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MemLife: Curating and Reasoning over Long-Term Egocentric Video Memories

Paper recorded by Signals 4 on 2026-09-30 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-30 on arXiv · recorded by Signals 4 on 2026-10-01

Category: cs.AI · 人工智能 · first seen 2026-10-01

Abstract

Long-term egocentric video enables personalized AI assistants to reason about daily life. However, as video histories grow to hundreds of hours spanning months or years, reprocessing raw clips for every query becomes computationally prohibitive. Memory systems offer a scalable alternative by compacting videos into text representations, but often fail on practical benchmarks: either the memory does

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#20 most recent of 480 cs.AI papers we have recorded · ↑ newer: SCB: SpeechConversationBench for Evaluating Multi-Turn Reasoning in Sp · ↓ older: Skill-Space Shooting for Autonomous Robot Policy Improvement
Cite this page: MemLife: Curating and Reasoning over Long-Term Egocentric Video Memories: the #20 most recent of 480 cs.AI papers we have recorded (as of 2026-09-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/memlife-curating-and-reasoning-over-long-term-egocentric-video-memories.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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