🧑‍🔬 Who cites Yi Gu

107 citations of their works from 107 papers of our library (of the 149,439 whose bibliographies we read) · 35 with a page here, the most cited first · ← Yi Gu

1. A Primer on the Inner Workings of Transformer-based Language ModelsarXiv:2405.00208Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.2024 · 72 citations
2. LLMs Know More Than They Show: On the Intrinsic Representation of LLM HallucinationsarXiv:2410.02707Hadas Orgad, Michael Toker, Zorik Gekhman, et al.2024 · 68 citations
3. SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Zijun Yao, Weijian Qi, Liangming Pan, et al.2025 · 52 citations
4. LLM Internal States Reveal Hallucination Risk Faced With a QueryarXiv:2407.03282Ziwei Ji, Delong Chen, Etsuko Ishii, et al.2024 · 52 citations
5. Hallucination Detection in LLMs Using Spectral Features of Attention MapsConference on Empirical Methods in Natural Language Processing (EMNLP)Jakub Binkowski, Denis Janiak, Albert Sawczyn, et al.2025 · 18 citations
6. Revisiting Jailbreaking for Large Language Models: A Representation Engineering PerspectiveInternational Conference on Computational Linguistics (COLING)Tianlong Li, Zhenghua Wang, Wenhao Liu, et al.2025 · 17 citations
7. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language ModelsarXiv:2503.24377Rui Wang, Hongru Wang, Boyang Xue, et al.2025 · 16 citations
8. ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenliang Zhang, Xinyu Hu, Huixuan Zhang, et al.2025 · 14 citations
9. Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.2025 · 13 citations
10. A Probabilistic Framework for LLM Hallucination Detection via Belief Tree PropagationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bairu Hou, Yang Zhang, Jacob Andreas, et al.2025 · 12 citations
11. Prompt-Guided Internal States for Hallucination Detection of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fujie Zhang, Peiqi Yu, Biao Yi, et al.2025 · 12 citations
12. Too Consistent to Detect: A Study of Self-Consistent Errors in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Hexiang Tan, Fei Sun, Sha Liu, et al.2025 · 12 citations
13. Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data FilteringAnnual Meeting of the Association for Computational Linguistics (ACL)Shuzheng Si, Haozhe Zhao, Gang Chen, et al.2025 · 11 citations
14. Calibrating Verbal Uncertainty as a Linear Feature to Reduce HallucinationsConference on Empirical Methods in Natural Language Processing (EMNLP)Ziwei Ji, Lei Yu, Yeskendir Koishekenov, et al.2025 · 11 citations
15. Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.2025 · 10 citations
16. Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary PerceptionAnnual Meeting of the Association for Computational Linguistics (ACL)Shiyu Ni, Keping Bi, Jiafeng Guo, et al.2025 · 9 citations
17. MUR: Momentum Uncertainty guided Reasoning for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hang Yan, Fangzhi Xu, Rongman Xu, et al.2026 · 8 citations
18. Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias ResultsAnnual Meeting of the Association for Computational Linguistics (ACL)Andrea Santilli, Adam Golinski, Michael Kirchhof, et al.2025 · 6 citations
19. The Unintended Trade-off of AI Alignment: Balancing Hallucination Mitigation and Safety in LLMsFindings of the Association for Computational LinguisticsOmar Mahmoud, Ali Khalil, Thommen George Karimpanal, et al.2026 · 2 citations
20. Beyond Ranking: Fine-Grained Diagnostics and Self-Improvement for MLLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Mingze Xu, Zijing Zhao, Qiming Peng, et al.2026
21. CoDA: Restoring Contextual Dominance via Copy-Encouraged Attention Intervention for Mitigating RAG HallucinationsFindings of the Association for Computational LinguisticsJinWei Shi, Qizhuo Xie, Qianzi Hou, et al.2026
22. Constructing a Dataset for Hallucination Detection in Japanese Summarization with Fine-grained Faithfulness LabelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Hikari Tanaka, Atsushi Keyaki, Mamoru Komachi2026
23. D²-RAG: Dual-Decision Retrieval-Augmented Generation via Multi-Dimensional Uncertainty and Utility-Aware DecodingFindings of the Association for Computational LinguisticsJinshuo Zhang, Xiaoding Zhou, Weiyu Zhang, et al.2026
24. FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMsFindings of the Association for Computational LinguisticsAlbert Sawczyn, Jakub Binkowski, Denis Janiak, et al.2026
25. HalluZig: Hallucination Detection using Zigzag PersistenceConference of the European Chapter of the Association for Computational Linguistics (EACL)Shreyas N. Samaga, Gilberto Gonzalez Arroyo, Tamal K. Dey2026
26. How Retrieved Context Shapes Internal Representations in RAGFindings of the Association for Computational LinguisticsSamuel Yeh, Sharon Li2026
27. LAFaCT: Attribution-based Localization and Focused Sequential Analysis of Fact-Critical Tokens for Hallucination DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Xin Wang, Jiahao Li, Licheng Zhang, et al.2026
28. LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL QueriesFindings of the Association for Computational LinguisticsXuancheng Ren, Shijing Hu, Zhihui Lu, et al.2026
29. Learning Uncertainty from Sequential Internal Dispersion in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.2026
30. Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-JudgmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Mi, Qiang Sheng, Shaofei Wang, et al.2026
31. RFS-Guard: Detecting Reasoning Hallucinations via Cross-Phase Routing Focus in Large Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zihang Liu, Fang Zhouhua, Hui Liu, et al.2026
32. The Digital Dunning-Kruger Effect: Decoupling Hallucinations via Geometric Hidden-state Observation for Semantic TruthfulnessAnnual Meeting of the Association for Computational Linguistics (ACL)Yueheng Mao, Min Yu, Gengwang Li, et al.2026
33. TPA: Next Token Probability Attribution for Detecting Hallucinations in RAGAnnual Meeting of the Association for Computational Linguistics (ACL)Pengqian Lu, Jie Lu, Anjin Liu, et al.2026
34. Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM HallucinationsAnnual Meeting of the Association for Computational Linguistics (ACL)Wen Luo, Guangyue Peng, Wei Li, et al.2026
35. VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-EvaluationFindings of the Association for Computational LinguisticsSeongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.2026

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