TwinCheck: Evidence-Grounded Negative-Twin Verification for Stateful Tool Agents
A novel verification framework to prevent catastrophic failure in autonomous tool-using agents.
A single locally plausible tool call can derail an otherwise successful agent trajectory. Suspicion alone does not justify intervention, because the replacement itself can introduce the very failure verification is meant to prevent. We introduce TwinCheck, an inference-time verif...
ArXiv CS.AI
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TwinCheck addresses the critical fragility of autonomous agents by providing a rigorous framework to validate tool interactions without introducing secondary errors. This methodology significantly enhances the reliability of complex task execution by mathematically ensuring that proposed alternatives maintain state consistency.
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