Avoid Seeking Confidence Scores from an LLM
| Source: HN | Original article
Experts warn against relying on LLMs for confidence scores. LLM confidence scores are often misconstrued.
Recent discussions have highlighted the misconception of relying on Large Language Models (LLMs) for confidence scores. As we previously touched upon in related news, the topic of LLMs and their limitations has been a subject of interest. The notion of asking an LLM for a confidence score is being challenged, with experts arguing that it is not the same as obtaining one from a classifier.
This matters because LLM confidence levels are often misunderstood as a measure of certainty, when in fact, they represent a probability distribution over classes. The distinction is crucial, as it affects how we evaluate and trust the responses generated by LLMs.
Moving forward, it will be essential to watch how the development of LLMs addresses the issue of confidence scores and uncertainty. Researchers are exploring methods to measure and overcome LLM hallucinations, and new approaches, such as the "Yes-score," are being tested to provide a more accurate discriminator between correct and incorrect answers. As the field continues to evolve, a clearer understanding of LLM confidence scores and their limitations will be vital for effective implementation and trust in these models.
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