9 papers
Linguistic Trajectory Encoding for Efficient Long-Horizon Spatial Memory in Embodied Agents
Tianyidan Xie, Shenyi Wang, Qiang Tang +7
Embodied agents performing long-horizon tasks require a memory representation in which the state transitions of dynamic objects remain queryable in natural language across hours-to…
PhysCodeBench: Benchmarking Physics-Aware Symbolic Simulation of 3D Scenes via Self-Corrective Multi-Agent Refinement
Tianyidan Xie, Peiyu Wang, Yuyi Qian +11
Translating natural-language descriptions of physical phenomena into executable simulation code requires both programming expertise and physical reasoning. Current large language m…
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…
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…
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…
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…
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…
Skywork R1V2: Multimodal Hybrid Reinforcement Learning for Reasoning
Peiyu Wang, Yichen Wei, Yi Peng +10
We present Skywork R1V2, a next-generation multimodal reasoning model and a major leap forward from its predecessor, Skywork R1V. At its core, R1V2 introduces a hybrid reinforcemen…
Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought
Yi Peng, Peiyu Wang, Xiaokun Wang +12
We introduce Skywork R1V, a multimodal reasoning model extending the an R1-series Large language models (LLM) to visual modalities via an efficient multimodal transfer method. Leve…