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arXiv AI By Dabin Sheng, Zhe Wu, Jinming Zhao, Junliang Xing, Yuanchun Shi

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

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The paper introduces TIDER, a time‑aware retrieval framework that uses a reinforcement‑learning trained temporal interval locator to identify relevant time windows for evidence retrieval in long‑horizon agent memory. By combining temporally grounded candidates with semantic retrieval and reranking them by proximity to the inferred windows, TIDER mitigates the displacement of target memories caused by temporally mismatched yet semantically similar entries. The lightweight 1.7B locator achieves state‑of‑the‑art accuracy on LifeBench and LoCoMo benchmarks, demonstrating the importance of temporal cues for effective evidence retrieval.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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