Progressive Agent Skill Generation via Reinforcement Learning

Excerpt

arXiv:2608.01678v2 Announce Type: replace-cross Abstract: Recent large language model agents often use external skills as modular procedural units that condition inference and improve complex task solving. Thus, automatically generating high-quality skills from documents or experience has become an important problem. Existing skill generation methods largely rely on heuristics or pipeline-style consolidation, which must be specially designed for different evidence sources. In contrast, learning-