Session-based user awareness in large language models

Abstract

Implementations are described herein for using the information about user engagement with large language model (LLM) output as a subsequent input into an LLM, so that the LLM is able to provide, for rendition on one or more output devices, a subsequent output that is tailored to the user. In various implementations, based on one or more input device signals, a user engagement event with an element of a first LLM output generated using a LLM and rendered using one or more output devices may be detected. Additional information about the element of the first LLM output may be captured and used to generate at least part of a subsequent input prompt for the LLM. The subsequent input prompt may be processed using the LLM to generate a subsequent LLM output for rendition on one or more of the output devices.