most citedSynthetic Datasets for Neural Program Synthesis

16 citations · 27 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20221 cited

Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation

Kevin Yang, Olivia Deng, Charles Chen +3

We introduce a novel setup for low-resource task-oriented semantic parsing which incorporates several constraints that may arise in real-world scenarios: (1) lack of similar datase…

cs.LG20191 cited

Hierarchical Variational Imitation Learning of Control Programs

Roy Fox, Richard Shin, William Paul +5

Autonomous agents can learn by imitating teacher demonstrations of the intended behavior. Hierarchical control policies are ubiquitously useful for such learning, having the potent…

cs.LG201916 cited

Synthetic Datasets for Neural Program Synthesis

Richard Shin, Neel Kant, Kavi Gupta +4

The goal of program synthesis is to automatically generate programs in a particular language from corresponding specifications, e.g. input-output behavior. Many current approaches…

cs.LG20199 cited

Encoding Database Schemas with Relation-Aware Self-Attention for Text-to-SQL Parsers

Richard Shin

When translating natural language questions into SQL queries to answer questions from a database, we would like our methods to generalize to domains and database schemas outside of…

cs.LG2019

Program Synthesis and Semantic Parsing with Learned Code Idioms

Richard Shin, Miltiadis Allamanis, Marc Brockschmidt +1

Program synthesis of general-purpose source code from natural language specifications is challenging due to the need to reason about high-level patterns in the target program and l…