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cs.RO2026

4D-WAM: Infusing Spatiotemporal Awareness into World Action Models through Trajectory Fields

Lishan Yang, Wenxuan Song, Xi Wang +14

Building on recent advances in world models, World Action Models (WAMs) jointly model video prediction and action generation. However, they typically represent videos in 2D pixel s…

cs.RO2026

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models

Haodong Yan, Jiaguan Zhu, Mingyuan Jia +12

Learning structured and control-relevant latent representations remains a key challenge for world models. Recent JEPA-based world models learn action-conditioned predictive latent…

cs.RO2026

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation

Junfeng Li, Junjie He, Zhide Zhong +12

Vision-Language-Action (VLA) models have become a powerful paradigm for robot manipulation, but training a single generalist policy for heterogeneous robot embodiments remains an o…

cs.RO2026

DFM-VLA: Iterative Action Refinement for Robot Manipulation via Discrete Flow Matching

Jiayi Chen, Wenxuan Song, Jiaxin Fang +12

Vision-Language-Action (VLA) models that encode actions using a discrete tokenization scheme have been widely adopted for robotic manipulation, but existing decoding paradigms rema…

cs.RO2020

Learning a Group-Aware Policy for Robot Navigation

Kapil Katyal, Yuxiang Gao, Jared Markowitz +4

Human-aware robot navigation promises a range of applications in which mobile robots bring versatile assistance to people in common human environments. While prior research has mos…