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P2 Research Paper AgentsData & evaluationEnterprise12:00 updateMicrosoftHugging Face

Microsoft researchers release 'ThinkingBox', a benchmark testing whether agents succeed at the same task 20 times in a row (community post)

What happened

A paper author identifying as a Microsoft employee introduced the agent benchmark 'ThinkingBox-Bench' on Reddit's r/MachineLearning. The benchmark consists of 507 policy-based business workflows across five domains: retail, travel and hospitality, auto insurance, internal IT at a neobank, and consulting IT/HR. It grades not on whether the agent says it finished the task, but on whether the database is actually in the correct state after the task ends. It also compares whether an agent succeeds once versus succeeding all 20 times across 20 repeated runs. According to the author, the paper, code, and dataset are public and also available on Hugging Face OpenEnv, but the original evaluation trajectories have not been released.

Why it matters

When companies use agents for real work, consistency across repeated runs and whether the actual system state changed correctly matter more than a single success rate. As a public evaluation tool that measures this gap, it can serve as a reference when assessing agent adoption. Specific result figures should be checked in the original paper.

Confidence medium · official source pending

Sources

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