behavior-imbalance

This paper identifies a failure mode in multi-teacher on-policy distillation for agentic language models where the student becomes over-reliant on tool-calling, and proposes Soft Clamp, a per-token divergence calibration method that reduces over-calling without sacrificing accuracy.