Systems and methods for a bifurcated model architecture for generating concise, natural language summaries of blocks of code

Abstract

Systems and methods are described for generating code summaries using bifurcated model architectures. The bifurcated model architecture may comprise a first model that generates code summaries based on native code script, and the second model may compare, de-duplicate, and/or categorize the code summaries into clusters that perform the same or similar functions. That is, the systems and methods may comprise a first model (e.g., a large language model) to predict new content (e.g., a code summary for a given native script code). The outputs of the first model are then inputted into a natural language processing (NLP) model to compare the code summaries. For example, the first model of the bifurcated architecture performs a crucial pre-processing step that prevents the NLP model from generating cluster descriptions that are specific to semantic structures, programming languages, and/or code formatting.