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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

The paper presents VideoCoCo, a system that generates physically consistent videos by having a coding agent produce executable Blender code that defines the scene and its dynamics,…

cs.CV2026

V2P-Bench: Evaluating Video-Language Understanding with Visual Prompts for Better Human-Model Interaction

Yiming Zhao, Yu Zeng, Yukun Qi +8

Large Vision-Language Models (LVLMs) have made significant strides in the field of video understanding in recent times. Nevertheless, existing video benchmarks predominantly rely o…

cs.CV2026

UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision

Ruiyan Han, Zhen Fang, XinYu Sun +9

While Unified Multimodal Models (UMMs) have achieved remarkable success in cross-modal comprehension, a significant gap persists in their ability to leverage such internal knowledg…

cs.CV2025

DualVLA: Building a Generalizable Embodied Agent via Partial Decoupling of Reasoning and Action

Zhen Fang, Zhuoyang Liu, Jiaming Liu +7

To build a generalizable Vision-Language-Action (VLA) model with strong reasoning ability, a common strategy is to first train a specialist VLA on robot demonstrations to acquire r…

cs.CV2025

VCR-Bench: A Comprehensive Evaluation Framework for Video Chain-of-Thought Reasoning

Yukun Qi, Yiming Zhao, Yu Zeng +7

The advancement of Chain-of-Thought (CoT) reasoning has significantly enhanced the capabilities of large language models (LLMs) and large vision-language models (LVLMs). However, a…

cs.CV2024

ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

Lin Chen, Xilin Wei, Jinsong Li +12

We present the ShareGPT4Video series, aiming to facilitate the video understanding of large video-language models (LVLMs) and the video generation of text-to-video models (T2VMs) v…