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Who cites Sebastian Farquhar

506 citations of their works from 488 papers of our library (of the 149,439 whose bibliographies we read) · 119 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Sebastian Farquhar

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  1. Gemini: A Family of Highly Capable Multimodal ModelsarXiv:2312.11805Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.2023 · 3,050 citations
  2. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextarXiv:2403.05530Gemini Team, Petko Georgiev, Ving Ian Lei, et al.2024 · 1,589 citations
  3. CTRL: A Conditional Transformer Language Model for Controllable GenerationarXiv:1909.05858Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al.2019 · 1,291 citations
  4. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  5. OpenAI o1 System CardarXiv:2412.16720OpenAI, Aaron Jaech, Adam Kalai, et al.2024 · 1,110 citations
  6. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic CapabilitiesarXiv:2507.06261Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.2025 · 974 citations
  7. CogView: Mastering Text-to-Image Generation via TransformersarXiv:2105.13290Ming Ding, Zhuoyi Yang, Wenyi Hong, et al.2021 · 469 citations
  8. BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference DatasetConference on Neural Information Processing Systems (NeurIPS)Jiaming Ji, Mickel Liu, Juntao Dai, et al.2023 · 362 citations
  9. CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingarXiv:2305.11738Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 326 citations
  10. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  11. A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future DirectionsComputational LinguisticsJunchao Wu, Shu Yang, Runzhe Zhan, et al.2025 · 277 citations
  12. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  13. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  14. 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
  15. Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 217 citations
  16. Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
  17. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  18. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
  19. 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
  20. Are aligned neural networks adversarially aligned?Conference on Neural Information Processing Systems (NeurIPS)Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.2023 · 157 citations
  21. Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and MitigationarXiv:2305.15852Niels Mundler, Jingxuan He, Slobodan Jenko, et al.2023 · 152 citations
  22. Unsolved Problems in ML SafetyarXiv:2109.13916Dan Hendrycks, Nicholas Carlini, John Schulman, et al.2021 · 151 citations
  23. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 149 citations
  24. Evaluating the Moral Beliefs Encoded in LLMsConference on Neural Information Processing Systems (NeurIPS)Nino Scherrer, Claudia Shi, Amir Feder, et al.2023 · 129 citations
  25. The WMDP Benchmark: Measuring and Reducing Malicious Use With UnlearningarXiv:2403.03218Nathaniel Li, Alexander Pan, Anjali Gopal, et al.2024 · 127 citations
  26. Fine-tuning Language Models for FactualityarXiv:2311.08401Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.2023 · 127 citations
  27. LM vs LM: Detecting Factual Errors via Cross ExaminationConference on Empirical Methods in Natural Language Processing (EMNLP)Roi Cohen, May Hamri, Mor Geva, et al.2023 · 126 citations
  28. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  29. The Alignment Problem from a Deep Learning PerspectivearXiv:2209.00626Richard Ngo, Lawrence Chan, Soren Mindermann2022 · 121 citations
  30. Alignment of Language AgentsarXiv:2103.14659Zachary Kenton, Tom Everitt, Laura Weidinger, et al.2021 · 120 citations
  31. Gradient based sample selection for online continual learningarXiv:1903.08671Rahaf Aljundi, Min Lin, Baptiste Goujaud, et al.2019 · 115 citations
  32. Can Machines Learn Morality? The Delphi ExperimentarXiv:2110.07574Liwei Jiang, Jena D. Hwang, Chandra Bhagavatula, et al.2021 · 110 citations
  33. INSIDE: LLMs' Internal States Retain the Power of Hallucination DetectionarXiv:2402.03744Chao Chen, Kai Liu, Ze Chen, et al.2024 · 108 citations
  34. Can LLM-Generated Misinformation Be Detected?arXiv:2309.13788Canyu Chen, Kai Shu2023 · 108 citations
  35. Model evaluation for extreme risksarXiv:2305.15324Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, et al.2023 · 104 citations
  36. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  37. A Survey of Confidence Estimation and Calibration in Large Language ModelsarXiv:2311.08298Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.2023 · 97 citations
  38. 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
  39. Do-Not-Answer: Evaluating Safeguards in LLMsFindings of the Association for Computational LinguisticsYuxia Wang, Haonan Li, Xudong Han, et al.2024 · 93 citations
  40. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  41. Selectively Answering Ambiguous QuestionsConference on Empirical Methods in Natural Language Processing (EMNLP)Jeremy Cole, Michael Zhang, Daniel Gillick, et al.2023 · 84 citations
  42. Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMsarXiv:2308.13387Yuxia Wang, Haonan Li, Xudong Han, et al.2023 · 78 citations
  43. Quantifying Uncertainty in Answers from any Language Model and Enhancing their TrustworthinessAnnual Meeting of the Association for Computational Linguistics (ACL)Jiuhai Chen, Jonas Mueller2024 · 72 citations
  44. Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoying Zhang, Baolin Peng, Ye Tian, et al.2024 · 69 citations
  45. LLMs Know More Than They Show: On the Intrinsic Representation of LLM HallucinationsarXiv:2410.02707Hadas Orgad, Michael Toker, Zorik Gekhman, et al.2024 · 68 citations
  46. Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsFindings of the Association for Computational LinguisticsAlfonso Amayuelas, Kyle Wong, Liangming Pan, et al.2024 · 66 citations
  47. Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in ChinchillaarXiv:2307.09458Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.2023 · 58 citations
  48. Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
  49. Unfamiliar Finetuning Examples Control How Language Models HallucinateConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Katie Kang, Eric Wallace, Claire Tomlin, et al.2025 · 47 citations
  50. LUQ: Long-text Uncertainty Quantification for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Caiqi Zhang, Fangyu Liu, Marco Basaldella, et al.2024 · 42 citations
  51. Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?Conference on Empirical Methods in Natural Language Processing (EMNLP)Gal Yona, Roee Aharoni, Mor Geva2024 · 40 citations
  52. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
  53. Through the Lens of Core Competency: Survey on Evaluation of Large Language ModelsarXiv:2308.07902Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.2023 · 35 citations
  54. Knowledge Boundary of Large Language Models: A SurveyAnnual Meeting of the Association for Computational Linguistics (ACL)Moxin Li, Yong Zhao, Wenxuan Zhang, et al.2025 · 30 citations
  55. SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check ConsistencyarXiv:2311.01740Jiaxin Zhang, Zhuohang Li, Kamalika Das, et al.2023 · 28 citations
  56. What is the Role of Small Models in the LLM Era: A SurveyComputational LinguisticsLihu Chen, Gael Varoquaux2024 · 23 citations
  57. Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back HomeAnnual Meeting of the Association for Computational Linguistics (ACL)Viktor Moskvoretskii, Maria Marina, Mikhail Salnikov, et al.2025 · 21 citations
  58. Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?Findings of the Association for Computational LinguisticsZhiting Mei, Christina Zhang, Tenny Yin, et al.2026 · 14 citations
  59. ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenliang Zhang, Xinyu Hu, Huixuan Zhang, et al.2025 · 14 citations
  60. LoGU: Long-form Generation with Uncertainty ExpressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Ruihan Yang, Caiqi Zhang, Zhisong Zhang, et al.2025 · 13 citations
  61. Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.2025 · 13 citations
  62. A Probabilistic Framework for LLM Hallucination Detection via Belief Tree PropagationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bairu Hou, Yang Zhang, Jacob Andreas, et al.2025 · 12 citations
  63. Too Consistent to Detect: A Study of Self-Consistent Errors in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Hexiang Tan, Fei Sun, Sha Liu, et al.2025 · 12 citations
  64. Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data FilteringAnnual Meeting of the Association for Computational Linguistics (ACL)Shuzheng Si, Haozhe Zhao, Gang Chen, et al.2025 · 11 citations
  65. Calibrating Verbal Uncertainty as a Linear Feature to Reduce HallucinationsConference on Empirical Methods in Natural Language Processing (EMNLP)Ziwei Ji, Lei Yu, Yeskendir Koishekenov, et al.2025 · 11 citations
  66. Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2025 · 11 citations
  67. Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.2025 · 10 citations
  68. Thinking Out Loud: Do Reasoning Models Know When They're Right?Conference on Empirical Methods in Natural Language Processing (EMNLP)Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.2025 · 9 citations
  69. Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary PerceptionAnnual Meeting of the Association for Computational Linguistics (ACL)Shiyu Ni, Keping Bi, Jiafeng Guo, et al.2025 · 9 citations
  70. MUR: Momentum Uncertainty guided Reasoning for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hang Yan, Fangzhi Xu, Rongman Xu, et al.2026 · 8 citations
  71. CER: Confidence Enhanced Reasoning in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Ali Razghandi, Seyed Mohammad Hadi Hosseini, Mahdieh Soleymani Baghshah2025 · 8 citations
  72. MetaFaith: Faithful Natural Language Uncertainty Expression in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.2025 · 6 citations
  73. Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias ResultsAnnual Meeting of the Association for Computational Linguistics (ACL)Andrea Santilli, Adam Golinski, Michael Kirchhof, et al.2025 · 6 citations
  74. KnowRL: Exploring Knowledgeable Reinforcement Learning for FactualityAnnual Meeting of the Association for Computational Linguistics (ACL)Baochang Ren, Shuofei Qiao, Ningyu Zhang, et al.2026 · 5 citations
  75. Uncertainty Distillation: Teaching Language Models to Express Semantic ConfidencearXiv:2503.14749Sophia Hager; David Mueller; Kevin Duh;, Nicholas Andrews2025 · 5 citations
  76. 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
  77. Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and OpportunitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Changdae Oh, Seongheon Park, To Eun Kim, et al.2026 · 4 citations
  78. Explaining Sources of Uncertainty in Automated Fact-CheckingAnnual Meeting of the Association for Computational Linguistics (ACL)Jingyi Sun, Greta Warren, Irina Shklovski, et al.2026 · 3 citations
  79. AGSC: Adaptive Granularity and Semantic Clustering for Uncertainty Quantification in Long-text GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Guanran Luo, Wentao Qiu, Wanru Zhao, et al.2026 · 2 citations
  80. Confidence over Time: Confidence Calibration with Temporal Logic for Large Language Model ReasoningFindings of the Association for Computational LinguisticsZhenjiang Mao, Anirudhh Venkat, Artem Bisliouk, et al.2026 · 2 citations
  81. Mind the Gap: Benchmarking LLM Uncertainty and Calibration with Specialty-Aware Clinical QA and Reasoning-Based Behavioural FeaturesConference of the European Chapter of the Association for Computational Linguistics (EACL)Alberto Testoni, Iacer Calixto2026 · 2 citations
  82. BaseCal: Unsupervised Confidence Calibration via Base Model SignalsAnnual Meeting of the Association for Computational Linguistics (ACL)Hexiang Tan, Wanli Yang, Junwei Zhang, et al.2026 · 1 citation
  83. Chain-of-Thought as a Lens: Evaluating Structured Reasoning Alignment between Human Preferences and Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Boxuan Wang, Zhuoyun Li, Xinmiao Huang, et al.2026 · 1 citation
  84. Efficient Self-Evaluation for Diffusion Language Models via Sequence RegenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Linhao Zhong, Linyu Wu, Wen Wang, et al.2026 · 1 citation
  85. From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language ModelsFindings of the Association for Computational LinguisticsJiaxin Zhang, Wendi Cui, Zhuohang Li, et al.2026 · 1 citation
  86. GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of ThoughtsFindings of the Association for Computational LinguisticsWenhao Zeng, Xuteng Zhang, Yuling Shi, et al.2026 · 1 citation
  87. ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, et al.2026 · 1 citation
  88. User Perceptions vs. Proxy LLM Judges: Privacy and Helpfulness in LLM Responses to Privacy-Sensitive ScenariosAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyuan Wu, Roshni Kaushik, Wenkai Li, et al.2026 · 1 citation
  89. Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Weiqing Luo, Zongye Hu, Xiao Wang, et al.2026 · 1 citation
  90. Adaptive Prompt Optimization for Open-Ended Tasks: Uncertainty Preference as a Secondary SignalFindings of the Association for Computational LinguisticsShuyang Zhang, Zhixuan Liu, Zhichen Dong, et al.2026
  91. AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?Findings of the Association for Computational LinguisticsHenan Sun, Kaichi Yu, Yuyao Wang, et al.2026
  92. ARCHITECT: Uncertainty-Aware Dynamic Tool Learning via Causal Intervention for Open-World AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhangyi Wang, Jiexiang Xu, Bingnan Yu, et al.2026
  93. Balancing Classification and Calibration Performance in Decision-Making LLMs via Calibration Aware Reinforcement LearningFindings of the Association for Computational LinguisticsDuygu Nur Yaldiz, Evangelia Spiliopoulou, Zheng Qi, et al.2026
  94. Calibrated? Not for Everyone: How Sexual Orientation and Religious Markers Distort LLM Accuracy and Confidence in Medical QAAnnual Meeting of the Association for Computational Linguistics (ACL)Alberto Testoni, Iacer Calixto2026
  95. Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty EstimationAnnual Meeting of the Association for Computational Linguistics (ACL)Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.2026
  96. Concept rather than Document: Context Compression via AMR-based Conceptual EntropyFindings of the Association for Computational LinguisticsKaize Shi, Xueyao Sun, Xiaohui Tao, et al.2026
  97. Credal Concept Bottleneck Models for Epistemic–Aleatoric Uncertainty DecompositionAnnual Meeting of the Association for Computational Linguistics (ACL)Tanmoy Mukherjee, Thomas Bailleux, Pierre Marquis, et al.2026
  98. DecoCal: Decoding with Calibration in Diffusion Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fan Xu, Huixuan Zhang, Xiaojun Wan2026
  99. Detection of Adversarial Prompts with Model Predictive EntropyFindings of the Association for Computational LinguisticsFranziska Rubenbauer, Sebastian Steindl, Patrick Levi, et al.2026
  100. DisCal: Distribution-Aware Calibration for Mathematical Reasoning Under Character-Level Noisy InputsAnnual Meeting of the Association for Computational Linguistics (ACL)Bo Zhang, Jiawei Zhang, Cong Gao, et al.2026

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