Inference and analysis of formal models of botnet command and control protocols. - Chia Yuan Cho; Domagoj Babic; Eui Chul Richard Shin; Dawn Song (CCS, 2010)

A Systematic Analysis of XSS Sanitization in Web Application Frameworks. - Joel Weinberger; Prateek Saxena; Devdatta Akhawe; Matthew Finifter; Eui Chul Richard Shin; Dawn Song (ESORICS, 2011)

Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN) - Neil Zhenqiang Gong; Ameet Talwalkar; Lester W. Mackey; Ling Huang 001; Eui Chul Richard Shin; Emil Stefanov; Elaine Shi; Dawn Song (CoRR, 2011)

FreeMarket: Shopping for free in Android applications. - Daniel Reynaud; Dawn Xiaodong Song; Thomas R. Magrino; Edward XueJun Wu; Eui Chul Richard Shin (NDSS, 2012)

On the Feasibility of Internet-Scale Author Identification. - Arvind Narayanan; Hristo S. Paskov; Neil Zhenqiang Gong; John Bethencourt; Emil Stefanov; Eui Chul Richard Shin; Dawn Song (IEEE Symposium on Security and Privacy, 2012)

Joint Link Prediction and Attribute Inference Using a Social-Attribute Network. - Neil Zhenqiang Gong; Ameet Talwalkar; Lester W. Mackey; Ling Huang 001; Eui Chul Richard Shin; Emil Stefanov; Elaine Shi; Dawn Song (ACM Trans. Intell. Syst. Technol., 2014)

Exploring Privacy Preservation in Outsourced K-Nearest Neighbors with Multiple Data Owners. - Frank Li 001; Richard Shin; Vern Paxson (CCSW, 2015)

Recognizing Functions in Binaries with Neural Networks. - Eui Chul Richard Shin; Dawn Song; Reza Moazzezi (USENIX Security Symposium, 2015)

ExploreKit: Automatic Feature Generation and Selection. - Gilad Katz; Eui Chul Richard Shin; Dawn Song (ICDM, 2016)

Latent Attention For If-Then Program Synthesis. - Chang Liu 021; Xinyun Chen; Eui Chul Richard Shin; Mingcheng Chen; Dawn Xiaodong Song (NIPS, 2016)

PIANO: Proximity-Based User Authentication on Voice-Powered Internet-of-Things Devices. - Neil Zhenqiang Gong; Altay Ozen; Yu Wu; Xiaoyu Cao; Richard Shin; Dawn Song; Hongxia Jin; Xuan Bao (ICDCS, 2017)

Making Neural Programming Architectures Generalize via Recursion. - Jonathon Cai; Richard Shin; Dawn Song (ICLR, 2017)

Parametrized Hierarchical Procedures for Neural Programming. - Roy Fox; Richard Shin; Sanjay Krishnan; Ken Goldberg; Dawn Song; Ion Stoica (ICLR (Poster), 2018)

Differentiable Neural Network Architecture Search. - Richard Shin; Charles Packer; Dawn Song (ICLR (Workshop), 2018)

Towards Specification-Directed Program Repair. - Richard Shin; Illia Polosukhin; Dawn Song (ICLR (Workshop), 2018)

Improving Neural Program Synthesis with Inferred Execution Traces. - Richard Shin; Illia Polosukhin; Dawn Song (NeurIPS, 2018)

Synthetic Datasets for Neural Program Synthesis. - Richard Shin; Neel Kant; Kavi Gupta; Chris Bender; Brandon Trabucco; Rishabh Singh; Dawn Song (ICLR (Poster), 2019)

Program Synthesis and Semantic Parsing with Learned Code Idioms. - Eui Chul Richard Shin; Miltiadis Allamanis; Marc Brockschmidt; Alex Polozov (NeurIPS, 2019)

Encoding Database Schemas with Relation-Aware Self-Attention for Text-to-SQL Parsers. - Richard Shin (CoRR, 2019)

Hierarchical Variational Imitation Learning of Control Programs. - Roy Fox; Richard Shin; William Paul; Yitian Zou; Dawn Song; Ken Goldberg; Pieter Abbeel; Ion Stoica (CoRR, 2019)

RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers. - Bailin Wang; Richard Shin; Xiaodong Liu 003; Oleksandr Polozov; Matthew Richardson (ACL, 2020)

Abstraction, Generalization, and Embodiment in Neural Program Synthesis. - Richard Shin (2020)

Constrained Language Models Yield Few-Shot Semantic Parsers. - Richard Shin; Christopher H. Lin; Sam Thomson; Charles Chen; Subhro Roy; Emmanouil Antonios Platanios; Adam Pauls; Dan Klein 001; Jason Eisner; Benjamin Van Durme (EMNLP (1), 2021)

Pruning Pretrained Encoders with a Multitask Objective. - Patrick Xia 002; Richard Shin (CoRR, 2021)

Guided K-best Selection for Semantic Parsing Annotation. - Anton Belyy; Chieh-Yang Huang; Jacob Andreas; Emmanouil Antonios Platanios; Sam Thomson; Richard Shin; Subhro Roy; Aleksandr Nisnevich; Charles Chen; Benjamin Van Durme (ACL (demo), 2022)

Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation. - Kevin Yang; Olivia Deng; Charles Chen; Richard Shin; Subhro Roy; Benjamin Van Durme (ACL (Findings), 2022)

Few-Shot Semantic Parsing with Language Models Trained on Code. - Richard Shin; Benjamin Van Durme (NAACL-HLT, 2022)

BenchCLAMP: A Benchmark for Evaluating Language Models on Semantic Parsing. - Subhro Roy; Sam Thomson; Tongfei Chen; Richard Shin; Adam Pauls; Jason Eisner; Benjamin Van Durme (CoRR, 2022)

Privacy-Preserving Domain Adaptation of Semantic Parsers. - Fatemehsadat Mireshghallah; Yu Su 001; Tatsunori Hashimoto; Jason Eisner; Richard Shin (ACL (1), 2023)

BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing. - Subhro Roy; Samuel Thomson; Tongfei Chen; Richard Shin; Adam Pauls; Jason Eisner; Benjamin Van Durme (NeurIPS, 2023)

ToolTalk: Evaluating Tool-Usage in a Conversational Setting. - Nicholas Farn; Richard Shin (CoRR, 2023)

Language-to-Code Translation with a Single Labeled Example. - Kaj Bostrom; Harsh Jhamtani; Hao Fang 002; Sam Thomson; Richard Shin; Patrick Xia 002; Benjamin Van Durme; Jason Eisner; Jacob Andreas (EMNLP, 2024)

Learning to Retrieve Iteratively for In-Context Learning. - Yunmo Chen; Tongfei Chen; Harsh Jhamtani; Patrick Xia 002; Richard Shin; Jason Eisner; Benjamin Van Durme (EMNLP, 2024)

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation. - Xinyu Tang 003; Richard Shin; Huseyin A. Inan; Andre Manoel; Fatemehsadat Mireshghallah; Zinan Lin 001; Sivakanth Gopi; Janardhan Kulkarni; Robert Sim (ICLR, 2024)