arXiv AI By Dharshan Kumaran, Arthur Conmy, Federico Barbero, Simon Osindero, Viorica Patraucean, Petar Veli\v{c}kovi\'c

How do LLMs Compute Verbal Confidence

Read the original on arXiv AI →

The Flow has not summarised this story yet — read it at arXiv AI.

arXiv Computation and Language
5d ago

An Analysis of Training-Free Self-Reported Confidence in Language Models

The paper investigates whether language models’ self-reported confidence is meaningful without additional training. By evaluating three training‑free signals—direct verbalization, post‑hoc probability estimates, and agreement across multiple generations—on 100 TriviaQA questions, the authors find that direct verbalization alone achieves high AUROC scores (0.956 and 0.937) for correctness prediction, while agreement-based methods perform noticeably worse. Re‑eliciting confidence for the same answers shows modest score shifts and occasional decision flips, and an audit of biography claims reveals only a small confidence gap between supported and contradicted statements.

By Lukas Meyer, Sofia Rossi, Wei Chen, Thomas Laurent, Yiming Li