Proof-of-Play: A Novel Consensus Model for Blockchain-based Peer-to-Peer Gaming System. - Ho Yin Yuen; Feijie Wu; Wei Cai 002; Henry C. B. Chan; Qiao Yan; Victor C. M. Leung (BSCI, 2019)

Infinity Battle: A Glance at How Blockchain Techniques Serve in a Serverless Gaming System. - Feijie Wu; Ho Yin Yuen; Henry C. B. Chan; Victor C. M. Leung; Wei Cai 002 (ACM Multimedia, 2020)

Parameterized Knowledge Transfer for Personalized Federated Learning. - Jie Zhang 076; Song Guo 001; Xiaosong Ma; Haozhao Wang; Wenchao Xu 001; Feijie Wu (NeurIPS, 2021)

Sign bit is enough: a learning synchronization framework for multi-hop all-reduce with ultimate compression. - Feijie Wu; Shiqi He; Song Guo 001; Zhihao Qu; Haozhao Wang; Weihua Zhuang; Jie Zhang 076 (DAC, 2022)

Accelerating Federated Learning via Sampling Anchor Clients with Large Batches. - Feijie Wu; Song Guo 001; Zhihao Qu; Shiqi He; Ziming Liu (CoRR, 2022)

Anchor Sampling for Federated Learning with Partial Client Participation. - Feijie Wu; Song Guo 001; Zhihao Qu; Shiqi He; Ziming Liu; Jing Gao 004 (ICML, 2023)

Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding. - Haoyu Wang 004; Yaqing Wang 001; Feijie Wu; Hongfei Xue; Jing Gao 004 (KDD, 2023)

GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning. - Shiqi He; Qifan Yan; Feijie Wu; Lanjun Wang; Mathias Lécuyer; Ivan Beschastnikh (MLSys, 2023)

Facilitating Serverless Match-based Online Games with Novel Blockchain Technologies. - Feijie Wu; Ho Yin Yuen; Henry C. B. Chan; Victor C. M. Leung; Wei Cai 002 (ACM Trans. Internet Techn., 2023)

From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization. - Feijie Wu; Song Guo 001; Haozhao Wang; Haobo Zhang 002; Zhihao Qu; Jie Zhang 076; Ziming Liu (IEEE Trans. Parallel Distributed Syst., 2023)

SHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation. - Xiaoze Liu; Ting Sun 004; Tianyang Xu; Feijie Wu; Cunxiang Wang; Xiaoqian Wang 001; Jing Gao 004 (EMNLP, 2024)

Towards Poisoning Fair Representations. - Tianci Liu 003; Haoyu Wang 004; Feijie Wu; Hengtong Zhang; Pan Li 005; Lu Su 001; Jing Gao 004 (ICLR, 2024)

FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model. - Feijie Wu; Zitao Li; Yaliang Li; Bolin Ding; Jing Gao 004 (KDD, 2024)

FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction. - Feijie Wu; Xingchen Wang; Yaqing Wang 001; Tianci Liu 003; Lu Su 001; Jing Gao 004 (NeurIPS, 2024)

Towards Efficient Heterogeneous Multi-Modal Federated Learning with Hierarchical Knowledge Disentanglement. - Xingchen Wang; Haoyu Wang 004; Feijie Wu; Tianci Liu 003; Qiming Cao; Lu Su 001 (SenSys, 2024)

On the Client Preference of LLM Fine-tuning in Federated Learning. - Feijie Wu; Xiaoze Liu; Haoyu Wang 004; Xingchen Wang; Jing Gao 004 (CoRR, 2024)

Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs. - Xiaoze Liu; Feijie Wu; Tianyang Xu; Zhuo Chen 007; Yichi Zhang 009; Xiaoqian Wang 001; Jing Gao 004 (IEEE Data Eng. Bull., 2024)

Tree Learning: Towards Promoting Coordination in Scalable Multi-Client Training Acceleration. - Tao Guo 004; Song Guo 001; Feijie Wu; Wenchao Xu 001; Jiewei Zhang; Qihua Zhou; Quan Chen 003; Weihua Zhuang (IEEE Trans. Mob. Comput., 2024)

Towards Federated RLHF with Aggregated Client Preference for LLMs. - Feijie Wu; Xiaoze Liu; Haoyu Wang 004; Xingchen Wang; Lu Su 001; Jing Gao 004 (ICLR, 2025)

Talk to Right Specialists: Routing and Planning in Multi-agent System for Question Answering. - Feijie Wu; Zitao Li; Fei Wei; Yaliang Li; Bolin Ding; Jing Gao 004 (CoRR, 2025)

SUV: Scalable Large Language Model Copyright Compliance with Regularized Selective Unlearning. - Tianyang Xu; Xiaoze Liu; Feijie Wu; Xiaoqian Wang 001; Jing Gao 004 (CoRR, 2025)