8 papers
RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation
Feng Jiang, Yang Chen, Kyle Xu +8
Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of using generated videos as scalable supervision for…
Aligning Progress and Feasibility: A Neuro-Symbolic Dual Memory Framework for Long-Horizon LLM Agents
Bin Wen, Ruoxuan Zhang, Yang Chen +2
Large language models (LLMs) have demonstrated strong potential in long-horizon decision-making tasks, such as embodied manipulation and web interaction. However, agents frequently…
ST-VLA: Enabling 4D-Aware Spatiotemporal Understanding for General Robot Manipulation
You Wu, Zixuan Chen, Cunxu Ou +9
Robotic manipulation in open-world environments requires reasoning across semantics, geometry, and long-horizon action dynamics. Existing hierarchical Vision-Language-Action (VLA)…
Mean-Flow based One-Step Vision-Language-Action
Yang Chen, Xiaoguang Ma, Bin Zhao
Recent advances in FlowMatching-based Vision-Language-Action (VLA) frameworks have demonstrated remarkable advantages in generating high-frequency action chunks, particularly for h…
DeCo: Task Decomposition and Skill Composition for Zero-Shot Generalization in Long-Horizon 3D Manipulation
Zixuan Chen, Junhui Yin, Yangtao Chen +6
Generalizing language-conditioned multi-task imitation learning (IL) models to novel long-horizon 3D manipulation tasks is challenging. To address this, we propose DeCo (Task Decom…
RoboHiMan: A Hierarchical Evaluation Paradigm for Compositional Generalization in Long-Horizon Manipulation
Yangtao Chen, Zixuan Chen, Nga Teng Chan +6
Enabling robots to flexibly schedule and compose learned skills for novel long-horizon manipulation under diverse perturbations remains a core challenge. Early explorations with en…