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PredActor: Predictive Action Diffusion for Steerable Onboard Humanoid Control

Paper recorded by Signals 4 on 2026-09-21 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.LG · 机器学习 · first seen 2026-09-22

Abstract

Diffusion models offer flexible motion generation, but translating this flexibility into feedback-responsive humanoid control remains challenging. Hierarchical systems steer motion through references that may exceed a separate tracker's capabilities, leaving recovery and physical execution largely to the tracker. Action-only diffusion generates actions directly but lacks an explicit future-state t

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#8 most recent of 250 cs.LG papers we have recorded · ↑ newer: Learning Prognostic Variables for AI Convective Parameterizations via · ↓ older: G-NAC: Graph Neural Automata Clustering via Emergent Domain Formation
Cite this page: PredActor: Predictive Action Diffusion for Steerable Onboard Humanoid Control: the #8 most recent of 250 cs.LG papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/predactor-predictive-action-diffusion-for-steerable-onboard-humanoid-control.html
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