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cs.CV2026

VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System

Haodong Li, Tianfei Ren, Xiaoxiao Ma +25

Text-to-video models have achieved remarkable visual quality, yet they still struggle to generate physically consistent dynamics because the temporal evolution of a scene must be i…

cs.CV2026

Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent

Zhen Fang, Yu Zeng, Wenxuan Huang +17

We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense spatiotemporal grounding couple…

cs.CV2026

Flow-OPD: On-Policy Distillation for Flow Matching Models

Zhen Fang, Wenxuan Huang, Yu Zeng +8

Existing Flow Matching (FM) text-to-image models suffer from two critical bottlenecks under multi-task alignment: the reward sparsity induced by scalar-valued rewards, and the grad…

cs.CV2026

VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation

Yiming Zhao, Yu Zeng, Wenxuan Huang +11

Large Vision-Language Models (LVLMs) have shown significant progress in video understanding, yet they face substantial challenges in tasks requiring precise spatiotemporal localiza…

cs.CV2026

SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation

Tianfei Ren, Zhipeng Yan, Yiming Zhao +13

While text-to-image models have made strong progress in visual fidelity, faithfully realizing complex visual intents remains challenging because many requirements must be tracked a…

cs.CV2026

Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models

Yu Zeng, Wenxuan Huang, Zhen Fang +14

Multimodal Large Language Models (MLLMs) have advanced VQA and now support Vision-DeepResearch systems that use search engines for complex visual-textual fact-finding. However, eva…