SKT：通过验证合成数据实现规模化技能使用训练

AI 摘要

SKT 是一种基于验证的合成数据生成流水线，用于提升语言模型代理的技能使用能力。它从 2000 个公共技能中生成 4000 个任务包和 27164 条验证轨迹，并通过监督微调显著提升模型性能。研究还构建了 SkillEval 基准，验证了该方法在不同模型和代理框架中的有效性。

正文节选

SKT: Skill-Use Training at Scale via Verified Synthetic Data Generation Abstract Agent skills have become an important mechanism for equipping language-model agents with reusable procedural knowledge. However, providing skills alone does not guarantee that current models can effectively identify, apply, and coordinate them. To improve skill-use capabilities, we introduce SKT, a verified data synthesis pipeline that constructs skill-grounded tasks and executable trajectories from large collection

发布时间：—

抓取时间：2026-08-04 12:08

来源机构：Hugging Face