Latent Confidence Alignment for LLM Self-Assessment
Researchers propose Latent Confidence Alignment Error (LCAE), a new framework for evaluating how well large language models assess their own reliability by accounting for item difficulty and model ability. Testing on 20 medical-domain models shows the approach improves self-assessment quality without degrading performance, revealing a correlation between model reliability and computational inference costs.