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DreamX: Video Diffusion Model is a Universal Latent Action Learner

Paper recorded by Signals 4 on 2026-11-03 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-11-03 on arXiv · recorded by Signals 4 on 2026-11-04

Category: cs.AI · 人工智能 · first seen 2026-11-04

Abstract

Learning a universal action representation from video requires modeling dynamics that are consistent across different executions of the same action yet invariant to changes in embodiment and appearance. Existing latent action models infer actions from visual transitions, but their representations often entangle the underlying action with irrelevant visual variations, limiting transfer across embod

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#1 most recent of 920 cs.AI papers we have recorded · ↓ older: From Autonomous Agents to Cognitive Symbionts: Toward AI-Augmented Hum
Cite this page: DreamX: Video Diffusion Model is a Universal Latent Action Learner: the #1 most recent of 920 cs.AI papers we have recorded (as of 2026-11-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/dreamx-video-diffusion-model-is-a-universal-latent-action-learner.html
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