🔗 Who cites «Improving Factual Consistency of Abstractive Summarization via Question Answering»

53 papers of our library cite it (of the 141,840 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Improving Factual Consistency of Abstractive Summarization via Question Answering»

Trusting Your Evidence: Hallucinate Less with Context-aware DecodingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Weijia Shi, Xiaochuang Han, Mike Lewis, et al.2024 · 240 citations
Q²: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Or Honovich, Leshem Choshen, Roee Aharoni, et al.2021 · 195 citations
Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error DetectorsAnnual Meeting of the Association for Computational Linguistics (ACL)Liyan Tang, Tanya Goyal, Alex Fabbri, et al.2023 · 126 citations
Evaluating Attribution in Dialogue Systems: The BEGIN BenchmarkTransactions of the Association for Computational Linguistics (TACL)Nouha Dziri, Hannah Rashkin, Tal Linzen, et al.2022 · 99 citations
Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable SurveyConference of the European Chapter of the Association for Computational Linguistics (EACL)Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.2023 · 87 citations
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

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

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