Yxuan Chen

Code search is essential for code reuse, allowing developers to efficiently locate relevant code snippets. Traditional encoder-based models, however, face challenges with poor generalization and input length limitations. In contrast, decoder-only large language models (LLMs), with their larger size, extensive pre-training, and ability to handle longer inputs, present a promising solution to these issues. However, their effectiveness in code search has not been fully explored.