Novel Preprocessing Technique for Data Embedding in Engineering Code Generation Using Large Language Model

We present four main contributions to enhance the performance of Large Language Models (LLMs) in generating domain-specific code: (i) utilizing LLM-based data splitting and data renovation techniques to improve the semantic representation of embeddings' space; (ii) introducing the Chain of Density for Renovation Credibility (CoDRC), driven by LLMs, and the Adaptive Text Renovation (ATR) algorithm for assessing data renovation reliability; (iii) developing the Implicit Knowledge Expansion and Contemplation (IKEC) Prompt technique; and (iv) effectively refactoring existing scripts to generate new …

code code generation cs.cl cs.se data domain embedding embeddings engineering language language model language models large language large language model large language models llm llms novel performance renovation representation semantic space