Unravelling the Mechanisms of Manipulating Numbers in Language Models
NeutralArtificial Intelligence
Recent research has revealed that large language models (LLMs) tend to generate similar and accurate representations for numbers, despite their known tendency to produce errors with numeric data. This study aims to clarify this contradiction by investigating how these models handle numbers and assessing the limits of their accuracy. Understanding these mechanisms is crucial as it can enhance the reliability of LLMs in processing numerical information, which is vital for various applications.
— Curated by the World Pulse Now AI Editorial System




