Optimal Differentially Private Learning with Public Data. - Andrew Lowy; Zeman Li; Tianjian Huang; Meisam Razaviyayn (CoRR, 2023)

Optimal Differentially Private Model Training with Public Data. - Andrew Lowy; Zeman Li; Tianjian Huang; Meisam Razaviyayn (ICML, 2024)

Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. - Zeman Li; Xinwei Zhang 001; Peilin Zhong; Yuan Deng; Meisam Razaviyayn; Vahab Mirrokni (ICLR, 2025)

PiKE: Adaptive Data Mixing for Multi-Task Learning Under Low Gradient Conflicts. - Zeman Li; Yuan Deng; Peilin Zhong; Meisam Razaviyayn; Vahab Mirrokni (CoRR, 2025)

Synthetic Text Generation for Training Large Language Models via Gradient Matching. - Dang Nguyen; Zeman Li; MohammadHossein Bateni; Vahab Mirrokni; Meisam Razaviyayn; Baharan Mirzasoleiman (CoRR, 2025)

ATLAS: Learning to Optimally Memorize the Context at Test Time. - Ali Behrouz; Zeman Li; Praneeth Kacham; Majid Daliri; Yuan Deng; Peilin Zhong; Meisam Razaviyayn; Vahab Mirrokni (CoRR, 2025)