awesome_codegeneration
github.com/liangqingyuan/awesome_codegeneration ↗A list of papers and resources dedicated to code generation
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me dataset for text-to-sql generation resources from awesome_codegeneration"
Installation instructions →What's inside
Datasets
- A Pilot Study for Chinese SQL Semantic ParsingDataset for Text-to-SQL generation
- Automated construction of database interfaces: Intergrating statistical and relational learning for semantic parsingDataset for Text-to-SQL generation
- Chase: A Large-Scale and Pragmatic Chinese Dataset for Cross-Database Context-Dependent Text-to-SQLDataset for Text-to-SQL generation
- Competition-Level Code Generation with AlphaCodeDataset for imperative programming language generation
- Constructing an interactive natural language interface for relational databasesDataset for Text-to-SQL generation
- Convolutional Neural Networks over Tree Structures for Programming Language Processing
Techniques
- Associating Natural Language Comment and Source Code EntitiesCode and comment
- Bridging pre-trained models and downstream tasks for source code understandingUnderstanding with pre-trained models
- CodeBERT: A Pre-Trained Model for Programming and Natural LanguagesPretrained models
- CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and GenerationPretrained models
- CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and GenerationPretrained models
- CoditT5: Pretraining for Source Code and Natural Language EditingPretrained models
Showing a sample of 49 resources. View the full list on GitHub →