Tag
This paper diagnoses and proposes SoftClamp, a calibration method that reduces tool-call boundary drift in multi-teacher on-policy distillation for agentic language models, decreasing over-calling while maintaining accuracy.
A proposed workflow for AI coding agents that emphasizes brainstorming and boundary enforcement before code editing, seeking community feedback on its utility.