Code Generation

105 papers with code • 13 benchmarks • 24 datasets

Code Generation is an important field to predict explicit code or program structure from multimodal data sources such as incomplete code, programs in another programming language, natural language descriptions or execution examples. Code Generation tools can assist the development of automatic programming tools to improve programming productivity.

Source: Deep Learning for Source Code Modeling and Generation

Image source: Measuring Coding Challenge Competence With APPS

Libraries

Use these libraries to find Code Generation models and implementations

Most implemented papers

pix2code: Generating Code from a Graphical User Interface Screenshot

tonybeltramelli/pix2code 22 May 2017

Transforming a graphical user interface screenshot created by a designer into computer code is a typical task conducted by a developer in order to build customized software, websites, and mobile applications.

Evaluating Large Language Models Trained on Code

openai/human-eval 7 Jul 2021

We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities.

A Syntactic Neural Model for General-Purpose Code Generation

pcyin/NL2code ACL 2017

We consider the problem of parsing natural language descriptions into source code written in a general-purpose programming language like Python.

A parallel corpus of Python functions and documentation strings for automated code documentation and code generation

Avmb/code-docstring-corpus IJCNLP 2017

Automated documentation of programming source code and automated code generation from natural language are challenging tasks of both practical and scientific interest.

StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing

pcyin/tranX ACL 2018

Semantic parsing is the task of transducing natural language (NL) utterances into formal meaning representations (MRs), commonly represented as tree structures.

TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation

pcyin/tranX EMNLP 2018

We present TRANX, a transition-based neural semantic parser that maps natural language (NL) utterances into formal meaning representations (MRs).

Content Enhanced BERT-based Text-to-SQL Generation

guotong1988/NL2SQL-BERT 16 Oct 2019

We present a simple methods to leverage the table content for the BERT-based model to solve the text-to-SQL problem.

PaLM: Scaling Language Modeling with Pathways

lucidrains/CoCa-pytorch Google Research 2022

To further our understanding of the impact of scale on few-shot learning, we trained a 540-billion parameter, densely activated, Transformer language model, which we call Pathways Language Model PaLM.

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

microsoft/CodeXGLUE 9 Feb 2021

Benchmark datasets have a significant impact on accelerating research in programming language tasks.

Latent Predictor Networks for Code Generation

deepmind/card2code ACL 2016

Many language generation tasks require the production of text conditioned on both structured and unstructured inputs.