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Richard Shin
Richard Shin (신의철)
I am currently a Research Scientist at Google DeepMind .
I work on post-training for Gemini 's coding capabilities,
with a particular focus on SWE agents. Earlier at Google, I worked on Jules .
Previously, I was a Principal Researcher at Microsoft Semantic Machines,
where my work leveraged large language models to enable scalable construction of conversational AI systems.
I also worked on other projects relating to privacy, model compression, and crowdsourcing,
in collaboration with interns and teammates.
I received my PhD in Computer Science
at UC Berkeley ,
where I was advised by Dawn Song .
I was a member of the Berkeley AI Research Lab and have also collaborated with the RISE Lab .
I also received my MS and BS degrees at UC Berkeley.
I've worked at
Google AI ,
Intel Labs ,
and Microsoft Research AI .
In the past, I have also done research relating to security applications of
machine learning, software security, and web security.
Papers 2025 Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities Gemini Team, Google
arXiv
2024 Learning to Retrieve Iteratively for In-Context Learning EMNLP 2024
Language-to-Code Translation with a Single Labeled Example EMNLP 2024
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation ICLR 2024
2023 BenchCLAMP: A Benchmark for Evaluating Language Models on Semantic Parsing NeurIPS 2023, Datasets and Benchmarks Track
ToolTalk: Evaluating Tool Usage in a Conversational Setting arXiv
Privacy-Preserving Domain Adaptation of Semantic Parsers ACL 2023
2022 Few-Shot Semantic Parsing with Language Models Trained On Code NAACL 2022 (short paper)
Guided K-best Selection for Semantic Parsing Annotation ACL 2022 (demo track)
Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation Findings of ACL 2022
2021 Pruning Pretrained Encoders with a Multitask Objective ENLSP workshop at NeurIPS 2021
Constrained Language Models Yield Few-Shot Semantic Parsers EMNLP 2021
2020 RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers ACL 2020
2019 Hierarchical Variational Imitation Learning of Control Programs arXiv
Program Synthesis and Semantic Parsing with Learned Code Idioms NeurIPS 2019
Synthetic Datasets for Neural Program Synthesis ICLR 2019
2018 Hierarchical Imitation Learning via Variational Inference of Control Programs Infer2Control workshop at NeurIPS 2018
Improving Neural Program Synthesis with Inferred Execution Traces NeurIPS 2018 (spotlight presentation )
Imitation Learning of Hierarchical Programs via Variational Inference NAMPI workshop at ICML 2018 (extended abstract)
Differentiable Neural Network Architecture Search ICLR 2018 workshop track
Towards Specification-Directed Program Repair ICLR 2018 workshop track
Parametrized Hierarchical Procedures for Neural Programming ICLR 2018
2017 JPEG-resistant Adversarial Images Machine Learning and Computer Security workshop at NeurIPS 2017
PIANO: Proximity-based User Authentication on Voice-Powered Internet-of-Things Devices ICDCS 2017
Making Neural Programming Architectures Generalize via Recursion ICLR 2017 (best paper award )
2016 ExploreKit: Automatic Feature Generation and Selection ICDM 2016 (short paper)
Latent Attention for If-Then Program Synthesis NeurIPS 2016
2015 Exploring Privacy Preservation in Outsourced K-Nearest Neighbors with Multiple Data Owners CCSW at CCS 2015
Recognizing Functions in Binaries with Neural Networks USENIX Security 2015
2014 Joint Link Prediction and Attribute Inference Using a Social-Attribute Network TIST , published 2014-04
2012 On the Feasibility of Internet-Scale Author Identification IEEE S&P 2012
FreeMarket: Shopping for free in Android applications NDSS 2012 (extended abstract)
2011 A Systematic Analysis of XSS Sanitization in Web Application Frameworks ESORICS 2011
2010 Inference and Analysis of Formal Models of Botnet Command and Control Protocols CCS 2010
The Emperor's New APIs: On the (In)Secure Usage of New Client-side Primitives W2SP workshop at IEEE S&P 2010
