Task: Summarization
Input (English): 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.
Output (English): Presents a seq2Tree model to translate a problem statement in natural language to the corresponding functional program in DSL, which has shown an improvement over the seq2seq baseline approach.