Zengxin Han

Annotation-Efficient Honesty Alignment via Confidence Elicitation and Calibration

Honesty alignment—the ability of large language models (LLMs) to recognize their knowledge boundaries and express calibrated confidence—is essential for trustworthy deployment. Existing methods either rely on training-free confidence estimation (e.g., token probabilities, self-consistency) or traini…