--- title: "Who cites ClashEval: Quantifying the — 46 citing papers" description: "46 papers of the Elamur Research library cite «ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence»…" canonical: "https://research.elamur.ai/free/en/papers/wu-2024-clasheval-quantifying-tug-war-between/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wu-2024-clasheval-quantifying-tug-war-between/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [ClashEval: Quantifying the tug-of-war between an…](https://md.research.elamur.ai/free/en/papers/wu-2024-clasheval-quantifying-tug-war-between/) / cited by # Who cites «ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence» 46 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 «ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence»](https://md.research.elamur.ai/free/en/papers/wu-2024-clasheval-quantifying-tug-war-between/) 1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations* 2. **[Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA](https://md.research.elamur.ai/free/en/papers/wang-2024-leave-no-document-behind-benchmarking/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minzheng Wang, Longze Chen, Fu Cheng, et al.*2024 · 72 citations* 3. **[A Reality Check on Context Utilisation for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/hagstrom-2025-reality-check-context-utilisation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lovisa Hagström, Sara Vera Marjanovic, Haeun Yu, et al.*2025 · 13 citations* 4. **[Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning](https://md.research.elamur.ai/free/en/papers/xu-2025-parenting-optimizing-knowledge-selection-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongxin Xu, Ruizhe Zhang, Xinke Jiang, et al.*2025 · 9 citations* 5. **[Insight Over Sight: Exploring the Vision-Knowledge Conflicts in Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-insight-over-sight-exploring-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Liu, Wenxuan Wang, Youliang Yuan, et al.*2025 · 6 citations* 6. **[Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-context-fidelity-boosting-enhancing-faithful/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weixu Zhang, Fanghua Ye, Qiang Gao, et al.*2026 · 1 citation* 7. **[Concept rather than Document: Context Compression via AMR-based Conceptual Entropy](https://md.research.elamur.ai/free/en/papers/shi-2026-concept-rather-than-document-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaize Shi, Xueyao Sun, Xiaohui Tao, et al.*2026* 8. **[CRiT-QA: Evaluating Multi-hop Reasoning with Counterfactual Chains and Distractor Traps](https://md.research.elamur.ai/free/en/papers/yun-2026-crit-qa-evaluating-multi-hop/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jungmin Yun, June Hyoung Kwon, Youngbin Kim*2026* 9. **[Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting](https://md.research.elamur.ai/free/en/papers/xia-2026-merlin-s-whisper-enabling-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Heming Xia, Cunxiao Du, Rui Li, et al.*2026* 10. **[Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data](https://md.research.elamur.ai/free/en/papers/yang-2026-quantifying-improving-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shiping Yang, Jie Wu, Wenbiao Ding, et al.*2026* 36 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wu-2024-clasheval-quantifying-tug-war-between/) — ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence