Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models

Manh Nguyen; Sunil Gupta; Hung Le

AAAI 2026technical0 citations

Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models

Abstract

Large Language Models (LLMs) exhibit strong performance across various natural language processing (NLP) tasks but remain vulnerable to hallucinations, generating factually incorrect or misleading outputs. Uncertainty estimation, often using predictive entropy estimation, is key to addressing this issue. However, existing methods often require multiple samples or extra computation to assess semantic entropy. This paper proposes an efficient, training-free uncertainty estimation method that approximates predictive entropy using the responses

BibTeX

@inproceedings{aaai2026_probabilitiesare,
  title = {Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models},
  author = {Manh Nguyen and Sunil Gupta and Hung Le},
  booktitle = {AAAI 2026},
  year = {2026}
}