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AI CURATED HOT STORY · 11/3/2026

Meta Proposes Routed CL to Boost Agent Performance via Task-Specific Memory Isolation

1 reports archived1 independent sourcesupdated 11/3/2026, 02:05:04
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Meta's new paper introduces Routed CL, an architecture that uses an LLM router to cluster agent memories by problem type instead of maintaining a single shared history. Experiments show this approach improves scores by 15-30% of the maximum possible gain and reduces estimated API costs by 65-72% compared to shared memory baselines.

LATEST/Meta's new paper introduces Routed CL, an architecture that uses an LLM router to cluster agent memories by problem type instead of maintaining a single shared history. Experiments show this approach improves scores by 15-30% of the maximum possible gain and reduces estimated API costs by 65-72% compared to shared memory baselines.

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  1. Rohan Paul (@rohanpaul_ai)T2·78 pts

    Meta Proposes Routed CL to Boost Agent Performance via Task-Specific Memory Isolation

    • Routed CL employs an LLM as a router to decide whether to reuse or create memory clusters before each run, isolating memories by task type.
    • Each cluster utilizes one of five specific memory types (e.g., raw runs or distilled lessons) to prevent interference from unrelated experiences.
    • Testing on 398 mixed problems across 4 models shows Routed CL significantly outperforms shared history baselines while drastically reducing token consumption.