Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills
- Published
- Source
- arXiv
- Paper number
- 719
- Field
- LLMs / NLP
- arXiv ID
- 2607.22529
Key points
- It uses reusable skills as the main carrier so that task diversity and verification reliability are both preserved.
- A proposer, a solver, and a skill controller all evolve together in the reinforcement-learning loop.
- The skill library creates about 20 new skills per iteration, updates existing skills, and drops useless ones.
- With Qwen3-4B, it gains up to 42.9 points on tool use, BFCL, and 12.0 points on logical reasoning, ZebraLogic.
- Dynamic skill evolution is the key, and it adds another 2.6 points in overall accuracy compared with self-learning without skills.
- Even models that start out misaligned show a large turnaround effect.
Paper links
External research summaries. These are not HDATF publications or measured product results.