NAPS: Natural Program Synthesis Dataset

Autor:	Zavershynskyi, Maksym, Skidanov, Alex, Polosukhin, Illia
Rok vydání:	2018
Předmět:	Computer Science - Machine Learning Computer Science - Artificial Intelligence Computer Science - Programming Languages Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We present a program synthesis-oriented dataset consisting of human written problem statements and solutions for these problems. The problem statements were collected via crowdsourcing and the program solutions were extracted from human-written solutions in programming competitions, accompanied by input/output examples. We propose using this dataset for the program synthesis tasks aimed for working with real user-generated data. As a baseline we present few models, with the best model achieving 8.8% accuracy, showcasing both the complexity of the dataset and large room for future research. Comment: 4 pages, 5 tables in 2nd Workshop on Neural Abstract Machines & Program Induction (NAMPI), @ICML 2018
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1807.03168 Zobrazit plný text záznamu View this record from Arxiv