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RL-Guided Temporal Localization for Dual-Channel Retrieval in Long-Horizon Agent Memory

Paper recorded by Signals 4 on 2026-10-16 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.AI · 人工智能 · first seen 2026-10-19

Abstract

Time-aware retrieval is crucial for long-horizon LLM agents to effectively leverage ever-growing long-term memory. Existing methods focus on lexical or semantic similarity, leading to target memories being crowded out by temporally mismatched yet semantically similar candidates. Even time-aware approaches inject temporal cues only during memory organization or answer generation, overlooking tempor

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#279 most recent of 960 cs.AI papers we have recorded · ↑ newer: From Trajectories to Differentiated Skills: Cognitive Differentiation · ↓ older: Darwin-Claw: Environment-Adaptive Experience Consolidation for Recursi
Cite this page: RL-Guided Temporal Localization for Dual-Channel Retrieval in Long-Horizon Agent Memory: the #279 most recent of 960 cs.AI papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/rl-guided-temporal-localization-for-dual-channel-retrieval-in-long-horizon-agent.html
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