Jiachen T. Wang

According to our database, Jiachen T. Wang authored at least 24 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Data Shapley in One Training Run.

Jiachen T. Wang, Prateek Mittal, Dawn Song, Ruoxi Jia

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

Language Models as Science Tutors.

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

CoRR, 2024

Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits.

Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Language Models as Science Tutors.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection.

Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang, Prateek Mittal

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Privacy-Preserving In-Context Learning for Large Language Models.

Tong Wu, Ashwinee Panda, Jiachen T. Wang, Prateek Mittal

Proceedings of the Twelfth International Conference on Learning Representations, 2024

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer.

Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li, Zhangyang Wang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Efficient Data Shapley for Weighted Nearest Neighbor Algorithms.

Jiachen T. Wang, Prateek Mittal, Ruoxi Jia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

One-Round Active Learning through Data Utility Learning and Proxy Models.

Jiachen T. Wang, Si Chen, Ruoxi Jia

Trans. Mach. Learn. Res., 2023

Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion.

Si Chen, Yi Zeng, Won Park, Jiachen T. Wang, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia

Trans. Mach. Learn. Res., 2023

Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation.

Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal

CoRR, 2023

Differentially Private In-Context Learning.

Ashwinee Panda, Tong Wu, Jiachen T. Wang, Prateek Mittal

CoRR, 2023

LAVA: Data Valuation without Pre-Specified Learning Algorithms.

Hoang Anh Just, Feiyang Kang, Jiachen T. Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia

CoRR, 2023

A Randomized Approach for Tight Privacy Accounting.

Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal

CoRR, 2023

A Note on "Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms".

Jiachen T. Wang, Ruoxi Jia

CoRR, 2023

A Note on "Towards Efficient Data Valuation Based on the Shapley Value".

Jiachen T. Wang, Ruoxi Jia

CoRR, 2023

Towards A Proactive ML Approach for Detecting Backdoor Poison Samples.

Xiangyu Qi, Tinghao Xie, Jiachen T. Wang, Tong Wu, Saeed Mahloujifar, Prateek Mittal

Proceedings of the 32nd USENIX Security Symposium, 2023

ModelPred: A Framework for Predicting Trained Model from Training Data.

Yingyan Zeng, Jiachen T. Wang, Si Chen, Hoang Anh Just, Ran Jin, Ruoxi Jia

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

A Randomized Approach to Tight Privacy Accounting.

Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Privacy-Friendly Approach to Data Valuation.

Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Uncovering Adversarial Risks of Test-Time Adaptation.

Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal

Proceedings of the International Conference on Machine Learning, 2023

Data Banzhaf: A Robust Data Valuation Framework for Machine Learning.

Jiachen T. Wang, Ruoxi Jia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning.

Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022