🔗 Who cites «A Survey on Hallucination in Large Vision-Language Models»

91 papers of our library cite it (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · ← back to «A Survey on Hallucination in Large Vision-Language Models»

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 · 3,231 citations
2. Large Language Models for Generative Information Extraction: A SurveyFrontiers of Computer ScienceDerong Xu, Wei Chen, Wenjun Peng, et al.2023 · 406 citations
3. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
4. Hallucination of Multimodal Large Language Models: A SurveyarXiv:2404.18930Zechen Bai, Pichao Wang, Tianjun Xiao, et al.2024 · 120 citations
5. Cracking the Code of Hallucination in LVLMs with Vision-aware Head DivergenceAnnual Meeting of the Association for Computational Linguistics (ACL)Jinghan He, Kuan Zhu, Haiyun Guo, et al.2025 · 21 citations
6. MMSearch-R1: Incentivizing LMMs to SearchAnnual Meeting of the Association for Computational Linguistics (ACL)Jinming Wu, Zihao Deng, Wei Li, et al.2026 · 16 citations
7. Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?Findings of the Association for Computational LinguisticsZhiting Mei, Christina Zhang, Tenny Yin, et al.2026 · 14 citations
8. Activation Steering Decoding: Mitigating Hallucination in Large Vision-Language Models through Bidirectional Hidden State InterventionAnnual Meeting of the Association for Computational Linguistics (ACL)Jingran Su, Jingfan Chen, Hongxin Li, et al.2025 · 12 citations
9. Insight Over Sight: Exploring the Vision-Knowledge Conflicts in Multimodal LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyuan Liu, Wenxuan Wang, Youliang Yuan, et al.2025 · 6 citations
10. INFACT: A Diagnostic Benchmark for Induced Faithfulness and Factuality Hallucinations in Video-LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yangjunqi, Yuecong Min, Jie Zhang, et al.2026 · 5 citations
11. Revealing and Enhancing Core Visual Regions: Harnessing Internal Attention Dynamics for Hallucination Mitigation in LVLMsFindings of the Association for Computational LinguisticsGuangtao Lyu, Qi Liu, Chenghao Xu, et al.2026 · 5 citations
12. Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Shunqi Mao, Chaoyi Zhang, Weidong Cai2026 · 4 citations
13. CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive DecodingFindings of the Association for Computational LinguisticsXi Zhang, Zaiqiao Meng, Jake Lever, et al.2026 · 2 citations
14. Once Correct, Still Wrong: Counterfactual Hallucination in Multilingual Vision-Language ModelsFindings of the Association for Computational LinguisticsBasel Mousi, Fahim Dalvi, Shammur Absar Chowdhury, et al.2026 · 2 citations
15. Dialectic-Med: Mitigating Diagnostic Hallucinations via Counterfactual Adversarial Multi-Agent DebateFindings of the Association for Computational LinguisticsZhixiang Lu, Jionglong Su2026 · 1 citation
16. CEBC: Conformal Evidence-Bounded Control for Low-Hallucination Vision–Language GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Ashish Mishra, Tarun Kumar, Arpit Shah, et al.2026
17. How Do Inpainting Artifacts Propagate to Language?Annual Meeting of the Association for Computational Linguistics (ACL)Pratham Yashwante, Davit Abrahamyan, Shresth Grover, et al.2026
18. Journey Before Destination: On the importance of Visual Faithfulness in Slow ThinkingConference of the European Chapter of the Association for Computational Linguistics (EACL)Rheeya Uppaal, Phu Mon Htut, Min Bai, et al.2026
19. Latent Attention Denoising: A Training-Free Energy-Based Framework for Mitigating Hallucinations in Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiwen Luo, Siyu Jiang, Weilong Jiang, et al.2026
20. MEUR: A Benchmark for Evaluating Vision-Language Models on Multimodal Event Understanding and ReasoningLanguage Resources and Evaluation Conference (LREC)Zimu Wang, Yuqi Wang, Tong Chen, et al.2026
21. Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual EnhancementAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenxin Qin, Qiang Li, Qingzhuo Wang, et al.2026
22. Mitigating Hallucinations in Large Vision-Language Models without Performance DegradationAnnual Meeting of the Association for Computational Linguistics (ACL)Xingyu Zhu, Junfeng Fang, Shuo Wang, et al.2026
23. Tricking Open-World Object Recognition Models: Uncertainty in Out-of-Distribution DetectionWorkshop on Towards Knowledgeable Foundation ModelsWout Teillers, Matias Valdenegro-Toro2026
24. VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-EvaluationFindings of the Association for Computational LinguisticsSeongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.2026

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

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/liu-2024-survey-hallucination-large-vision-language/cited-by/