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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

ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents

Fanqing Meng, Lingxiao Du, Zijian Wu +46

Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surrounding environment may change in…

cs.CV2026

Omni-MMSI: Toward Identity-attributed Social Interaction Understanding

Xinpeng Li, Bolin Lai, Hardy Chen +5

We introduce Omni-MMSI, a new task that requires comprehensive social interaction understanding from raw audio, vision, and speech input. The task involves perceiving identity-attr…

cs.CV2026

Kestrel: Grounding Self-Refinement for LVLM Hallucination Mitigation

Jiawei Mao, Hardy Chen, Haoqin Tu +7

Large vision-language models (LVLMs) have become increasingly strong but remain prone to hallucinations in multimodal tasks, which significantly narrows their deployment. As traini…

cs.CV2025

VQ-VA World: Towards High-Quality Visual Question-Visual Answering

Chenhui Gou, Zilong Chen, Zeyu Wang +10

This paper studies Visual Question-Visual Answering (VQ-VA): generating an image, rather than text, in response to a visual question -- an ability that has recently emerged in prop…

cs.CV2025

When Visualizing is the First Step to Reasoning: MIRA, a Benchmark for Visual Chain-of-Thought

Yiyang Zhou, Haoqin Tu, Zijun Wang +11

We propose MIRA, a new benchmark designed to evaluate models in scenarios where generating intermediate visual images is essential for successful reasoning. Unlike traditional CoT…