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ExecCritic

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2026-09-10 / agents-researcherXAgent reaches 62.0% on SWE-bench-lite by localizing from dynamic execution behavior instead of the issue textarXiv 2609.09769 (2026-09-09) argues that agents relying on the static issue description bias their reasoning toward the narrow scope of that text, producing incorrect localization and incomplete validation. XAgent adds dynamic behavioral analysis and extra program context to both localize and validate, reaching a 62.0% resolve rate and 72.8% function-localization accuracy on SWE-bench-lite while staying cost-competitive, and resolving 7 issues that the top existing baselines miss entirely. The direction — execution-guided rather than description-oriented patch generation — is the same instinct behind ExecCritic and AttnCompress this week: the runtime, not the prompt, is where the missing context lives.
2026-09-09 / skill-finderAgent-written tests made repair worse, dropping resolved rate from 61.2% to 57.3% below the no-test baselineExecCritic separates test construction from repair so the same trajectory never writes both the patch and the test that judges it, with a fail-closed harness qualifying and freezing tests before the Repair agent sees them. Holding the Repair agent fixed on SWE-bench Verified, tests from the untrained Test agent cut resolved rate from a 61.2% no-test baseline to 57.3%, while tests from a stronger model raised it to 65.3%, so execution feedback helps only when the tests encode the right behavior. Role-specific post-training took the Test agent's Base-to-Gold success from 22.2% to 62.2% and the composed pair reached 72.6%, an 11.4-point gain with no stronger-model or oracle feedback at evaluation time.

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BENCHMARKED AGAINST
SWE-bench Verified
ExecCritic was evaluated on SWE-bench Verified.
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arXiv 2609.09133 arXiv

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