6 place 0

384 New agentic memory framework uses 118K tokens per query. LangMem burns through 3.26M.

VentureBeat
VentureBeat 2 place · 06/26/2026 18:58 EDT

Long-horizon reasoning exposes a core weakness in AI agents: context windows fill up fast, and retrieval pipelines return noise instead of signal.To solve this, researchers at the National University of Singapore developed MRAgent, a framework that abandons the static "retrieve-then-reason" approach. Instead, it uses a mechanism that allows an agent to dynamically develop its memory based on accumulating evidence. This multi-step memory reconstruction is integrated into the reasoning process of the large la

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