Behavior Foundation Models (BFMs) give humanoids a promptable policy over a latent behavior space, enabling one single vector to represent a motion to imitate, a pose to reach, or a reward to maximize. Forward-Backward representations successfully produce such spaces, but at the cost of hundreds of GPU-hours for a sing...
Tan-Dzung Do, Tuan Dat Phuong, Nico Bohlinger et al.· 0 citations
Whole-body compliant control is essential for deploying heavy humanoids under high payload in human-centric environments. Most prior force-aware learning-based pipelines focus on end-effector resistance, per-link upper-body springs, or end-effector stiffness modulation, leaving arbitrary-site perturbations on heavy pla...
Tan-Dzung Do, Cuc T.Trinh, Tuan Dat Phuong et al.· 1 citation
Low-bit vision-language-action inference must reduce observation-to-action latency while preserving robot behavior. We present FoldQuantVLA, a post-training quantization framework that carries a consistent activation representation through calibration, weight rounding, and native integer execution. It combines channel...
Hung T. Ho, Khanh-Binh Nguyen, Quan Nguyen et al.· 0 citations
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