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Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models
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2026-02-07 13:50:23
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VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models VideoHallucer Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models Yuxuan Wang 1,2 , Yueqian Wang 2,3 , Dongyan Zhao 2,3 , Cihang Xie 3 , Zilong Zheng 1,2, , 1 Beijing Institute for General Artificial Intelligence, 1 State Key Laboratory of General Artificial Intelligence, 2 Peking University, 3 UC, Santa Cruz arXiv Code Data Introduction Recent advancements in Multimodal Large Language Models (MLLMs) have extended their capabilities to video understanding. Yet, these models are often plagued by "hallucinations", where irrelevant or nonsensical content is generated, deviating from the actual video context. This work introduces VideoHallucer, the first comprehensive benchmark for hallucination detection in large video-language models (LVLMs). VideoHallucer categorizes hallucinations into two ...
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