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Never Look Back: Understanding Persistence in 3D Object Memory from Egocentric Videos

Paper recorded by Signals 4 on 2026-10-07 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-07 on arXiv · recorded by Signals 4 on 2026-10-08

Category: cs.AI · 人工智能 · first seen 2026-10-08

Abstract

As we move through the world and carry out everyday tasks, we encounter objects that may become relevant only later. We are capable of recalling where we left something or what was inside a container, even without knowing we would need it later. Here, we study how an embodied assistant can build a similar memory from egocentric videos, by observing a person's day-to-day activities. We present Ledg

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#381 most recent of 960 cs.AI papers we have recorded · ↑ newer: Distilling Routed 3D Privilege for Spatial Reasoning in Vision-Languag · ↓ older: Decoupling Exploration from Optimization in RLVR
Cite this page: Never Look Back: Understanding Persistence in 3D Object Memory from Egocentric Videos: the #381 most recent of 960 cs.AI papers we have recorded (as of 2026-10-07). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/never-look-back-understanding-persistence-in-3d-object-memory-from-egocentric-vi.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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