#artificial intelligence
Jul 2026
A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training
Bounded unfiltered teacher continuations at learner-induced contexts improve over pure behavioral cloning at matched budgets and suggest that a few teacher steps, placed at learner-induced contexts, can be a more cost-efficient supervision allocation than longer or more heavily curated teacher completions.
Junze Ye, Jiayi Cheng, Miao Lu et al.
· arXiv.org · 2 citations