🔗 Who cites «PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions»

25 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions»

1. Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,974 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. A Survey of Hallucination in Large Foundation ModelsarXiv:2309.05922Vipula Rawte, Amit Sheth, Amitava Das2023 · 226 citations
4. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
5. 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
6. Fine-grained Hallucination Detection and Editing for Language ModelsarXiv:2401.06855Abhika Mishra, Akari Asai, Vidhisha Balachandran, et al.2024 · 100 citations
7. 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
8. Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular DataFindings of the Association for Computational LinguisticsMubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.2023 · 38 citations
9. Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Tobias Schreieder, Tim Schopf, Michael Färber2026 · 1 citation
10. PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language ModelsFindings of the Association for Computational LinguisticsZetian Ouyang, Linlin Wang, Gerard de Melo, et al.2026

15 more papers of our library cite it; they have no page here yet.

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