2018/02/12 by Illia Polosukhin, Polosukhin, Illia, Alexander Skidanov +1 · 1 citation
Computer Science · Materials Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning and Data Classification #Machine Learning in Materials Science #Natural Language Processing Techniques #Programming Languages (cs.PL) #Software Engineering Research #Topic Modeling #cs.AI #cs.CL #cs.PL
paper · pdf · doi:10.48550/arxiv.1802.04335
9 pages, 3 figures, ICLR workshop
arxiv created 2018/02/12 · openalex publication_date 2018/02/12 · arxiv updated 2018/02/14 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
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 a sequence-to-sequence model with attention baseline.