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Rolling-WAM: World Action Models with Rolling Imagination

Paper recorded by Signals 4 on 2026-09-24 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-24 on arXiv · recorded by Signals 4 on 2026-09-25

Category: cs.AI · 人工智能 · first seen 2026-09-25

Abstract

World Action Models (WAMs) couple action generation with future visual prediction for robotic manipulation. However, completing the joint video-action denoising process at each replanning cycle incurs substantial latency, delaying action updates and limiting closed-loop responsiveness. We present Rolling-WAM, a formulation that distributes joint denoising across successive replanning cycles. Our m

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#4 most recent of 400 cs.AI papers we have recorded · ↑ newer: RAPID: Robot Agentic Programming from Demonstrations · ↓ older: Coding Agents for Generalized Task and Motion Planning Problems
Cite this page: Rolling-WAM: World Action Models with Rolling Imagination: the #4 most recent of 400 cs.AI papers we have recorded (as of 2026-09-24). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/rolling-wam-world-action-models-with-rolling-imagination.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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