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Recursive Video In-Context Learning for Agentic Robot

Paper recorded by Signals 4 on 2026-10-05 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-05 on arXiv · recorded by Signals 4 on 2026-10-06

Category: cs.AI · 人工智能 · first seen 2026-10-06

Abstract

LLM agents that orchestrate frozen vision-language-action (VLA) policies improve across episodes through text memory, which records what the agent did but not how the task is done. A demonstration video shows it, but fits poorly into an agent's context. The full video slows every turn, fixed keyframes lose the contact detail that decides whether a grasp holds, and what the agent needs shifts from

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#445 most recent of 980 cs.AI papers we have recorded · ↑ newer: Learning to Read the Contextual Tokens in Diffusion Transformers · ↓ older: UniSlider: Perceptually Uniform Sliders for Continuous Image Editing
Cite this page: Recursive Video In-Context Learning for Agentic Robot: the #445 most recent of 980 cs.AI papers we have recorded (as of 2026-10-05). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/recursive-video-in-context-learning-for-agentic-robot.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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