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ORCIDJiachen T. Wang
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- affiliation: Princeton University, Princeton, NJ, USA
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2020 – today
- 2025
[c18]Yingtai Xiao, Yuqing Zhu, Sirat Samyoun, Wanrong Zhang, Jiachen T. Wang, Jian Du:
TokenShapley: Token Level Context Attribution with Shapley Value. ACL (Findings) 2025: 3882-3894- [c17]Jiachen T. Wang, Prateek Mittal, Dawn Song, Ruoxi Jia:
Data Shapley in One Training Run. ICLR 2025 - [c16]Jiachen T. Wang, Dawn Song, James Zou, Prateek Mittal, Ruoxi Jia:
Capturing the Temporal Dependence of Training Data Influence. ICLR 2025 - [i24]Tong Wu, Chong Xiang, Jiachen T. Wang, Prateek Mittal:
Effectively Controlling Reasoning Models through Thinking Intervention. CoRR abs/2503.24370 (2025) - [i23]Zixin Ding, Junyuan Hong, Jiachen T. Wang, Zinan Lin, Zhangyang Wang, Yuxin Chen:
Scaling Textual Gradients via Sampling-Based Momentum. CoRR abs/2506.00400 (2025) - [i22]Yingtai Xiao, Yuqing Zhu, Sirat Samyoun, Wanrong Zhang, Jiachen T. Wang, Jian Du:
TokenShapley: Token Level Context Attribution with Shapley Value. CoRR abs/2507.05261 (2025) - [i21]Tong Wu, Chong Xiang, Jiachen T. Wang, Weichen Yu, Chawin Sitawarin, Vikash Sehwag, Prateek Mittal:
Does More Inference-Time Compute Really Help Robustness? CoRR abs/2507.15974 (2025) - [i20]Mahavir Dabas, Tran Huynh, Nikhil Reddy Billa, Jiachen T. Wang, Peng Gao, Charith Peris, Yao Ma, Rahul Gupta, Ming Jin, Prateek Mittal, Ruoxi Jia:
Adversarial Déjà Vu: Jailbreak Dictionary Learning for Stronger Generalization to Unseen Attacks. CoRR abs/2510.21910 (2025) - [i19]Jiachen T. Wang, Tong Wu, Kaifeng Lyu, James Zou, Dawn Song, Ruoxi Jia, Prateek Mittal:
Can Small Training Runs Reliably Guide Data Curation? Rethinking Proxy-Model Practice. CoRR abs/2512.24503 (2025) - 2024
- [j3]Himanshu Jahagirdar, Jiachen T. Wang, Ruoxi Jia:
Data Valuation in the Absence of a Reliable Validation Set. Trans. Mach. Learn. Res. 2024 (2024) - [c15]Jiachen T. Wang, Prateek Mittal, Ruoxi Jia:
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms. AISTATS 2024: 2557-2565 - [c14]Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li, Zhangyang Wang:
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer. ICLR 2024 - [c13]Tong Wu, Ashwinee Panda, Jiachen T. Wang, Prateek Mittal:
Privacy-Preserving In-Context Learning for Large Language Models. ICLR 2024 - [c12]Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang, Prateek Mittal:
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection. ICLR 2024 - [c11]Alexis Chevalier, Jiayi Geng, Alexander Wettig, Howard Chen, Sebastian Mizera, Toni Annala, Max Jameson Aragon, Arturo Rodríguez Fanlo, Simon Frieder, Simon Machado, Akshara Prabhakar, Ellie Thieu, Jiachen T. Wang, Zirui Wang, Xindi Wu, Mengzhou Xia, Wenhan Xia, Jiatong Yu, Junjie Zhu, Zhiyong Jason Ren, Sanjeev Arora, Danqi Chen:
Language Models as Science Tutors. ICML 2024 - [c10]Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia:
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. ICML 2024 - [c9]Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen T. Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia:
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models. NeurIPS 2024 - [c8]Jiachen T. Wang, Tong Wu, Dawn Song, Prateek Mittal, Ruoxi Jia:
GREATS: Online Selection of High-Quality Data for LLM Training in Every Iteration. NeurIPS 2024 - [i18]Jiachen T. Wang, Prateek Mittal, Ruoxi Jia:
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms. CoRR abs/2401.11103 (2024) - [i17]Alexis Chevalier, Jiayi Geng, Alexander Wettig, Howard Chen, Sebastian Mizera, Toni Annala, Max Jameson Aragon, Arturo Rodríguez Fanlo, Simon Frieder, Simon Machado, Akshara Prabhakar, Ellie Thieu, Jiachen T. Wang, Zirui Wang, Xindi Wu, Mengzhou Xia, Wenhan Jia, Jiatong Yu, Jun-Jie Zhu, Zhiyong Jason Ren, Sanjeev Arora, Danqi Chen:
Language Models as Science Tutors. CoRR abs/2402.11111 (2024) - [i16]Jiachen T. Wang, Zhun Deng, Hiroaki Chiba-Okabe, Boaz Barak, Weijie J. Su
:
An Economic Solution to Copyright Challenges of Generative AI. CoRR abs/2404.13964 (2024) - [i15]Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia:
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. CoRR abs/2405.03875 (2024) - [i14]Jiachen T. Wang, Prateek Mittal, Dawn Song, Ruoxi Jia:
Data Shapley in One Training Run. CoRR abs/2406.11011 (2024) - [i13]Jiayao Zhang, Yuran Bi, Mengye Cheng, Jinfei Liu, Kui Ren, Qiheng Sun, Yihang Wu, Yang Cao, Raul Castro Fernandez, Haifeng Xu, Ruoxi Jia, Yongchan Kwon, Jian Pei, Jiachen T. Wang, Haocheng Xia, Li Xiong, Xiaohui Yu, James Zou:
A Survey on Data Markets. CoRR abs/2411.07267 (2024) - [i12]Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen T. Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia:
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models. CoRR abs/2412.07808 (2024) - [i11]Jiachen T. Wang, Dawn Song, James Zou, Prateek Mittal, Ruoxi Jia:
Capturing the Temporal Dependence of Training Data Influence. CoRR abs/2412.09538 (2024) - 2023
- [j2]Si Chen, Yi Zeng, Won Park, Jiachen T. Wang, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia:
Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Jiachen T. Wang, Si Chen, Ruoxi Jia:
One-Round Active Learning through Data Utility Learning and Proxy Models. Trans. Mach. Learn. Res. 2023 (2023) - [c7]Jiachen T. Wang, Ruoxi Jia:
Data Banzhaf: A Robust Data Valuation Framework for Machine Learning. AISTATS 2023: 6388-6421 - [c6]Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Uncovering Adversarial Risks of Test-Time Adaptation. ICML 2023: 37456-37495 - [c5]Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal:
A Privacy-Friendly Approach to Data Valuation. NeurIPS 2023 - [c4]Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal:
A Randomized Approach to Tight Privacy Accounting. NeurIPS 2023 - [c3]Yingyan Zeng, Jiachen T. Wang, Si Chen, Hoang Anh Just, Ran Jin, Ruoxi Jia:
ModelPred: A Framework for Predicting Trained Model from Training Data. SaTML 2023: 432-449 - [c2]Xiangyu Qi, Tinghao Xie, Jiachen T. Wang, Tong Wu, Saeed Mahloujifar, Prateek Mittal:
Towards A Proactive ML Approach for Detecting Backdoor Poison Samples. USENIX Security Symposium 2023: 1685-1702 - [i10]Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Uncovering Adversarial Risks of Test-Time Adaptation. CoRR abs/2301.12576 (2023) - [i9]Jiachen T. Wang, Ruoxi Jia:
A Note on "Towards Efficient Data Valuation Based on the Shapley Value". CoRR abs/2302.11431 (2023) - [i8]Jiachen T. Wang, Ruoxi Jia:
A Note on "Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms". CoRR abs/2304.04258 (2023) - [i7]Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal:
A Randomized Approach for Tight Privacy Accounting. CoRR abs/2304.07927 (2023) - [i6]Hoang Anh Just, Feiyang Kang, Jiachen T. Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia:
LAVA: Data Valuation without Pre-Specified Learning Algorithms. CoRR abs/2305.00054 (2023) - [i5]Ashwinee Panda, Tong Wu, Jiachen T. Wang, Prateek Mittal:
Differentially Private In-Context Learning. CoRR abs/2305.01639 (2023) - [i4]Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang, Prateek Mittal:
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection. CoRR abs/2308.12439 (2023) - [i3]Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal:
Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation. CoRR abs/2308.15709 (2023) - [i2]Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li, Zhangyang Wang:
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer. CoRR abs/2312.03724 (2023) - 2022
- [c1]Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal:
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. NeurIPS 2022 - [i1]Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal:
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. CoRR abs/2209.07716 (2022)
Coauthor Index
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