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  "text": "Self-improving harnesses are one of the most discussed ideas in AI right now.\n\n(bookmark it)\n\nThis work proposes a new harness, RuHarness, that beats the strongest harness-evolution baseline by 4.5 points on held-out tasks with Qwen3.5-35B-A3B, and by 5.3 points with GLM-4.7-Flash.\n\nThe work targets a gap in current methods. They evolve the harness but keep the criteria that guide each edit fixed, so the criteria stop matching the agent's weaknesses after a few rounds.\n\nRuHarness evolves the rubric along with the harness. Each round, it finds behavioral criteria in the trajectories, re-scores them, and directs harness edits at the most relevant unresolved weakness. Criteria that stop firing go dormant and return if the weakness reappears.\n\nIf your harness evolution stops improving after a few rounds, update the critic too.\n\nhttps://t.co/V1cHiIR4Hg\n\nChat with Paper: https://t.co/2ucnAs9f0P",
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