collaborators

8 papers

cs.RO2026

PhysCodeBench: Benchmarking Physics-Aware Symbolic Simulation of 3D Scenes via Self-Corrective Multi-Agent Refinement

Tianyidan Xie, Peiyu Wang, Yuyi Qian +7

Physics-aware symbolic simulation of 3D scenes is critical for robotics, embodied AI, and scientific computing, requiring models to understand natural language descriptions of phys…

cs.MM2026

CineAGI: Character-Consistent Movie Creation through LLM-Orchestrated Multi-Modal Generation and Cross-Scene Integration

Tianyidan Xie, Zhentao Huang, Mingjie Wang +4

Automated movie creation requires coordinating multiple characters, modalities, and narrative elements across extended sequences -- a challenge that existing end-to-end approaches…

cs.CV2026

PhysLayer: Language-Guided Layered Animation with Depth-Aware Physics

Tianyidan Xie, Zhentao Huang, Mingjie Wang +4

Existing image-to-video generation methods often produce physically implausible motions and lack precise control over object dynamics. While prior approaches have incorporated phys…

cs.CV2025

Skywork-R1V4: Toward Agentic Multimodal Intelligence through Interleaved Thinking with Images and DeepResearch

Yifan Zhang, Liang Hu, Haofeng Sun +12

Despite recent progress in multimodal agentic systems, existing approaches often treat image manipulation and web search as disjoint capabilities, rely heavily on costly reinforcem…

cs.CV2025

Skywork UniPic: Unified Autoregressive Modeling for Visual Understanding and Generation

Peiyu Wang, Yi Peng, Yimeng Gan +12

We introduce Skywork UniPic, a 1.5 billion-parameter autoregressive model that unifies image understanding, text-to-image generation, and image editing within a single architecture…

cs.CV2025

Skywork-VL Reward: An Effective Reward Model for Multimodal Understanding and Reasoning

Xiaokun Wang, Peiyu Wang, Jiangbo Pei +9

We propose Skywork-VL Reward, a multimodal reward model that provides reward signals for both multimodal understanding and reasoning tasks. Our technical approach comprises two key…