activity
20152022
most citedMaking Neural Programming Architectures Generalize via Recursion

95 citations · 251 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CL2022

Privacy-Preserving Domain Adaptation of Semantic Parsers

Fatemehsadat Mireshghallah, Yu Su, Tatsunori Hashimoto +2

Task-oriented dialogue systems often assist users with personal or confidential matters. For this reason, the developers of such a system are generally prohibited from observing ac…

cs.CL2022★ 1 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.CL2021

Few-Shot Semantic Parsing with Language Models Trained On Code

Richard Shin, Benjamin Van Durme

Large language models can perform semantic parsing with little training data, when prompted with in-context examples. It has been shown that this can be improved by formulating the…

cs.CL2021★ 2 cited

Constrained Language Models Yield Few-Shot Semantic Parsers

Richard Shin, Christopher H. Lin, Sam Thomson +7

We explore the use of large pretrained language models as few-shot semantic parsers. The goal in semantic parsing is to generate a structured meaning representation given a natural…

cs.LG2019★ 1 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.LG2019★ 16 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.CL2019★ 73 cited

RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

Bailin Wang, Richard Shin, Xiaodong Liu +2

When translating natural language questions into SQL queries to answer questions from a database, contemporary semantic parsing models struggle to generalize to unseen database sch…

cs.LG2019★ 9 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★ 51 cited

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…

cs.LG2017★ 95 cited

Making Neural Programming Architectures Generalize via Recursion

Jonathon Cai, Richard Shin, Dawn Song

Empirically, neural networks that attempt to learn programs from data have exhibited poor generalizability. Moreover, it has traditionally been difficult to reason about the behavi…

cs.CR2017★ 3 cited

PIANO: Proximity-based User Authentication on Voice-Powered Internet-of-Things Devices

Neil Zhenqiang Gong, Altay Ozen, Yu Wu +5

Voice is envisioned to be a popular way for humans to interact with Internet-of-Things (IoT) devices. We propose a proximity-based user authentication method (called PIANO) for acc…

cs.CR2015

Exploring Privacy Preservation in Outsourced K-Nearest Neighbors with Multiple Data Owners

Frank Li, Richard Shin, Vern Paxson

The k-nearest neighbors (k-NN) algorithm is a popular and effective classification algorithm. Due to its large storage and computational requirements, it is suitable for cloud outs…