How Asynchronous can Federated Learning Be? - Ningxin Su; Baochun Li (IWQoS, 2022)

Plato: An Open-Source Research Framework for Production Federated Learning. - Baochun Li; Ningxin Su; Chen Ying; Fei Wang 075 (ACM TUR-C, 2023)

Asynchronous Federated Unlearning. - Ningxin Su; Baochun Li (INFOCOM, 2023)

Multi-Server Stable Rendezvous for the Metaverse. - Ningxin Su; Baochun Li; Bo Li 001 (MetaCom, 2023)

Pack: Towards Communication-Efficient Homomorphic Encryption in Federated Learning. - Zeyuan Zuo; Ningxin Su; Baochun Li; Teng Zhang (SoCC, 2024)

Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning. - Sijia Chen; Ningxin Su; Baochun Li (ICDCS, 2024)

Titanic: Towards Production Federated Learning with Large Language Models. - Ningxin Su; Chenghao Hu; Baochun Li; Bo Li 001 (INFOCOM, 2024)

Relic: Federated Conditional Textual Inversion with Prototype Alignment. - Sijia Chen; Ningxin Su; Baochun Li (IWQoS, 2024)

MLOps in the Metaverse: Human-Centric Continuous Integration. - Ningxin Su; Baochun Li (IEEE J. Sel. Areas Commun., 2024)