🔗 Who cites «DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering»

59 papers of our library cite it (of the 141,840 whose bibliographies we read) · 8 with a page here, the most cited first · ← back to «DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering»

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 · 3,222 citations
2. Making Retrieval-Augmented Language Models Robust to Irrelevant ContextarXiv:2310.01558Ori Yoran, Tomer Wolfson, Ori Ram, et al.2023 · 193 citations
3. LawBench: Benchmarking Legal Knowledge of Large Language ModelsarXiv:2309.16289Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.2023 · 186 citations
4. Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 179 citations
5. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 170 citations
6. Context-faithful Prompting for Large Language ModelsFindings of the Association for Computational LinguisticsWenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.2023 · 145 citations
7. IfQA: A Dataset for Open-domain Question Answering under Counterfactual PresuppositionsWenhao Yu, Meng Jiang, Peter Clark, et al.2023 · 26 citations
8. CRiT-QA: Evaluating Multi-hop Reasoning with Counterfactual Chains and Distractor TrapsLanguage Resources and Evaluation Conference (LREC)Jungmin Yun, June Hyoung Kwon, Youngbin Kim2026

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

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