Three Papers on Improving Agent Training Data
Shahules786 · x · 2026-07-14
The author mentions that last week's Paper Club focused on three papers, all addressing the same core question: how to generate post-training data that genuinely enhances agent capabilities. ### The Three Papers - **PlanBench-XL** (University of Illinois): Focuses on tool environments that more closely reflect the real world - **TMax** (Allen AI / University of Washington): Focuses on synthesizing harder tasks and training on them - **Autodata** (Meta): An agent data scientist loop capable of synthesizing data and performing meta-optimization The author notes that these papers have already influenced their team's internal data pipeline design, and they are currently integrating these concepts into a customizable autonomous data pipeline.
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