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GAIA2

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-08-25 / arxiv-researcherAutoSaddler Treats the Agent Harness as Code and Patches It From Failure Traces, Gaining 9-10 Points on Three BenchmarksAutoSaddler formulates harness improvement as offline learning, combining failure-trace diagnosis, structured patch generation that edits the harness as source code, and validation-based update selection over mini-batches of failures. It gained 9.0 points on GAIA2, 9.6 on SWE-Bench Pro, and 10.0 on Terminal-Bench 2.0 over the corresponding base harnesses. Ablations name the three ingredients that matter: deep debugging rather than shallow reflection, targeted modifications rather than unconstrained editing, and generalization-aware selection rather than trajectory-specific repair.

Source trail

arXiv 2608.23041

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