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20232026
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cs.CV2026

Thinking Without Images: Internalizing Visual Manipulation with On-Policy Self-Distillation

Yishuo Cai, Jiahui Liu, Yuanxin Liu +9

''Thinking with Images'' has emerged as an effective paradigm for fine-grained visual reasoning: by explicitly zooming into relevant regions and reasoning over crops, models can ac…

cs.CV2026

Innovator-VL: A Multimodal Large Language Model for Scientific Discovery

Zichen Wen, Boxue Yang, Shuang Chen +30

We present Innovator-VL, a scientific multimodal large language model designed to advance understanding and reasoning across diverse scientific domains while maintaining excellent…

cs.CV2025

Conan: Progressive Learning to Reason Like a Detective over Multi-Scale Visual Evidence

Kun Ouyang, Yuanxin Liu, Linli Yao +5

Video reasoning, which requires multi-step deduction across frames, remains a major challenge for multimodal large language models (MLLMs). While reinforcement learning (RL)-based…

cs.CV2025

RICO: Improving Accuracy and Completeness in Image Recaptioning via Visual Reconstruction

Yuchi Wang, Yishuo Cai, Shuhuai Ren +6

Image recaptioning is widely used to generate training datasets with enhanced quality for various multimodal tasks. Existing recaptioning methods typically rely on powerful multimo…

cs.CV2025

TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming Videos

Linli Yao, Yicheng Li, Yuancheng Wei +11

The rapid growth of online video platforms, particularly live streaming services, has created an urgent need for real-time video understanding systems. These systems must process c…

cs.CV2025

Generative Frame Sampler for Long Video Understanding

Linli Yao, Haoning Wu, Kun Ouyang +5

Despite recent advances in Video Large Language Models (VideoLLMs), effectively understanding long-form videos remains a significant challenge. Perceiving lengthy videos containing…