Abstract: One embodiment of a method for correcting a response generated by a machine learning model includes receiving the response from the machine learning model, where the response is generated by the machine learning model based on a request and a context, determining a plurality of portions of the context that are similar to one or more portions of the response, for each portion of the context included in the plurality of portions of the context, determining whether the portion of the context supports at least one portion of the response, and performing one or more operations to generate a corrected response based on the response and whether each portion of the context included in the plurality of portions of the context supports at least one portion of the response.

Abstract: One embodiment of a method for generating a query includes receiving a user input, selecting, from a plurality of predefined inputs, at least one predefined input based on similarity to the user input, and prompting a trained machine learning model to generate a query based on the user input and at least one predefined query associated with the least one predefined input.

Abstract: Various embodiments set forth systems and techniques for generating domain-specific question answering models. The techniques include receiving a set of input text corresponding to a particular domain; generating, based on the set of input text, a question-answer dataset corresponding to the particular domain, the question-answer dataset comprising a plurality of question-answer pairs; and causing one or more machine learning algorithms to be applied to the question-answer dataset to generate a question answering model associated with the particular domain.