arXiv cs.CLPaper
On-Policy Self-Training: Data-Free Self-Improvement in Large Language Models
This is legitimate progress on unsupervised post-training. The ability to self-improve using only topic guidance and synthetic reasoning is compelling if reproducible. The claims span multiple domains which is ambitious. For anyone running foundation models, this matters: if self-training at this scale and quality is real, it changes the cost and timeline of continued model improvement. Read the experiments carefully because the generality claim is the whole story.