Mitigating modality prior-induced hallucinations in multimodal large language models via...

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Explainable and interpretable multimodal large language models: A comprehensive survey

Y Dang, K Huang, J Huo, Y Yan, S Huang, D Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with
large language models (LLMs) and computer vision (CV) systems driving advancements in …
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VidHal: Benchmarking Temporal Hallucinations in Vision LLMs

WY Choong, Y Guo, M Kankanhalli - arxiv preprint arxiv:2411.16771, 2024 - arxiv.org
Vision Large Language Models (VLLMs) are widely acknowledged to be prone to
hallucination. Existing research addressing this problem has primarily been confined to …
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OccludeNet: A Causal Journey into Mixed-View Actor-Centric Video Action Recognition under Occlusions

G Zhou, W Liu, W Huang, X Jia, X Zhong… - arxiv preprint arxiv …, 2024 - arxiv.org
The lack of occlusion data in commonly used action recognition video datasets limits model
robustness and impedes sustained performance improvements. We construct OccludeNet, a …
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