Rethinking Verification in Agent Harnesses
The paper studies verification in agent harnesses across four lifecycle layers (initial instructions, mid-turn reminders, completion gates, independent review), comparing 17 designs across seven frontier coding models on Terminal-Bench and SWE-bench Verified, plus expert evaluation on VisualBench. Independent critic review gave the most favorable accuracy-cost tradeoff, while additional review rounds or critics added up to 3.5 points on average TB accuracy.
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- Primary sourceHugging Face Daily Papers
- Discovery linkHugging Face
- Linked in sourceView arXiv page
- Linked in sourceView PDF
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The paper studies verification in agent harnesses across four lifecycle layers (initial instructions, mid-turn reminders, completion gates, independent review), comparing 17 designs across seven frontier coding models on Terminal-Bench and SWE-bench Verified, plus expert evaluation on VisualBench. Independent critic review gave the most favorable accuracy-cost tradeoff, while additional review rounds or critics added up to 3.5 points on average TB accuracy.
Key findings from the stored brief
- Independent critic review improved average accuracy by 5.9-9.5 points on Terminal-Bench and 3.9-6.6 on SWE-bench Verified.
- Review costs were 1.13-1.25 times baseline on TB and 1.00-1.04 times on SWE, per the paper.
- On VisualBench, independent review achieved net preferences of 13.2-23.8 points over the baseline.
- Initial instructions and execution-time reminders gave modest, model-dependent gains without substantially increasing output tokens.
Source claims not independently checked; results are reported on specific benchmarks with seven coding models.
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Evidence & sources
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Why this may matter
The results offer empirical guidance for designing verification in agent harnesses and position independent review followed by revision as a practical lever for test-time scaling, relevant to builders choosing between accuracy and cost.
Limits and open questions
Source claims not independently checked; results are reported on specific benchmarks with seven coding models.
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