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awesome_codegeneration
A list of papers and resources dedicated to code generation
https://github.com/LIANGQINGYUAN/awesome_codegeneration
- Learning to generate pseudo-code from source code using statistical machine translation
- Latent Predictor Networks for Code Generation
- Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow
- Mapping language to code in programmatic context
- Measuring coding challenge competence with apps
- Evaluating large language models trained on code
- Competition-Level Code Generation with AlphaCode
- Lyra: A Benchmark for Turducken-Style Code Generation
- Evaluation of spoken language systems: The ATIS domain
- Learning to parse database queries using inductive logic programming
- Automated construction of database interfaces: Intergrating statistical and relational learning for semantic parsing
- Constructing an interactive natural language interface for relational databases
- SQLizer: query synthesis from natural language
- Learning a neural semantic parser from user feedback
- Improving Text-to-SQL Evaluation Methodology
- Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
- Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task
- A Pilot Study for Chinese SQL Semantic Parsing
- On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries
- Tableqa: a large-scale chinese text-to-sql dataset for table-aware sql generation
- DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset
- KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers
- Sparc: Cross-domain semantic parsing in context
- CoSQL: A conversational text-to-SQL challenge towards cross-domain natural language interfaces to databases
- Chase: A Large-Scale and Pragmatic Chinese Dataset for Cross-Database Context-Dependent Text-to-SQL
- Towards a Big Data Curated Benchmark of Inter-project Code Clones
- Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree
- Convolutional Neural Networks over Tree Structures for Programming Language Processing
- TreeGen: A Tree-Based Transformer Architecture for Code Generation
- CodeBERT: A Pre-Trained Model for Programming and Natural Languages
- GraphCodeBERT: Pre-training Code Representations with Data Flow
- CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
- CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
- Unified Pre-training for Program Understanding and Generation
- Evaluating large language models trained on code
- PANGU-CODER: Program Synthesis with Function-Level Language Modeling
- CoditT5: Pretraining for Source Code and Natural Language Editing
- IdBench: Evaluating Semantic Representations of Identifier Names in Source Code
- VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
- Unleashing the Power of Compiler Intermediate Representation to Enhance Neural Program Embeddings
- Associating Natural Language Comment and Source Code Entities
- Deep Just-In-Time Inconsistency Detection Between Comments and Source Cod
- Grape: Grammar-Preserving Rule Embedding
- Bridging pre-trained models and downstream tasks for source code understanding
- Natural Attack for Pre-trained Models of Code
- Compressing Pre-trained Models of Code into 3 MB
- Copilot - time, right from your editor.
- Tabnine
- CodeWhisperer - powered coding companion.
- Captain Stack
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