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# Tabular Monte Carlo Control

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  1. arXiv

    Agents stop guessing when to ask for help: ARIA picks consultation points and recovers 68% of the gap on SWE-bench at under half the cost

    ARIA turns when to consult a stronger model into a learned sequential decision: across SWE-bench Verified, Terminal-Bench 2.1 and a telecom customer-service benchmark it recovers 44–81% of the executor–advisor success gap at less than half the Advisor-only cost.

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