Research1 min read
Calibration of Agent Confidence from Internal Representations
Research investigates whether model internal representations indicate task success in multi-turn agentic systems. New methods, LTD and ARP, provide a zero-overhead reliability monitor for agent confidence across benchmarks and model families.
From arXiv cs.AI