What is recorded here?
Added identifier tagging/recovery and text–code dual generation to T5-style pretraining, then extended the family with modular encoder/decoder use, mixed denoising/contrastive/matching/causal objectives and compute-efficient initialization from pretrained code LLMs.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
CodeT5+ does not require the original identifier-specific features in every variant. Large-model scaling freezes the deep decoder while training encoder/cross-attention components; inherited pretraining cost remains. Benchmark pass rates are not verified software correctness or unrestricted code-generation reliability.
Read the original work
- CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
- CodeT5+: Open Code Large Language Models for Code Understanding and Generation
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Yue Wang; Weishi Wang; Shafiq Joty; Steven C.H. Hoi; Hung Le; Akhilesh Deepak Gotmare; Nghi D.Q. Bui; Junnan Li
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
CodeT5/CodeT5+: identifier-aware code pretraining and modular code models
Added identifier tagging/recovery and text–code dual generation to T5-style pretraining, then extended the family with modular encoder/decoder use, mixed denoising/contrastive/matching/causal objectives and compute-efficient initialization from pretrained code LLMs.
Scientific scope
CodeT5+ does not require the original identifier-specific features in every variant. Large-model scaling freezes the deep decoder while training encoder/cross-attention components; inherited pretraining cost remains. Benchmark pass rates are not verified software correctness or unrestricted code-generation reliability.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Yue Wang; Weishi Wang; Shafiq Joty; Steven C.H. Hoi; Hung Le; Akhilesh Deepak Gotmare; Nghi D.Q. Bui; Junnan Li
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.