GitHub

[CVPR-2024] LEAD: Learning Decomposition for Source-free Universal Domain Adaptation

The main challenge for Source-free Universal Domain Adaptation (SF-UniDA) is determining whether covariate-shifted samples belong to target-private unknown categories. Existing methods tackle this ...
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, ...