Quantitative Analysis of Technical Debt and Pattern Violation in Large Language Model Architectures

This article likely presents a quantitative analysis of technical debt and pattern violations within the architecture of Large Language Models (LLMs). The focus is on measuring and understanding these issues, which can impact maintainability, scalability, and performance. The source being ArXiv suggests a peer-reviewed or pre-print research paper.