Author

Jun-Feng Long

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Preprint Oct 2026

SuperMimic: Scaling Humanoid Whole-Body Control with One Differentiable World Model

Tracking large human-motion datasets has become the dominant route to general, expressive humanoid whole-body control, but scaling across many motions is expensive. Current pipelines use model-free reinforcement learning, either merging per-motion specialists through lossy distillation, or brute-forcing a single policy...

Qia-Yuan Liao, Yi-Yang Shao, Jun-Feng Long et al. · 1 citation

#machine learning Preprint Sep 2026

Humanoid Safe Stop via Learned Stoppability Value

Safe-Stop is proposed, a task-agnostic framework that pairs a learned stop policy with learned stoppability estimators, and yields decisions that are robust without sacrificing reactivity.

Jun-Feng Long, Pieter Abbeel, K. Sreenath et al. · 0 citations