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2024-06-13 09:37:12

This https://arxiv.org/abs/2308.07429 has been replaced.
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Semantic Similarity Loss for Neural Source Code Summarization
This paper presents a procedure for and evaluation of using a semantic similarity metric as a loss function for neural source code summarization. Code summarization is the task of writing natural language descriptions of source code. Neural code summarization refers to automated techniques for generating these descriptions using neural networks. Almost all current approaches involve neural networks as either standalone models or as part of a pretrained large language models e.g., GPT, Codex, LL…