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Who cites Potsawee Manakul

608 citations of their works from 604 papers of our library (of the 149,439 whose bibliographies we read) · 163 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Potsawee Manakul

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  1. Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,974 citations
  2. A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,648 citations
  3. 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
  4. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  5. 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
  6. FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.2023 · 987 citations
  7. 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
  8. WizardLM: Empowering large pre-trained language models to follow complex instructionsInternational Conference on Learning Representations (ICLR)Can Xu, Qingfeng Sun, Kai Zheng, et al.2023 · 741 citations
  9. HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, et al.2023 · 651 citations
  10. MetaGPT: Meta Programming for A Multi-Agent Collaborative FrameworkarXiv:2308.00352Sirui Hong, Mingchen Zhuge, Jiaqi Chen, et al.2023 · 630 citations
  11. Large Legal Fictions: Profiling Legal Hallucinations in Large Language ModelsarXiv:2401.01301 · Journal of Legal Analysis 16, no. 1 (2024): 64-93Matthew Dahl, Varun Magesh, Mirac Suzgun, et al.2024 · 437 citations
  12. Towards Mitigating LLM Hallucination via Self ReflectionFindings of the Association for Computational LinguisticsZiwei Ji, Tiezheng Yu, Yan Xu, et al.2023 · 354 citations
  13. Large Language Models for Information Retrieval: A SurveyACM Transactions on Information SystemsYutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen2023 · 339 citations
  14. CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingarXiv:2305.11738Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 326 citations
  15. Chain-of-Verification Reduces Hallucination in Large Language ModelsarXiv:2309.11495Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, et al.2023 · 305 citations
  16. Large Language Models are Effective Text Rankers with Pairwise Ranking PromptingFindings of the Association for Computational LinguisticsZhen Qin, Rolf Jagerman, Kai Hui, et al.2024 · 300 citations
  17. Ragas: Automated Evaluation of Retrieval Augmented GenerationarXiv:2309.15217Shahul Es, Jithin James, Luis Espinosa-Anke, et al.2023 · 283 citations
  18. Hallucination-Free? Assessing the Reliability of Leading AI Legal Research ToolsarXiv:2405.20362Varun Magesh, Faiz Surani, Matthew Dahl, et al.2024 · 271 citations
  19. DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language ModelsarXiv:2309.03883Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.2023 · 269 citations
  20. Large Language Models for Data Annotation and Synthesis: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Tan, Dawei Li, Song Wang, et al.2024 · 262 citations
  21. OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-AllocationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionQidong Huang, Xiaoyi Dong, Pan Zhang, et al.2023 · 238 citations
  22. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  23. A Survey of Hallucination in Large Foundation ModelsarXiv:2309.05922Vipula Rawte, Amit Sheth, Amitava Das2023 · 226 citations
  24. 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
  25. Prompt Injection attack against LLM-integrated ApplicationsarXiv:2306.05499Yi Liu; Gelei Deng; Yuekang Li; Kailong Wang; Zihao Wang; Xiaofeng Wang; Tianwei Zhang; Yepang Liu; Haoyu Wang; Yan Zheng; Leo Yu Zhang;, Yang Liu2023 · 208 citations
  26. 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
  27. 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
  28. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  29. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  30. The Troubling Emergence of Hallucination in Large Language Models - An Extensive Definition, Quantification, and Prescriptive RemediationsConference on Empirical Methods in Natural Language Processing (EMNLP)Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, et al.2023 · 171 citations
  31. Long-form factuality in large language modelsConference on Neural Information Processing Systems (NeurIPS)Jerry Wei, Chengrun Yang, Xinying Song, et al.2024 · 165 citations
  32. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 161 citations
  33. 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
  34. LLM-based NLG Evaluation: Current Status and ChallengesComputational LinguisticsMingqi Gao, Xinyu Hu, Xunjian Yin, et al.2025 · 153 citations
  35. The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Junyi Li, Jie Chen, Ruiyang Ren, et al.2024 · 153 citations
  36. Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and MitigationarXiv:2305.15852Niels Mundler, Jingxuan He, Slobodan Jenko, et al.2023 · 152 citations
  37. A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence GenerationarXiv:2307.03987Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu2023 · 143 citations
  38. LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation TasksarXiv:2406.18403Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.2024 · 141 citations
  39. Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
  40. 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
  41. INSIDE: LLMs' Internal States Retain the Power of Hallucination DetectionarXiv:2402.03744Chao Chen, Kai Liu, Ze Chen, et al.2024 · 108 citations
  42. Fine-grained Hallucination Detection and Editing for Language ModelsarXiv:2401.06855Abhika Mishra, Akari Asai, Vidhisha Balachandran, et al.2024 · 100 citations
  43. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
  44. 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
  45. 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
  46. A Survey of Confidence Estimation and Calibration in Large Language ModelsarXiv:2311.08298Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.2023 · 97 citations
  47. 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
  48. 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
  49. Pride and Prejudice: LLM Amplifies Self-Bias in Self-RefinementAnnual Meeting of the Association for Computational Linguistics (ACL)Wenda Xu, Guanglei Zhu, Xuandong Zhao, et al.2024 · 88 citations
  50. LLM Comparative Assessment: Zero-shot NLG Evaluation through Pairwise Comparisons using Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Adian Liusie, Potsawee Manakul, Mark Gales2024 · 87 citations
  51. A Survey of Large Language Models in Medicine: Progress, Application, and ChallengearXiv:2311.05112Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.2023 · 87 citations
  52. Retrieval-Augmented Generation for Natural Language Processing: A SurveyArtificial Intelligence ReviewShangyu Wu, Ying Xiong, Yufei Cui, et al.2024 · 86 citations
  53. Selectively Answering Ambiguous QuestionsConference on Empirical Methods in Natural Language Processing (EMNLP)Jeremy Cole, Michael Zhang, Daniel Gillick, et al.2023 · 84 citations
  54. HalluLens: LLM Hallucination BenchmarkAnnual Meeting of the Association for Computational Linguistics (ACL)Yejin Bang, Ziwei Ji, Alan Schelten, et al.2025 · 82 citations
  55. 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
  56. Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model EvaluatorsarXiv:2403.16950Yinhong Liu, Han Zhou, Zhijiang Guo, et al.2024 · 76 citations
  57. 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
  58. Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-JudgeInternational Joint Conference on Natural Language Processing (IJCNLP)Lin Shi, Chiyu Ma, Wenhua Liang, et al.2025 · 71 citations
  59. 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
  60. 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
  61. Monitoring Reasoning Models for Misbehavior and the Risks of Promoting ObfuscationarXiv:2503.11926Bowen Baker, Joost Huizinga, Leo Gao, et al.2025 · 63 citations
  62. Improving Language Models via Plug-and-Play Retrieval FeedbackarXiv:2305.14002Wenhao Yu, Zhihan Zhang, Zhenwen Liang, et al.2023 · 54 citations
  63. On the application of Large Language Models for language teaching and assessment technologyarXiv:2307.08393Andrew Caines, Luca Benedetto, Shiva Taslimipoor, et al.2023 · 51 citations
  64. Attribute First, then Generate: Locally-attributable Grounded Text GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Aviv Slobodkin, Eran Hirsch, Arie Cattan, et al.2024 · 48 citations
  65. 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
  66. Can Multiple-choice Questions Really Be Useful in Detecting the Abilities of LLMs?Language Resources and Evaluation Conference (LREC)Wangyue Li, Liangzhi Li, Tong Xiang, et al.2024 · 47 citations
  67. Towards Mitigating Hallucination in Large Language Models via Self-ReflectionarXiv:2310.06271Ziwei Ji, Tiezheng Yu, Yan Xu, et al.2023 · 47 citations
  68. Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language ModelsarXiv:2308.11764Mohamed Elaraby, Mengyin Lu, Jacob Dunn, et al.2023 · 43 citations
  69. 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
  70. 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
  71. Direct Judgement Preference OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP)PeiFeng Wang, Austin Xu, Yilun Zhou, et al.2025 · 35 citations
  72. Interpretable Unified Language CheckingarXiv:2304.03728Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.2023 · 32 citations
  73. 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
  74. 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
  75. What is the Role of Small Models in the LLM Era: A SurveyComputational LinguisticsLihu Chen, Gael Varoquaux2024 · 23 citations
  76. HALoGEN: Fantastic LLM Hallucinations and Where to Find ThemAnnual Meeting of the Association for Computational Linguistics (ACL)Abhilasha Ravichander, Shrusti Ghela, David Wadden, et al.2025 · 22 citations
  77. IslamicEval 2025: The First Shared Task of Capturing LLMs Hallucination in Islamic ContentArabic Natural Language Processing Conference (ArabicNLP)Hamdy Mubarak, Rana Malhas, Watheq Mansour, et al.2025 · 19 citations
  78. Hallucination Detection in LLMs Using Spectral Features of Attention MapsConference on Empirical Methods in Natural Language Processing (EMNLP)Jakub Binkowski, Denis Janiak, Albert Sawczyn, et al.2025 · 18 citations
  79. Comparing Hallucination Detection Metrics for Multilingual GenerationarXiv:2402.10496Haoqiang Kang, Terra Blevins, Luke Zettlemoyer2024 · 18 citations
  80. Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Chih-Kai Yang, Neo S. Ho, Hung-yi Lee2025 · 17 citations
  81. Aristotle: Mastering Logical Reasoning with A Logic-Complete Decompose-Search-Resolve FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Meng Luo, et al.2025 · 16 citations
  82. Sparks of Science: Hypothesis Generation Using Structured Paper DataarXiv:2504.12976Charles O'Neill, Tirthankar Ghosal, Roberta R\uaileanu, et al.2025 · 16 citations
  83. Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTSFindings of the Association for Computational LinguisticsShijia Xu, Zhou Wu, Xiaolong Jia, et al.2026 · 15 citations
  84. 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
  85. 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
  86. Safer or Luckier? LLMs as Safety Evaluators Are Not Robust to ArtifactsAnnual Meeting of the Association for Computational Linguistics (ACL)Hongyu Chen, Seraphina Goldfarb-Tarrant2025 · 13 citations
  87. 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
  88. What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific PresentationsAnnual Meeting of the Association for Computational Linguistics (ACL)Dongqi Liu, Chenxi Whitehouse, Xi Yu, et al.2025 · 13 citations
  89. From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning TasksarXiv:2409.04168Andreas Stephan, Dawei Zhu, Matthias Aßenmacher, et al.2024 · 13 citations
  90. 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
  91. Prompt-Guided Internal States for Hallucination Detection of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fujie Zhang, Peiqi Yu, Biao Yi, et al.2025 · 12 citations
  92. 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
  93. AraHalluEval: A Fine-grained Hallucination Evaluation Framework for Arabic LLMsArabic Natural Language Processing Conference (ArabicNLP)Aisha Alansari, Hamzah Luqman2025 · 9 citations
  94. Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and AlignmentarXiv:2501.13080Melissa Kazemi Rad, Huy Nghiem, Andy Luo, et al.2025 · 9 citations
  95. 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
  96. 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
  97. 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
  98. Explanatory Summarization with Discourse-Driven PlanningTransactions of the Association for Computational Linguistics (TACL)Dongqi Liu, Xi Yu, Vera Demberg, et al.2025 · 8 citations
  99. Exploiting the English Vocabulary Profile for L2 word-level vocabulary assessment with LLMsWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Stefano Bannò, Kate M. Knill, Mark J. F. Gales2025 · 8 citations
  100. Confidence Estimation for LLMs in Multi-turn InteractionsFindings of the Association for Computational LinguisticsCaiqi Zhang, Ruihan Yang, Xiaochen Zhu, et al.2026 · 7 citations

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