Think Locally, Act Globally: Federated Learning with Local and Global Representations. - Paul Pu Liang; Terrance Liu; Liu Ziyin 001; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2020)

Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study. - Terrance Liu; Paul Pu Liang; Michal Muszynski; Ryo Ishii; David Brent; Randy Auerbach; Nicholas B. Allen; Louis-Philippe Morency (CoRR, 2020)

Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data. - Paul Pu Liang; Terrance Liu; Anna Cai; Michal Muszynski; Ryo Ishii; Nicholas B. Allen; Randy Auerbach; David Brent; Ruslan Salakhutdinov; Louis-Philippe Morency (ACL/IJCNLP (1), 2021)

Leveraging Public Data for Practical Private Query Release. - Terrance Liu; Giuseppe Vietri; Thomas Steinke 002; Jonathan R. Ullman; Zhiwei Steven Wu (ICML, 2021)

Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods. - Terrance Liu; Giuseppe Vietri; Steven Wu 001 (NeurIPS, 2021)

Private Synthetic Data with Hierarchical Structure. - Terrance Liu; Zhiwei Steven Wu (CoRR, 2022)

Confidence-Ranked Reconstruction of Census Microdata from Published Statistics. - Travis Dick; Cynthia Dwork; Michael Kearns; Terrance Liu; Aaron Roth 001; Giuseppe Vietri; Zhiwei Steven Wu (CoRR, 2022)

Generating Private Synthetic Data with Genetic Algorithms. - Terrance Liu; Jingwu Tang; Giuseppe Vietri; Steven Wu 001 (ICML, 2023)

Multi-group Uncertainty Quantification for Long-form Text Generation. - Terrance Liu; Steven Wu 001 (UAI, 2025)

Winning the MIDST Challenge: New Membership Inference Attacks on Diffusion Models for Tabular Data Synthesis. - Xiaoyu Wu; Yifei Pang; Terrance Liu; Zhiwei Steven Wu (CoRR, 2025)

Generate-then-Verify: Reconstructing Data from Limited Published Statistics. - Terrance Liu; Eileen Xiao; Pratiksha Thaker; Adam Smith 006; Zhiwei Steven Wu (CoRR, 2025)

Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies. - Terrance Liu; Shuyi Wang; Daniel Preotiuc-Pietro; Yash Chandarana; Chirag Gupta (CoRR, 2025)

Breaking the Gold Standard: Extracting Forgotten Data under Exact Unlearning in Large Language Models. - Xiaoyu Wu; Yifei Pang; Terrance Liu; Zhiwei Steven Wu (CoRR, 2025)

Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference. - Terrance Liu; Matteo Boglioni; Yiwei Fu; Shengyuan Hu 001; Pratiksha Thaker; Zhiwei Steven Wu (CoRR, 2025)

Optimizing Canaries for Privacy Auditing with Metagradient Descent. - Matteo Boglioni; Terrance Liu; Andrew Ilyas; Zhiwei Steven Wu (CoRR, 2025)