CORRECTING GENERATIVE LANGUAGE MODEL HALLUCINATIONS USING SEMANTIC REPLACEMENT

Abstract

A generative language model, such as an LLM, may “hallucinate,” such that it provides an output category that is incorrect or not relevant to its input. One solution is to use semantic replacement after the generative language model finishes outputting the category. A prompt may be provided to a generative language model, the prompt instructing the generative language model to generate output that classifies an input to the generative language model. Output may be received from the generative language model, the output classifying the input into a category. It may be determined that the category is an invalid category. A valid category be obtained based on the invalid category. The invalid category may be substituted with the valid category.

CPC Classifications