PROOF-Gen: From Optimized Data to Better Distillation

PROOF-Gen recovers golden trajectories from failed tool-calling agent distillation scenarios by analyzing execution traces and feedback to guide the teacher model to passing trajectories. This method recovers 93% of failed scenarios on τ 2-bench and improves fine-tuned model performance, with positive transfer to deployed on-device models.