CodeHID: Learning an Addressable Hierarchical Code Index for Generative Code Retrieval
This paper proposes CodeHID, a generative code retrieval framework that reformulates the code retrieval task from flat candidate matching to coarse-to-fine semantic address generation and outperforms existing sparse retrieval, pre-trained code models, dense code retrieval, and generative retrieval baselines by a large...