collaborators

10 papers

cs.LG2026

Decoupled Physical Modeling and Execution for Physics Reasoning

Ye Zhang, Xuehang Guo, Rui Pan +4

Physics reasoning requires constructing a consistent model of the underlying physical system rather than relying solely on symbolic or formula-based manipulation. Although large la…

cs.CV2026

APT: Atomic Physical Transitions for Causal Video-Language Understanding

Shang Wu, Haoran Lu, Songling Liu +7

Physical events are not understood by their names alone, but by the causal state changes that compose them. A clip-level label such as "bounce" can be correct while hiding the proc…

cs.CV2026

Phys4D: Fine-Grained Physics-Consistent 4D Modeling from Video Diffusion

Haoran Lu, Shang Wu, Songling Liu +10

Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often struggle with fine-grained physical consiste…

cs.CV2026

Towards Sparse Video Understanding and Reasoning

Chenwei Xu, Zhen Ye, Shang Wu +8

We present \revise (\underline{Re}asoning with \underline{Vi}deo \underline{S}parsity), a multi-round agent for video question answering (VQA). Instead of uniformly sampling frames…

cs.CV2026

PhyPrompt: RL-based Prompt Refinement for Physically Plausible Text-to-Video Generation

Shang Wu, Chenwei Xu, Zhuofan Xia +6

State-of-the-art text-to-video (T2V) generators frequently violate physical laws despite high visual quality. We show this stems from insufficient physical constraints in prompts r…

cs.AI2025

AdvEvo-MARL: Shaping Internalized Safety through Adversarial Co-Evolution in Multi-Agent Reinforcement Learning

Zhenyu Pan, Yiting Zhang, Zhuo Liu +13

LLM-based multi-agent systems excel at planning, tool use, and role coordination, but their openness and interaction complexity also expose them to jailbreak, prompt-injection, and…