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20242026
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cs.CV2026

DensityKV: Density-Guided KV Cache Compression for Long Video Generation

Wenqu Zhao, Xuemin Chi, Xin Zhang +6

Autoregressive video diffusion models enable streaming generation through sliding-window attention, but each generated block is conditioned on previously generated content, causing…

cs.CV2026

Draw2Think: Harnessing Geometry Reasoning through Constraint Engine Interaction

Juncheng Hu, Jiawei Du, Xin Zhang +1

Vision-language models solve geometry problems with rising accuracy, yet their intermediate states remain latent and unverifiable: a relation expressed in textual reasoning or draw…

cs.CV2026

WorldArena: A Unified Benchmark for Evaluating Perception and Functional Utility of Embodied World Models

Yu Shang, Zhuohang Li, Yiding Ma +18

While world models have emerged as a cornerstone of embodied intelligence by enabling agents to reason about environmental dynamics through action-conditioned prediction, their eva…

cs.CV2025

LongScape: Advancing Long-Horizon Embodied World Models with Context-Aware MoE

Yu Shang, Lei Jin, Yiding Ma +4

Video-based world models hold significant potential for generating high-quality embodied manipulation data. However, current video generation methods struggle to achieve stable lon…

cs.CV2025

MoWM: Mixture-of-World-Models for Embodied Planning via Latent-to-Pixel Feature Modulation

Yangcheng Yu, Xin Jin, Yu Shang +4

Embodied action planning is a core challenge in robotics, requiring models to generate precise actions from visual observations and language instructions. While video generation wo…

cs.CV2025

RoboScape: Physics-informed Embodied World Model

Yu Shang, Xin Zhang, Yinzhou Tang +4

World models have become indispensable tools for embodied intelligence, serving as powerful simulators capable of generating realistic robotic videos while addressing critical data…

cs.CV2024

InfinityDrive: Breaking Time Limits in Driving World Models

Xi Guo, Chenjing Ding, Haoxuan Dou +3

Autonomous driving systems struggle with complex scenarios due to limited access to diverse, extensive, and out-of-distribution driving data which are critical for safe navigation.…