🔗 Who cites «FELM: Benchmarking Factuality Evaluation of Large Language Models»

78 papers of our library cite it (of the 149,439 whose bibliographies we read) · 28 with a page here, the most cited first · ← back to «FELM: Benchmarking Factuality Evaluation of Large Language Models»

1. 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
2. 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
3. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
4. Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
5. 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
6. Long-form factuality in large language modelsConference on Neural Information Processing Systems (NeurIPS)Jerry Wei, Chengrun Yang, Xinying Song, et al.2024 · 165 citations
7. Measuring short-form factuality in large language modelsarXiv:2411.04368Jason Wei, Nguyen Karina, Hyung Won Chung, et al.2024 · 160 citations
8. Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language ModelsFindings of the Association for Computational LinguisticsMiaoran Li, Baolin Peng, Michel Galley, et al.2024 · 87 citations
9. Factuality of Large Language Models: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Yuxia Wang, Minghan Wang, Muhammad Arslan Manzoor, et al.2024 · 77 citations
10. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
11. The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form InputarXiv:2501.03200Alon Jacovi, Andrew Wang, Chris Alberti, et al.2025 · 32 citations
12. Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and EvaluationACM Computing SurveysSteffen Eger, Yong Cao, Jennifer D'Souza, et al.2025 · 25 citations
13. Towards Effective Extraction and Evaluation of Factual ClaimsAnnual Meeting of the Association for Computational Linguistics (ACL)Dasha Metropolitansky, Jonathan Larson2025 · 20 citations
14. FactBench: A Dynamic Benchmark for In-the-Wild Language Model Factuality EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Farima Fatahi Bayat, Lechen Zhang, Sheza Munir, et al.2025 · 16 citations
15. Halwasa: Quantify and Analyze Hallucinations in Large Language Models: Arabic as a Case StudyLanguage Resources and Evaluation Conference (LREC)Hamdy Mubarak, Hend Al-Khalifa, Khaloud Suliman Alkhalefah2024 · 14 citations
16. U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMsarXiv:2412.03205Konstantin Chernyshev, Vitaliy Polshkov, Ekaterina Artemova, et al.2024 · 13 citations
17. 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
18. SimpleQA Verified: A Reliable Factuality Benchmark to Measure Parametric KnowledgearXiv:2509.07968Lukas Haas, Gal Yona, Giovanni D'Antonio, et al.2025 · 12 citations
19. Chinese SafetyQA: A Safety Short-form Factuality Benchmark for Large Language ModelsarXiv:2412.15265Yingshui Tan, Boren Zheng, Baihui Zheng, et al.2024 · 4 citations
20. HalluTruthQA: A Fine-Grained Benchmark for Hallucination Detection, Localization, and Explanation in Arabic Question AnsweringarXiv:2607.20219Abdessalam Bouchekif; Mohammed-En-Nadhir Zighem; Salah Eddine Bekhouche; Hichem Telli; Somaya Eltanbouly; Shahd Gaben; Heba Sbahi; Samer Rashwani; Mutaz Al-Khatib; Emad Mohamed; Mohammed Ghaly;, Abdenour Hadid2026 · 3 citations
21. HAD: HAllucination Detection Language Models Based on a Comprehensive Hallucination TaxonomyAnnual Meeting of the Association for Computational Linguistics (ACL)Fan Xu, Xinyu Hu, Zhenghan Yu, et al.2026 · 1 citation
22. HalluTruthQA-4K: A Fine-Grained Corpus and Annotation Process for Arabic Hallucination Detection and Truth VerificationarXiv:2608.03966Salah Eddine Bekhouche; Abdessalam Bouchekif; Hichem Telli; Mohammed-En-Nadhir Zighem;, Abdenour Hadid2026 · 1 citation
23. Assessing Web Search Credibility and Response Groundedness in Chat AssistantsConference of the European Chapter of the Association for Computational Linguistics (EACL)Ivan Vykopal, Matúš Pikuliak, Simon Ostermann, et al.2026
24. Detecting Hallucinations in Authentic LLM–Human InteractionsLanguage Resources and Evaluation Conference (LREC)Yujie Ren, Niklas Gruhlke, Anne Lauscher2026
25. Distill and Align Decomposition for Enhanced Claim VerificationFindings of the Association for Computational LinguisticsJabez Magomere, Elena Kochkina, Samuel Mensah, et al.2026
26. PRISM: Probing Reasoning, Instruction, and Source Memory in LLM HallucinationsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuhe Wu, Guangyu Wang, Yuran Chen, et al.2026
27. ReFACT: A Benchmark for Scientific Confabulation Detection with Positional Error AnnotationsConference of the European Chapter of the Association for Computational Linguistics (EACL)Yindong Wang, Martin Preiß, Margarita Bugueño, et al.2026
28. Survey on Hallucinations in Large Language Models (大语言模型的幻觉问题研究综述)Journal of SoftwareZeyuan Liu (刘泽垣), Pengjiang Wang (王鹏江), Xiaobin Song (宋晓斌), et al.2024

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