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A Survey on Language Models for Code
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Length:
68 minutes
Released:
Nov 22, 2023
Format:
Podcast episode
Description
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.
2023: Ziyin Zhang, Chaoyu Chen, Bingchang Liu, Cong Liao, Zi Gong, Hang Yu, Jianguo Li, Rui Wang
https://arxiv.org/pdf/2311.07989v2.pdf
2023: Ziyin Zhang, Chaoyu Chen, Bingchang Liu, Cong Liao, Zi Gong, Hang Yu, Jianguo Li, Rui Wang
https://arxiv.org/pdf/2311.07989v2.pdf
Released:
Nov 22, 2023
Format:
Podcast episode
Titles in the series (100)
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