Who cites «INFACT: A Diagnostic Benchmark for Induced Faithfulness and Factuality Hallucinations in Video-LLMs»
- Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Qianchi Zhang, Hainan Zhang, Liang Pang, et al.2026 · 27 citations
- Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Wenrui Zhou, Mohamed Hendy, Shu Yang, et al.2026 · 6 citations
- VideoPro: Adaptive Program Reasoning for Long Video UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Chenglin Li, Feng Han, Yikun Wang, et al.2026 · 6 citations
- 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
This page in Markdown → https://md.research.elamur.ai/free/en/papers/yangjunqi-2026-infact-diagnostic-benchmark-induced-faithfulness/cited-by/