Systems and methods for modulating outputs of large language models responsive to confidential information

Abstract

Systems and methods for the generation and usage of an identifier determiner model is provided. The identifier determiner model is generated in a sequestered computing node by receiving an untrained foundational model and a data set. The data set is bifurcated into a raw set and a de-identified set. The untrained foundational model is then tuned using the de-identified set to generate a sanitized model and the raw set to generate a raw model. Queries are presented to the raw model and the sanitized model to generate outputs. The identifier determiner machine learning model is generated by using the outputs to classify information as either sensitive or non-sensitive. The system may then receive a new foundational model. The identifier determiner machine learning model may be applied to outputs of this new foundational model to filter out sensitive information, either through redaction, or preventing them from being asked.

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