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#artificial intelligence Preprint Sep 2026

LongEmo: Towards Emotion Understanding and Reasoning in Long Videos

While recent Multimodal Large Language Models (MLLMs) have shown promise in affective computing, their reasoning capabilities are largely confined to short video clips with limited interactions. However, real-world emotions are not merely isolated instantaneous reactions but dynamic and cumulative processes deeply shap...

Shuo Zhang, Yifan Zhou, Han-Yu Wang et al. · 0 citations
#machine learning Preprint Sep 2026

GleanVID: Complementary Token Selection for Efficient Video Large Language Models

Video Large Language Models (VideoLLMs) have achieved strong video understanding capabilities but incur substantial inference overhead due to the large number of visual tokens. Existing VideoLLM token compression methods largely rely on selection-independent scoring, overlooking cross-frame complementarity and conseque...

Shuo Yang, Chang-Bai Li, Rui Tang et al. · 0 citations

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