Terrance Liu - RankMe

21 papers A* 4A 1Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Breaking the Gold Standard: Extracting Forgotten Data under Exact Unlearning in Large Language Models. CoRR Xiaoyu Wu, Yifei Pang, Terrance Liu, Zhiwei Steven Wu
2025	A*	`conf`	Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies. EMNLP Terrance Liu, Shuyi Wang, Daniel Preotiuc-Pietro, Yash Chandarana, Chirag Gupta
2025	J	`jnl`	Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies. CoRR Terrance Liu, Shuyi Wang, Daniel Preotiuc-Pietro, Yash Chandarana, Chirag Gupta
2025	J	`jnl`	Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference. CoRR Terrance Liu, Matteo Boglioni, Yiwei Fu, Shengyuan Hu, Pratiksha Thaker, Zhiwei Steven Wu
2025	J	`jnl`	Generate-then-Verify: Reconstructing Data from Limited Published Statistics. CoRR Terrance Liu, Eileen Xiao, Pratiksha Thaker, Adam Smith, Zhiwei Steven Wu
2025	A	`conf`	Multi-group Uncertainty Quantification for Long-form Text Generation. UAI Terrance Liu, Steven Wu
2025	J	`jnl`	Optimizing Canaries for Privacy Auditing with Metagradient Descent. CoRR Matteo Boglioni, Terrance Liu, Andrew Ilyas, Zhiwei Steven Wu
2025	J	`jnl`	Winning the MIDST Challenge: New Membership Inference Attacks on Diffusion Models for Tabular Data Synthesis. CoRR Xiaoyu Wu, Yifei Pang, Terrance Liu, Zhiwei Steven Wu
2024	J	`jnl`	Multi-group Uncertainty Quantification for Long-form Text Generation. CoRR Terrance Liu, Zhiwei Steven Wu
2023	A*	`conf`	Generating Private Synthetic Data with Genetic Algorithms. ICML Terrance Liu, Jingwu Tang, Giuseppe Vietri, Steven Wu
2023	J	`jnl`	Generating Private Synthetic Data with Genetic Algorithms. CoRR Terrance Liu, Jingwu Tang, Giuseppe Vietri, Zhiwei Steven Wu
2022	J	`jnl`	Confidence-Ranked Reconstruction of Census Microdata from Published Statistics. CoRR Travis Dick, Cynthia Dwork, Michael Kearns, Terrance Liu, Aaron Roth, Giuseppe Vietri, Zhiwei Steven Wu
2022	J	`jnl`	Private Synthetic Data with Hierarchical Structure. CoRR Terrance Liu, Zhiwei Steven Wu
2021	A*	`conf`	Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods. NeurIPS Terrance Liu, Giuseppe Vietri, Steven Wu
2021	J	`jnl`	Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods. CoRR Terrance Liu, Giuseppe Vietri, Zhiwei Steven Wu
2021	—	`conf`	Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data. ACL/IJCNLP (1) Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nicholas B. Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov, Louis-Philippe Morency
2021	J	`jnl`	Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data. CoRR Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nicholas B. Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov, Louis-Philippe Morency
2021	A*	`conf`	Leveraging Public Data for Practical Private Query Release. ICML Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan R. Ullman, Zhiwei Steven Wu
2021	J	`jnl`	Leveraging Public Data for Practical Private Query Release. CoRR Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan R. Ullman, Zhiwei Steven Wu
2020	J	`jnl`	Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study. CoRR Terrance Liu, Paul Pu Liang, Michal Muszynski, Ryo Ishii, David Brent, Randy Auerbach, Nicholas B. Allen, Louis-Philippe Morency
2020	J	`jnl`	Think Locally, Act Globally: Federated Learning with Local and Global Representations. CoRR Paul Pu Liang, Terrance Liu, Liu Ziyin, Ruslan Salakhutdinov, Louis-Philippe Morency