Enhancing Confidence Expression in Large Language Models Through Learning from Past Experience

arXiv:2404.10315v1 Announce Type: new
Abstract: Large Language Models (LLMs) have exhibited remarkable performance across various downstream tasks, but they may generate inaccurate or false information with a confident tone. One of the possible solutions is to empower the LLM confidence expression capability, in which the confidence expressed can be well-aligned with the true probability of the generated answer being correct. However, leveraging the intrinsic ability of LLMs or the signals from the output logits of answers proves challenging in accurately …

abstract arxiv capability confidence cs.cl experience false generate information language language models large language large language models llm llms performance solutions tasks through type