IEEE

Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation

Abstract: The advent of large language models (LLMs) has revolutionized the field of code translation, enabling automated translation between programming languages. Despite these advancements, the ...
IEEE

Flexible and Secure Code Deployment in Federated Learning using Large Language Models: Prompt Engineering to Enhance Malicious Code Detection

Abstract: Federated Learning is a machine learning methodology that emphasizes data privacy, involving minimal interaction with each other’s systems, primarily exchanging model parameters. However, ...
GitHub

CGBridge: Bridging Code Graphs and Large Language Models for Better Structure-Aware Code Understanding

CGBridge is a novel framework designed to enhance the code understanding capabilities of Large Language Models (LLMs) by integrating rich structural information from code graphs. Our approach follows ...