Elamur Research⌕
☰
home / authors / Edwin Chen / cited by

Who cites Edwin Chen

358 citations of their works from 328 papers of our library (of the 149,439 whose bibliographies we read) · 104 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Edwin Chen

1 2

  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. ELEPHANT: Measuring and understanding social sycophancy in LLMsScienceMyra Cheng, Sunny Yu, Cinoo Lee, et al.2025 · 188 citations
  25. 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
  26. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  27. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
  28. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
  29. The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False DatasetsarXiv:2310.06824Samuel Marks, Max Tegmark2023 · 169 citations
  30. 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
  31. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  32. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
  33. 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
  34. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  35. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
  36. 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
  37. Fundamental Limitations of Alignment in Large Language ModelsarXiv:2304.11082Yotam Wolf, Noam Wies, Oshri Avnery, et al.2023 · 114 citations
  38. 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
  39. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  40. 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
  41. 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
  42. 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
  43. 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
  44. 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
  45. 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
  46. 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
  47. 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
  48. Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
  49. 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
  50. SALMON: Self-Alignment with Instructable Reward ModelsarXiv:2310.05910Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.2023 · 41 citations
  51. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
  52. 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
  53. 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
  54. Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge EvaluationarXiv:2306.05783Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.2023 · 34 citations
  55. 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
  56. Language Models as Science TutorsarXiv:2402.11111Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.2024 · 30 citations
  57. 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
  58. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 27 citations
  59. 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
  60. Quality-Diversity through AI FeedbackarXiv:2310.13032Herbie Bradley, Andrew Dai, Hannah Teufel, et al.2023 · 19 citations
  61. Conformity in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaochen Zhu, Caiqi Zhang, Tom Stafford, et al.2025 · 18 citations
  62. 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
  63. 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
  64. Evaluating Large Language Models for Health-related Queries with PresuppositionsFindings of the Association for Computational LinguisticsNavreet Kaur, Monojit Choudhury, Danish Pruthi2024 · 15 citations
  65. Preference Optimization for Reasoning with Pseudo FeedbackarXiv:2411.16345Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.2024 · 15 citations
  66. 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
  67. 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
  68. 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
  69. 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
  70. 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
  71. 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
  72. 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
  73. 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
  74. 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
  75. 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
  76. Task Matters: Knowledge Requirements Shape LLM Responses to Context–Memory ConflictFindings of the Association for Computational LinguisticsKaiser Sun, Fan Bai, Mark Dredze2026 · 3 citations
  77. 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
  78. 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
  79. 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
  80. Learning Multilingual Agentic Policy to Control SycophancyConference of the European Chapter of the Association for Computational Linguistics (EACL)Leonardo Ranaldi, Giulia Pucci2026 · 2 citations
  81. Persona Jailbreaking in Large Language ModelsFindings of the Association for Computational LinguisticsJivnesh Sandhan, Fei Cheng, Tushar Sandhan, et al.2026 · 2 citations
  82. 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
  83. 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
  84. 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
  85. 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
  86. SycoBench-600: Measuring Sycophancy and Correction Selectivity in LLM AssistantsFindings of the Association for Computational LinguisticsDebu Sinha2026 · 1 citation
  87. The Pluralistic Moral Gap: Understanding Moral Judgment and Value Differences between Humans and Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Giuseppe Russo, Debora Nozza, Paul Röttger, et al.2026 · 1 citation
  88. Trajectory Signatures of Deception in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Viraaji Mothukuri, Reza M. Parizi2026 · 1 citation
  89. Understanding and Mitigating Political Stance Cross-topic Generalization in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jiayi Zhang, Shu Yang, Junchao Wu, et al.2026 · 1 citation
  90. Agentic Oversight via Dialectic ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Leonardo Ranaldi, Federico Ranaldi2026
  91. At Your Own PACE: A Causal Framework for Evaluating EQ in LLMsFindings of the Association for Computational LinguisticsLei Lyu, Shengling Wang, Ke Chao, et al.2026
  92. Bridging Cognition and Affect: Emotion-Aware Opinion Summarization using LLMsFindings of the Association for Computational LinguisticsArnav Attri, Anuj Attri2026
  93. Computational models of pragmatic reasoning with flexible generation of meaning and expression alternativesarXiv:2607.18443Polina Tsvilodub, Fausto Carcassi, Michael Franke2026
  94. CoopValue: Revealing LLM Value Preferences Through Multi-Agent CooperationFindings of the Association for Computational LinguisticsZee Hen Tang, Mi-Yen Yeh2026
  95. DialDefer: A Framework for Detecting and Mitigating LLM Dialogic DeferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Parisa Rabbani, Priyam Sahoo, Ruben Mathew, et al.2026
  96. Evaluating Language Model Pluralism through In-the-wild Crowd DiscussionsAnnual Meeting of the Association for Computational Linguistics (ACL)Gagan Mundada, Rohan Surana, Nandhini Swaminathan, et al.2026
  97. Faithfulness vs. Safety: Evaluating LLM Behavior Under Counterfactual Medical EvidenceFindings of the Association for Computational LinguisticsKaijie Mo, Siddhartha Venkatayogi, Chantal Shaib, et al.2026
  98. Feeling Right vs. Being Right: How AI Sycophancy Affects Value-Laden DeliberationAnnual Meeting of the Association for Computational Linguistics (ACL)Jeongwoo Ryu, Soomin Kim, Jinsu Eun, et al.2026
  99. Generalizing Trust: Weak-to-Strong Trustworthiness in Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Lillian Sun, Martin Pawelczyk, Zhenting Qi, et al.2026
  100. Interpretable Semantic Gradients in SSD: A PCA Sweep Approach and a Case Study on AI DiscourseFindings of the Association for Computational LinguisticsHubert Plisiecki, Maria Leniarska, Jan Piotrowski, et al.2026

1 2

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/edwin-chen/cited-by/