Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search

This article from ArXiv focuses on enhancing the reliability of uncertainty estimations in Large Language Models (LLMs). It proposes a method leveraging beam search to improve consistency-based uncertainty measures. The core idea likely revolves around generating multiple plausible outputs using beam search and then analyzing the variance or agreement among these outputs to quantify uncertainty. This approach aims to provide more robust and reliable uncertainty estimates compared to existing methods.

• •Focuses on improving uncertainty estimation in LLMs.
• •Utilizes beam search to enhance consistency-based uncertainty measures.
• •Aims to provide more robust and reliable uncertainty estimates.