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MetaExp adds 14.8 points on AutomationBench to an agent model

The researchers report that the result holds when the training data does not include the test subject.

Claimed, not confirmed

Researchers used 4,956 task records from 1,000 task families to fine-tune the Qwen3.5-122B-A10B model. The model got 8.5 more points on SpreadsheetBench and 14.8 more on AutomationBench. The source reports no test by a different group. For a person who makes agents, a model can get new skill from use.

Sources

  1. MetaExp: Learning to Self-Improve through Experience via Verifiable Cross-Task Environment Scalingarxiv.org
AI MATTER · NEWS · AI MATTER · NEWS ·17 OCT2026

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