Jiachen T. Wang

According to our database, Jiachen T. Wang authored at least 16 papers between 2022 and 2024.

Collaborative distances:

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

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

Efficient Data Shapley for Weighted Nearest Neighbor Algorithms.

Jiachen T. Wang, Prateek Mittal, Ruoxi Jia

CoRR, 2024

2023

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

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

CoRR, 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

BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection.

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

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