Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. - Jiachen T. Wang; Saeed Mahloujifar; Shouda Wang; Ruoxi Jia 001; Prateek Mittal (NeurIPS, 2022)

Data Banzhaf: A Robust Data Valuation Framework for Machine Learning. - Jiachen T. Wang; Ruoxi Jia 001 (AISTATS, 2023)

Uncovering Adversarial Risks of Test-Time Adaptation. - Tong Wu; Feiran Jia; Xiangyu Qi; Jiachen T. Wang; Vikash Sehwag; Saeed Mahloujifar; Prateek Mittal (ICML, 2023)

A Privacy-Friendly Approach to Data Valuation. - Jiachen T. Wang; Yuqing Zhu 005; Yu-Xiang Wang 003; Ruoxi Jia 001; Prateek Mittal (NeurIPS, 2023)

A Randomized Approach to Tight Privacy Accounting. - Jiachen T. Wang; Saeed Mahloujifar; Tong Wu; Ruoxi Jia 001; Prateek Mittal (NeurIPS, 2023)

ModelPred: A Framework for Predicting Trained Model from Training Data. - Yingyan Zeng; Jiachen T. Wang; Si Chen 008; Hoang Anh Just; Ran Jin; Ruoxi Jia 001 (SaTML, 2023)

Towards A Proactive ML Approach for Detecting Backdoor Poison Samples. - Xiangyu Qi; Tinghao Xie; Jiachen T. Wang; Tong Wu; Saeed Mahloujifar; Prateek Mittal (USENIX Security Symposium, 2023)

A Note on "Towards Efficient Data Valuation Based on the Shapley Value". - Jiachen T. Wang; Ruoxi Jia 001 (CoRR, 2023)

A Note on "Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms". - Jiachen T. Wang; Ruoxi Jia 001 (CoRR, 2023)

A Randomized Approach for Tight Privacy Accounting. - Jiachen T. Wang; Saeed Mahloujifar; Tong Wu; Ruoxi Jia 001; Prateek Mittal (CoRR, 2023)

LAVA: Data Valuation without Pre-Specified Learning Algorithms. - Hoang Anh Just; Feiyang Kang; Jiachen T. Wang; Yi Zeng 005; Myeongseob Ko; Ming Jin 002; Ruoxi Jia 001 (CoRR, 2023)

Differentially Private In-Context Learning. - Ashwinee Panda; Tong Wu; Jiachen T. Wang; Prateek Mittal (CoRR, 2023)

Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation. - Jiachen T. Wang; Yuqing Zhu 005; Yu-Xiang Wang 003; Ruoxi Jia 001; Prateek Mittal (CoRR, 2023)

Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion. - Si Chen 008; Yi Zeng 005; Won Park; Jiachen T. Wang; Xun Chen; Lingjuan Lyu; Zhuoqing Mao 001; Ruoxi Jia 001 (Trans. Mach. Learn. Res., 2023)

One-Round Active Learning through Data Utility Learning and Proxy Models. - Jiachen T. Wang; Si Chen 008; Ruoxi Jia 001 (Trans. Mach. Learn. Res., 2023)

Efficient Data Shapley for Weighted Nearest Neighbor Algorithms. - Jiachen T. Wang; Prateek Mittal; Ruoxi Jia 001 (AISTATS, 2024)

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer. - Junyuan Hong; Jiachen T. Wang; Chenhui Zhang; Zhangheng Li; Bo Li 026; Zhangyang Wang (ICLR, 2024)

Privacy-Preserving In-Context Learning for Large Language Models. - Tong Wu; Ashwinee Panda; Jiachen T. Wang; Prateek Mittal (ICLR, 2024)

BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection. - Tinghao Xie; Xiangyu Qi; Ping He; Yiming Li; Jiachen T. Wang; Prateek Mittal (ICLR, 2024)

Language Models as Science Tutors. - Alexis Chevalier; Jiayi Geng; Alexander Wettig; Howard Chen 003; Sebastian Mizera; Toni Annala; Max Jameson Aragon; Arturo Rodríguez Fanlo; Simon Frieder; Simon Machado; Akshara Prabhakar; Ellie Thieu; et al. (ICML, 2024)

Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. - Jiachen T. Wang; Tianji Yang; James Zou 001; Yongchan Kwon; Ruoxi Jia 001 (ICML, 2024)

Boosting Alignment for Post-Unlearning Text-to-Image Generative Models. - Myeongseob Ko; Henry Li; Zhun Wang; Jonathan Patsenker; Jiachen T. Wang; Qinbin Li; Ming Jin 002; Dawn Song; Ruoxi Jia 001 (NeurIPS, 2024)

GREATS: Online Selection of High-Quality Data for LLM Training in Every Iteration. - Jiachen T. Wang; Tong Wu; Dawn Song; Prateek Mittal; Ruoxi Jia 001 (NeurIPS, 2024)

Language Models as Science Tutors. - Alexis Chevalier; Jiayi Geng; Alexander Wettig; Howard Chen 003; Sebastian Mizera; Toni Annala; Max Jameson Aragon; Arturo Rodríguez Fanlo; Simon Frieder; Simon Machado; Akshara Prabhakar; Ellie Thieu; et al. (CoRR, 2024)

An Economic Solution to Copyright Challenges of Generative AI. - Jiachen T. Wang; Zhun Deng; Hiroaki Chiba-Okabe; Boaz Barak; Weijie J. Su (CoRR, 2024)

A Survey on Data Markets. - Jiayao Zhang 006; Yuran Bi; Mengye Cheng; Jinfei Liu; Kui Ren 001; Qiheng Sun; Yihang Wu; Yang Cao 011; Raul Castro Fernandez; Haifeng Xu; Ruoxi Jia 001; Yongchan Kwon; et al. (CoRR, 2024)

Data Valuation in the Absence of a Reliable Validation Set. - Himanshu Jahagirdar; Jiachen T. Wang; Ruoxi Jia 001 (Trans. Mach. Learn. Res., 2024)

TokenShapley: Token Level Context Attribution with Shapley Value. - Yingtai Xiao; Yuqing Zhu 005; Sirat Samyoun; Wanrong Zhang 002; Jiachen T. Wang; Jian Du (ACL (Findings), 2025)

Data Shapley in One Training Run. - Jiachen T. Wang; Prateek Mittal; Dawn Song; Ruoxi Jia 001 (ICLR, 2025)

Capturing the Temporal Dependence of Training Data Influence. - Jiachen T. Wang; Dawn Song; James Zou 001; Prateek Mittal; Ruoxi Jia 001 (ICLR, 2025)

Effectively Controlling Reasoning Models through Thinking Intervention. - Tong Wu; Chong Xiang 001; Jiachen T. Wang; Prateek Mittal (CoRR, 2025)

Scaling Textual Gradients via Sampling-Based Momentum. - Zixin Ding; Junyuan Hong; Jiachen T. Wang; Zinan Lin 001; Zhangyang Wang; Yuxin Chen (CoRR, 2025)

Does More Inference-Time Compute Really Help Robustness? - Tong Wu; Chong Xiang 001; Jiachen T. Wang; Weichen Yu; Chawin Sitawarin; Vikash Sehwag; Prateek Mittal (CoRR, 2025)