Paper recorded by Signals 4 on 2026-10-23 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-23 on arXiv · recorded by Signals 4 on 2026-10-26
Category: cs.LG · 机器学习 · first seen 2026-10-26
Vision-language-action (VLA) policies can adapt to local human intervention, while federated learning can combine distributed robot experience without pooling raw records. We examine their prospective intersection: sharing adaptations derived from diverse human corrections across tasks, environments, people, and robot embodiments. Corrections differ in modality, safety semantics(urgency, behaviora