🧑‍🔬 Who cites Dejiao Zhang

198 citations of their works from 180 papers of our library (of the 141,840 whose bibliographies we read) · 17 with a page here, the most cited first · ← Dejiao Zhang

Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,957 citations
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 · 3,222 citations
CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive SummarizationConference on Empirical Methods in Natural Language Processing (EMNLP)Shuyang Cao, Lu Wang2021 · 258 citations
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
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive SummarizationAnnual Meeting of the Association for Computational Linguistics (ACL)Meng Cao, Yue Dong, Jackie Cheung2022 · 167 citations
1. ChatGPT as a Factual Inconsistency Evaluator for Text SummarizationarXiv:2303.15621Zheheng Luo, Qianqian Xie, Sophia Ananiadou2023 · 160 citations
   Improving Factual Consistency of Abstractive Summarization via Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Feng Nan, Cicero Nogueira dos Santos, Henghui Zhu, et al.2021 · 128 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
   JointCL: A Joint Contrastive Learning Framework for Zero-Shot Stance DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Bin Liang, Qinglin Zhu, Xiang Li, et al.2022 · 119 citations
   Large Language Models Enable Few-Shot ClusteringTransactions of the Association for Computational Linguistics (TACL)Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, et al.2024 · 109 citations
   FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive SummarizationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)David Wan, Mohit Bansal2022 · 101 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
   Evaluating Large Language Models for Health-related Queries with PresuppositionsFindings of the Association for Computational LinguisticsNavreet Kaur, Monojit Choudhury, Danish Pruthi2024 · 15 citations
   GUMsley: Evaluating Entity Salience in Summarization for 12 English GenresConference of the European Chapter of the Association for Computational Linguistics (EACL)Jessica Lin, Amir Zeldes2024 · 8 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

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