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Remembering Is Not Enough: Refining Memories and Learning When to Use Them in Multi-Agent Systems
Memory helps LLM-based multi-agent systems reuse experience, but stored advice can be flawed or applied in the wrong situation. Team-level success or failure alone cannot reliably show whether a memory needs correction or should not have been used. We propose DiscernMem, a training-free framework th
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