Source record

Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2607.26722.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Research paper proposing DREvo, a harness self-evolution method for LLM agents that combines function-level evidence anchoring, state-dependent evidence recalibration, and role-conditioned search intent distillation. Claims smoother evolution trajectories and average accuracy gains of 16.2% and 14.2% over baselines on five benchmarks.

A concrete method for improving agent harnesses under tight iteration budgets, with measured gains across five benchmarks — useful for builders tuning agent systems.

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