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20242026
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cs.CV2026

VisualNeedle: Benchmarking Active Visual Search in Information-Dense Scenes

Jingru Chen, Yiming Liu, Mingtao Chen +5

Frontier multimodal large language models (MLLMs) have been reported to achieve over 90% accuracy on fine-grained perception benchmarks. However, such scores do not necessarily imp…

cs.CV2026

Self-Consistent Latent Reasoning: Long Latent Sequence Reasoning for Vision-Language Model

Chenfeng Wang, Wei He, Xuhan Zhu +10

In language reasoning, longer chains of thought consistently yield better performance, which naturally suggests that visual latent reasoning may likewise benefit from longer latent…

cs.CV2026

Visually-grounded Humanoid Agents

Hang Ye, Xiaoxuan Ma, Fan Lu +3

Digital human generation has been studied for decades and supports a wide range of real-world applications. However, most existing systems are passively animated, relying on privil…

cs.CV2025

Vision-Centric Activation and Coordination for Multimodal Large Language Models

Yunnan Wang, Fan Lu, Kecheng Zheng +4

Multimodal large language models (MLLMs) integrate image features from visual encoders with LLMs, demonstrating advanced comprehension capabilities. However, mainstream MLLMs are s…

cs.CV2025

Benchmarking Large Vision-Language Models via Directed Scene Graph for Comprehensive Image Captioning

Fan Lu, Wei Wu, Kecheng Zheng +7

Generating detailed captions comprehending text-rich visual content in images has received growing attention for Large Vision-Language Models (LVLMs). However, few studies have dev…

cs.CV2025

Learning Visual Generative Priors without Text

Shuailei Ma, Kecheng Zheng, Ying Wei +7

Although text-to-image (T2I) models have recently thrived as visual generative priors, their reliance on high-quality text-image pairs makes scaling up expensive. We argue that gra…