video pretraining

Native Action-Prior Learning from Videos for World Action Modelsarxiv.org

Native Action-Prior Learning (NAVA‑WAM) trains robot action policies directly from observation‑only videos by matching future video flow through a joint attention mechanism, then fine‑tunes with a small set of labeled demos. Experiments show it beats prior methods on both in‑distribution and out‑of‑distribution tasks and transfers to real robots with fewer action labels.