5 citations · 5 across the 8 of their papers we have counts for
9 papers
Towards Privacy-Preserving Federated Prompt Tuning under Data Heterogeneity: A Subspace-Decomposed Expert Approach
Yuhua Wang, Xiaodong Li, Yihao Guo +6
Federated prompt tuning (FPT) enables collaborative adaptation of vision--language models (VLMs) using lightweight prompts. Existing methods often address heterogeneity and privacy…
Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning
Yuhua Wang, Qinnan Zhang, Xiaodong Li +6
Prototype-based Personalized Federated Learning (ProtoPFL) enables efficient multi-domain adaptation by communicating compact class prototypes, but directly sharing them poses priv…
Mask-Free Privacy Extraction and Rewriting: A Domain-Aware Approach via Prototype Learning
Xiaodong Li, Yuhua Wang, Qingchen Yu +5
Client-side privacy rewriting is crucial for deploying LLMs in privacy-sensitive domains. However, existing approaches struggle to balance privacy and utility. Full-text methods of…
ContribChain: A Stress-Balanced Blockchain Sharding Protocol with Node Contribution Awareness
Xinpeng Huang, Wanqing Jie, Shiwen Zhang +8
Existing blockchain sharding protocols have focused on eliminating imbalanced workload distributions. However, even with workload balance, disparities in processing capabilities ca…
CodeBC: A More Secure Large Language Model for Smart Contract Code Generation in Blockchain
Lingxiang Wang, Hainan Zhang, Qinnan Zhang +4
Large language models (LLMs) excel at generating code from natural language instructions, yet they often lack an understanding of security vulnerabilities. This limitation makes it…
Detecting Stealthy Backdoor Samples based on Intra-class Distance for Large Language Models
Jinwen Chen, Hainan Zhang, Fei Sun +4
Stealthy data poisoning during fine-tuning can backdoor large language models (LLMs), threatening downstream safety. Existing detectors either use classifier-style probability sign…
FedSEA-LLaMA: A Secure, Efficient and Adaptive Federated Splitting Framework for Large Language Models
Zishuai Zhang, Hainan zhang, Weihua Li +4
Private data holds promise for improving LLMs due to its high quality, but its scattered distribution across data silos and the high computational demands of LLMs limit their deplo…
Know Your Account: Double Graph Inference-based Account De-anonymization on Ethereum
Shuyi Miao, Wangjie Qiu, Hongwei Zheng +6
The scaled Web 3.0 digital economy, represented by decentralized finance (DeFi), has sparked increasing interest in the past few years, which usually relies on blockchain for token…
Economic Systems in Metaverse: Basics, State of the Art, and Challenges
Huawei Huang, Qinnan Zhang, Taotao Li +7
Economic systems play pivotal roles in the metaverse. However, we have not yet found an overview that systematically introduces economic systems for the metaverse. Therefore, we re…