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arXiv — cs.AI preprintsInternational19 October 2026

When to Forget: Risk-Controlled Context Adaptation for Long-Horizon Agents

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arXiv:2610.22897v1 Announce Type: new Abstract: Long-horizon agents learn from failure, but the value of a failure record can change as execution progresses. We study when retaining, compressing, or removing the same history block improves subsequent execution relative to full-history KEEP. We introduce RECAP, a framework that combines matched context interventions, execution-relational prediction, and independent policy certification. Matched environment states and rollout seeds measure success and continuation prompt-cost differences; prefix-only relations between a failure block and the cur
— arXiv — cs.AI preprints

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