language Models for Health-related Queries with PresuppositionsFindings of the Association for Computational LinguisticsNavreet Kaur, Monojit Choudhury, Danish Pruthi2024 · 15 citations
  79. Preference Optimization for Reasoning with Pseudo FeedbackarXiv:2411.16345Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.2024 · 15 citations
  80. Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target AtomsAnnual Meeting of the Association for Computational Linguistics (ACL)Mengru Wang, Ziwen Xu, Shengyu Mao, et al.2025 · 14 citations
  81. Aligning Large Language Models with Human Opinions through Persona Selection and Value — Belief — Norm ReasoningarXiv:2311.08385Do Xuan Long, Kenji Kawaguchi, Min-Yen Kan, et al.2023 · 12 citations
  82. Multiple LLM Agents Debate for Equitable Cultural AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Dayeon Ki, Rachel Rudinger, Tianyi Zhou, et al.2025 · 10 citations
  83. Cancer-Myth: Evaluating Large Language Models on Patient Questions with False PresuppositionsarXiv:2504.11373Wang Bill Zhu, Tianqi Chen, Xinyan Velocity Yu, et al.2025 · 7 citations
  84. Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Wenrui Zhou, Mohamed Hendy, Shu Yang, et al.2026 · 6 citations
  85. Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is MissingTransactions of the Association for Computational Linguistics (TACL)Dennis Ulmer, Alexandra Lorson, Ivan Titov, et al.2026 · 4 citations
  86. Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken EnglishProceedings of the AAAI/ACM Conference on AI Ethics and SocietyBryce Anderson, Riley Galpin, Tom S. Juzek2025 · 4 citations
  87. Confidence Should Be Calibrated More Than One Turn DeepAnnual Meeting of the Association for Computational Linguistics (ACL)Zhaohan Zhang, Chengzhengxu Li, Xiaoming Liu, et al.2026 · 3 citations
  88. Evaluating the Effect of Retrieval Augmentation on Social BiasesConference of the European Chapter of the Association for Computational Linguistics (EACL)Tianhui Zhang, Yi Zhou, Danushka Bollegala2026 · 3 citations
  89. LLM-Powered Benchmark Factory: Reliable, Generic, and EfficientAnnual Meeting of the Association for Computational Linguistics (ACL)Peiwen Yuan, Shaoxiong Feng, Yiwei Li, et al.2026 · 3 citations
  90. Task Matters: Knowledge Requirements Shape LLM Responses to Context–Memory ConflictFindings of the Association for Computational LinguisticsKaiser Sun, Fan Bai, Mark Dredze2026 · 3 citations
  91. Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Chi Zhang, Wenxuan Ding, Jiale Liu, et al.2026 · 2 citations
  92. From Belief Entrenchment to Robust Reasoning in LLM AgentsTransactions of the Association for Computational Linguistics (TACL)Jihwan Oh, Minchan Jeong, Jongwoo Ko, et al.2026 · 2 citations
  93. From Fact to Judgment: Investigating the Impact of Task Framing on LLM Conviction in Dialogue SystemsInternational Workshop on Spoken Dialogue System TechnologyParisa Rabbani, Nimet Beyza Bozdag, Dilek Hakkani-Tur2026 · 2 citations
  94. Learning Multilingual Agentic Policy to Control SycophancyConference of the European Chapter of the Association for Computational Linguistics (EACL)Leonardo Ranaldi, Giulia Pucci2026 · 2 citations
  95. Persona Jailbreaking in Large Language ModelsFindings of the Association for Computational LinguisticsJivnesh Sandhan, Fei Cheng, Tushar Sandhan, et al.2026 · 2 citations
  96. Red-Bandit: Test-Time Adaptation for LLM Red-Teaming via Bandit-Guided LoRA ExpertsAnnual Meeting of the Association for Computational Linguistics (ACL)Christos Ziakas, Nicholas Loo, Nishita Jain, et al.2026 · 2 citations
  97. Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?Annual Meeting of the Association for Computational Linguistics (ACL)Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.2026 · 2 citations
  98. Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and InvestigationFindings of the Association for Computational LinguisticsYuxiang Wang, Xinnan Dai, Wenqi Fan, et al.2026 · 1 citation
  99. Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMsFindings of the Association for Computational LinguisticsGabriele Maraia, Fabio Massimo Zanzotto, Leonardo Ranaldi2026 · 1 citation
  100. SycoBench-600: Measuring Sycophancy and Correction Selectivity in LLM AssistantsFindings of the Association for Computational LinguisticsDebu Sinha2026 · 1 citation

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