most citedExploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

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cs.CV2025★ 1 cited

Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation

Hongcheng Gao, Jiashu Qu, Jingyi Tang +6

The hallucination of large multimodal models (LMMs), providing responses that appear correct but are actually incorrect, limits their reliability and applicability. This paper aims…

cs.CV2025

Treble Counterfactual VLMs: A Causal Approach to Hallucination

Shawn Li, Jiashu Qu, Yuxiao Zhou +3

Vision-Language Models (VLMs) have advanced multi-modal tasks like image captioning, visual question answering, and reasoning. However, they often generate hallucinated outputs inc…