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"…
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