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cs.CV2026

VisualClaw: A Real-Time, Personalized Agent for the Physical World

Haoqin Tu, Jianwen Chen, Zijun Wang +14

Vision language models are serving as general-purpose interfaces for complex multimodal tasks. However, deployment still faces three gaps: VLMs typically incur high latency and cos…

cs.CV2026

EntropyPrune: Matrix Entropy Guided Visual Token Pruning for Multimodal Large Language Models

Yahong Wang, Juncheng Wu, Zhangkai Ni +6

Multimodal large language models (MLLMs) incur substantial inference cost due to the processing of hundreds of visual tokens per image. Although token pruning has proven effective…

cs.CV2026

MedVLThinker: Simple Baselines for Multimodal Medical Reasoning

Xiaoke Huang, Juncheng Wu, Hui Liu +2

Large Reasoning Models (LRMs) have introduced a new paradigm in AI by enabling models to ``think before responding" via chain-of-thought reasoning. However, the absence of open and…

cs.CV2026

MedFrameQA: A Multi-Image Medical VQA Benchmark for Clinical Reasoning

Suhao Yu, Haojin Wang, Juncheng Wu +9

Real-world clinical practice demands multi-image comparative reasoning, yet current medical benchmarks remain limited to single-frame interpretation. We present MedFrameQA, the fir…

cs.CV2025

MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Yunfei Xie, Ce Zhou, Lang Gao +8

This paper introduces MedTrinity-25M, a comprehensive, large-scale multimodal dataset for medicine, covering over 25 million images across 10 modalities with multigranular annotati…

cs.CV2025

SCING:Towards More Efficient and Robust Person Re-Identification through Selective Cross-modal Prompt Tuning

Yunfei Xie, Yuxuan Cheng, Juncheng Wu +3

Recent advancements in adapting vision-language pre-training models like CLIP for person re-identification (ReID) tasks often rely on complex adapter design or modality-specific tu…