Methods › Natural Language Processing › Transformers › CodeBERT

CodeBERT

66 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

CodeBERT is a bimodal pre-trained model for programming language (PL) and natural language (NL). CodeBERT learns general-purpose representations that support downstream NL-PL applications such as natural language code search, code documentation generation, etc. CodeBERT is developed with a Transformer-based neural architecture, and is trained with a hybrid objective function that incorporates the pre-training task of replaced token detection, which is to detect plausible alternatives sampled from generators. This enables the utilization of both bimodal data of NL-PL pairs and unimodal data, where the former provides input tokens for model training while the latter helps to learn better generators.

Source: CodeBERT: A Pre-Trained Model for Programming and...

Papers archive 2025-07-28

30 shown of 66, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 80 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Code Search12
Vulnerability Detection10
Clone Detection8
Code Summarization8
Code Generation7
Language Modelling7
Retrieval6
Bug fixing3
Classification3
Code Classification3
Code Completion3
Code Documentation Generation3
Code Translation3
Contrastive Learning3
Data Augmentation3
Language Modeling3
Large Language Model3
Representation Learning3
Transfer Learning3
Decoder2

Usage over time archive 2025-07-28

Papers per year tagged with CodeBERT: 2020 to 2025, peak 18 18 0 2020: 1 paper 2020 2021: 12 papers 2021 2022: 17 papers 2022 2023: 18 papers 2023 2024: 11 papers 2024 2025: 7 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (66 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Transformers

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