SOURCE-LINKED INTELLIGENCE
SPT: Skills as Pre-Training Data for Agentic Language Models
Agentic (tool-using) language models are mainly trained on tool-call traces and agent trajectories during post-training. These data provide direct behavioral supervision, but producing them requires task environments, execution, and verification, making broad tool and task coverage expensive. Publicly available skills offer another source of training data: they encode reusable tool semantics and workflows but are typically used only as inference-time context. We introduce Skill Pre-Training (SPT), a mid-training method that applies causal language modeling to SkillCorpus, a collection of publi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-27T03:08:31.000Z
First collected: 2026-09-21T09:11:58.312Z. This is not the publication date.