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DRSR: Learning Set-Level Deletion Risk for Efficient Long-Horizon Agents

arXiv:2609.27276v1 Announce Type: new Abstract: Long-horizon language-model agents accumulate reasoning traces, tool exchanges, and observations whose relevance changes with the current decision. Existing compression strategies often score historical units independently, but the safety of deleting…

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  1. 2026-09-24 04:00 · arXiv cs.AI
    DRSR: Learning Set-Level Deletion Risk for Efficient Long-Horizon Agents

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