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Status: Unchecked ×Keyword: code intelligence ×Clear all

2 claims from 1 paper

1. Computer Science › Software Engineering Research

   Prompt Tuning in Code Intelligence: An Experimental Evaluation

   Wang, Yang, Gao, Peng, Zhang and Lyu · IEEE Transactions on Software Engineering · 2023

   The paper tests prompt tuning against fine-tuning on CodeBERT and CodeT5 across four code tasks, and reports that prompt tuning does better, especially when task-specific data is scarce.

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   1. UncheckedIn this study, prompt tuning of pre-trained code models scored better than standard fine-tuning on all four code intelligence tasks tested.“Our experimental results show that prompt tuning consistently outperforms fine-tuning in all four tasks.”
   2. UncheckedPrompt tuning may help most when training data is scarce, raising fine-tuning's BLEU scores by over 26% on average for code summarization.“In addition, prompt tuning shows great potential in low-resource scenarios, e.g., improving the BLEU scores of fine-tuning by more than 26% on average for code summarization.”