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REM: What to Store, When to Recall, What to Forget in Experience Memory for Coding Agents
Large language model (LLM) agents now autonomously complete long-horizon tasks, such as repository-level coding, through hundreds of think-act steps, yet the experience each run produces is rarely reused on the next. Prior memory systems concentrate on retrieval, finding the most relevant past traje
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