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cs.CV2026
FrameScout: Scouting Query-Relevant Frames for Long Video Understanding
Haonan Hu, Shuhao Chen, Weisen Jiang +3
Long video understanding requires VideoLLMs to answer queries about videos spanning tens of minutes to hours, but such long videos produce far more visual tokens than current Video…
cs.CV2026
TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models
Haokui Zhang, Congyang Ou, Dawei Yan +5
Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most existing methods rely on heuristic…
cs.CV2024
EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions
Kai Chen, Yunhao Gou, Runhui Huang +28
GPT-4o, an omni-modal model that enables vocal conversations with diverse emotions and tones, marks a milestone for omni-modal foundation models. However, empowering Large Language…