EA-WM is presented, an Event-Aware Generative World Model that effectively closes the loop between kinematic control and visual perception, and introduces event-aware bidirectional fusion blocks that modulate cross-branch attention, capturing object state changes and interaction dynamics.
Qualitative examples show the PhysBrain 1.5 model's ability to produce end-effector trajectories and predict future scenes through spatially aligned RGB, depth, and robot-mask outputs.
DeepCybo Team, Yue Bin, Hai-Peng Cao et al.· 0 citations
This work introduces physical rank consistency (PRC) to measure how well tokenization preserves local physical distance rankings after reconstruction, and presents ActionPiece, which preserves physical action relationships through joint supervision of representation learning and quantization.
Shijie Lian, Bin Yu, Zhao-Long Shen et al.· 1 citation
It is argued that FBFM offers a new paradigm for fine-grained online correction, bridging open-loop flow generation with closed-loop real-world dynamics.
SIEVE, a structure-aware data selection method for VLA imitation learning that can surpass full-data training while using only 50% of demonstrations and 50% of training steps, suggests that reusable structure, captured through primitives and transitions, is an important signal for efficient VLA imitation learning.
Changti Wu, Bin Yu, Zhaolong Shen et al.· 1 citation
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