4 papers
R2M-Bench: Evaluating Revisit Memory via Relative Consistency in Interactive Video World Models
Qiwen Gu, Bingjie Gao, Rui Chen +7
High similarity between first-visit and return frames does not necessarily show that a video world model remembered the scene; the intervening rollout may simply have changed very…
DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation
DreamX Team, Rui Chen, Xiangxiang Chu +7
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…
Robo-ValueRL: Reliable Value Estimation for Offline-to-Online Reinforcement Learning
Wenke Xia, Pei Ren, Wenbo Yu +10
Offline-to-online reinforcement learning is promising for generalizable robotic manipulation, yet its full-stack complexity obscures reproduction and diagnosis. Within such systems…
DreamX-World 1.0: A General-Purpose Interactive World Model
DreamX Team, Yancheng Bai, Rui Chen +20
DreamX-World 1.0 is a general-purpose interactive text/image-to-video world model for controllable long-horizon generation. It supports camera navigation, revisits to previously ob…