PROOF-Gen: From Optimized Data to Better Distillation

Researchers have introduced PROOF-Gen, a method designed to improve the distillation of tool-calling capabilities into deployable models by optimizing the teacher-generated data used during supervised fine-tuning. This approach seeks to refine the standard post-training pipelines that developers frequently rerun to maintain the performance of active AI agents.