AI RESEARCH
CodeRefine: A Pipeline for Enhancing LLM-Generated Code Implementations of Research Papers
arXiv CS.AI
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ArXi:2408.13366v2 Announce Type: replace-cross This paper presents CodeRefine, a novel framework for automatically transforming research paper methodologies into functional code using Large Language Models (LLMs). Our multi-step approach first extracts and summarizes key text chunks from papers, analyzes their code relevance, and creates a knowledge graph using a predefined ontology. Code is then generated from this structured representation and enhanced through a proposed retrospective retrieval-augmented generation approach.