Papers by Mengzhen Wang

1 papers
Fine-Grained Features-based Code Search for Precise Query-Code Matching (2025.coling-main)

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Challenge: Existing methods to locate code snippets from databases represent the semantics of code and query by averaging the features of each token and word.
Approach: They propose a fine-grained code search model that consists of a cross-modal encoder, mapping layer and classification layer to capture fine-granular interactions between code and query.
Outcome: The proposed model significantly outperforms existing methods across multiple programming language datasets.

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