A Survey on Language Models for Code.
CoRR(2023)
摘要
In this work we systematically review the recent advancements in code
processing with language models, covering 50+ models, 30+ evaluation tasks, and
500 related works. We break down code processing models into general language
models represented by the GPT family and specialized models that are
specifically pretrained on code, often with tailored objectives. We discuss the
relations and differences between these models, and highlight the historical
transition of code modeling from statistical models and RNNs to pretrained
Transformers and LLMs, which is exactly the same course that had been taken by
NLP. We also discuss code-specific features such as AST, CFG, and unit tests,
along with their application in training code language models, and identify key
challenges and potential future directions in this domain. We keep the survey
open and updated on github repository at
https://github.com/codefuse-ai/Awesome-Code-LLM.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要