Specialized token prediction by a large language model to prompt external intervention

Abstract

Certain aspects provide methods for training and using large language models (LLMs) to predict specialized tokens for prompting human intervention. A method includes obtaining a plurality of training data instances, each including: a training input including a first timestamp and a prompt and/or an intermediate response to the prompt, and a training output including a second timestamp and a response. The method includes annotating the training output of one or more training data instances to include an action token indicating that external intervention is required, wherein the annotation, for each training data instance, is based on: a time difference between the second timestamp and the first timestamp, a number of words included in the response; or at least one trigger word included in the response. The method also includes training the LLM on the training data instances to predict when external intervention is required and accordingly generate the action token.