Neural Program Search: Solving Data Processing Tasks from Description and Examples

Illia Polosukhin; Alexander Skidanov

ICLR 2018workshop9 citations

Neural Program Search: Solving Data Processing Tasks from Description and Examples

Abstract

We present a Neural Program Search, an algorithm to generate programs from natural language description and a small number of input / output examples. The algorithm combines methods from Deep Learning and Program Synthesis fields by designing rich domain-specific language (DSL) and defining efficient search algorithm guided by a Seq2Tree model on it. To evaluate the quality of the approach we also present a semi-synthetic dataset of descriptions with test examples and corresponding programs. We show that our algorithm significantly outperforms sequence-to-sequence model with attention baseline.

Deep learningStructured PredictionNatural Language ProcessingNeural Program Synthesis

BibTeX

@misc{
polosukhin2018neural,
title={Neural Program Search: Solving Data Processing Tasks from Description and Examples},
author={Illia Polosukhin and Alexander Skidanov},
year={2018},
url={https://openreview.net/forum?id=B1KJJf-R-},
}