Author

Lian Li

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Preprint Oct 2026

Continuous-Action World Models: Learning Cross-Embodiment Spatiotemporal Dynamics Priors

We introduce Continuous-Action World Models (CoAWM), a framework for learning cross-embodiment spatiotemporal dynamics priors that support robot action generation across embodiments and execution frequencies. At its core is a shared latent function space that captures the spatial and temporal structure of robot actions...

Lian Li, Qing-Wen Liu · 0 citations

#machine learning Preprint May 2026

World Model Control by Trajectory Reachability Metrics

A fixed encoder is studied in a fixed encoder and trajectory reachability metrics (TRM), a small temporal pairwise cost trained from logged trajectories and used to rank predicted endpoints of a candidate action sequence against a goal is introduced.

Lian Li, Shengzhi Wang, Li-Bin Qiu et al. · 2 citations

Preprint Jul 2026

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models

This work introduces Adjacent Set Action Reconstruction (ASAR), a method that identifies an adjacent set using standardized early action prefixes and reconstructs a full action sequence through locally weighted aggregation with a light anchor from the sequence with minimum cost.

Lian Li, Qingwen Liu, Mingqing Liu et al. · 0 citations