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Locating Hidden Failures Makes Long-Horizon Agents More Reliable

Rahman, Salman et al.
arXiv (All) · Papers
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machine-learning
As AI agents take on long, autonomous tasks, we increasingly oversee rather than perform the work, yet we still judge them almost entirely by whether they finally succeed. An outcome cannot reveal where a run went wrong, whether the agent recovered, or the irreversible harm it caused along the way,
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