Author

Rui Chen

AMAP, Alibaba Group

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Preprint Sep 2026

The Right Future for Action: Learning Action-Relevant Predictive States in World Action Models

These findings motivate Action-Relevant Predictive States (ARPS), a compact predictive interface between the video and action experts that achieves 99.2% success on LIBERO and transfers to LIBERO-Plus without adaptation, reaching 87.3% and exceeding Fast-WAM by 39.2 percentage points.

Qi-Wen Gu, Ji-Fan Li, Bing-Jie Gao et al. · 5 citations · ⚡1

Preprint Aug 2026

R2M-Bench: Evaluating Revisit Memory via Relative Consistency in Interactive Video World Models

The results of R2M-Bench support same-rollout relative calibration as a practical way to distinguish revisit-specific consistency from generic temporal stability.

Qiwen Gu, Bing-Jie Gao, Rui Chen et al. · 5 citations · ⚡1

Preprint Aug 2026

DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation

We present \textbf{DreamX-Phi 1.0}, an action-conditioned video world model for robotic manipulation that, given an observed frame, a language instruction, and a prescribed action sequence comprising end-effector poses and gripper states, predicts the resulting future observations. Yet realism alone does not guarantee...

Dream Team, Rui Chen, Xiangxiang Chu et al. · 5 citations