A New Defense Against Adversarial Images: Turning a Weakness into a Strength. - Shengyuan Hu 001; Tao Yu; Chuan Guo 001; Wei-Lun Chao; Kilian Q. Weinberger (NeurIPS, 2019)

Federated Multi-Task Learning for Competing Constraints. - Tian Li 005; Shengyuan Hu 001; Ahmad Beirami; Virginia Smith (CoRR, 2020)

Ditto: Fair and Robust Federated Learning Through Personalization. - Tian Li 005; Shengyuan Hu 001; Ahmad Beirami; Virginia Smith (ICML, 2021)

On Privacy and Personalization in Cross-Silo Federated Learning. - Ken Ziyu Liu; Shengyuan Hu 001; Steven Wu 001; Virginia Smith (NeurIPS, 2022)

Provably Fair Federated Learning via Bounded Group Loss. - Shengyuan Hu 001; Zhiwei Steven Wu; Virginia Smith (CoRR, 2022)

FedSynth: Gradient Compression via Synthetic Data in Federated Learning. - Shengyuan Hu 001; Jack Goetz; Kshitiz Malik; Hongyuan Zhan; Zhe Liu; Yue Liu (CoRR, 2022)

Federated Learning as a Network Effects Game. - Shengyuan Hu 001; Dung Daniel T. Ngo; Shuran Zheng; Virginia Smith; Zhiwei Steven Wu (CoRR, 2023)

Private Multi-Task Learning: Formulation and Applications to Federated Learning. - Shengyuan Hu 001; Steven Wu 001; Virginia Smith (Trans. Mach. Learn. Res., 2023)

No Free Lunch in LLM Watermarking: Trade-offs in Watermarking Design Choices. - Qi Pang; Shengyuan Hu 001; Wenting Zheng; Virginia Smith (NeurIPS, 2024)

Fair Federated Learning via Bounded Group Loss. - Shengyuan Hu 001; Zhiwei Steven Wu; Virginia Smith (SaTML, 2024)

Attacking LLM Watermarks by Exploiting Their Strengths. - Qi Pang; Shengyuan Hu 001; Wenting Zheng; Virginia Smith (CoRR, 2024)

Privacy Amplification for the Gaussian Mechanism via Bounded Support. - Shengyuan Hu 001; Saeed Mahloujifar; Virginia Smith; Kamalika Chaudhuri; Chuan Guo 001 (CoRR, 2024)

Jogging the Memory of Unlearned Model Through Targeted Relearning Attack. - Shengyuan Hu 001; Yiwei Fu; Zhiwei Steven Wu; Virginia Smith (CoRR, 2024)

Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning. - Shengyuan Hu 001; Yiwei Fu; Steven Z. Wu; Virginia Smith (ICLR, 2025)

Position: LLM Unlearning Benchmarks are Weak Measures of Progress. - Pratiksha Thaker; Shengyuan Hu 001; Neil Kale; Yash Maurya; Zhiwei Steven Wu; Virginia Smith (SaTML, 2025)

Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference. - Terrance Liu; Matteo Boglioni; Yiwei Fu; Shengyuan Hu 001; Pratiksha Thaker; Zhiwei Steven Wu (CoRR, 2025)

BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap. - Shengyuan Hu 001; Neil Kale; Pratiksha Thaker; Yiwei Fu; Steven Wu 001; Virginia Smith (CoRR, 2025)