58 citations · 173 across the 27 of their papers we have counts for
27 papers
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection
Jiaqi Wang, Xiaochen Wang, Lingjuan Lyu +2
This study introduces the Federated Medical Knowledge Injection (FEDMEKI) platform, a new benchmark designed to address the unique challenges of integrating medical knowledge into…
Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization
Yuanpu Cao, Tianrong Zhang, Bochuan Cao +4
Researchers have been studying approaches to steer the behavior of Large Language Models (LLMs) and build personalized LLMs tailored for various applications. While fine-tuning see…
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning
Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu +3
This paper presents FedType, a simple yet pioneering framework designed to fill research gaps in heterogeneous model aggregation within federated learning (FL). FedType introduces…
Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models
Yuan Zhong, Xiaochen Wang, Jiaqi Wang +5
Synthesizing electronic health records (EHR) data has become a preferred strategy to address data scarcity, improve data quality, and model fairness in healthcare. However, existin…
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
Liwei Che, Jiaqi Wang, Xinyue Liu +1
Federated learning (FL) has obtained tremendous progress in providing collaborative training solutions for distributed data silos with privacy guarantees. However, few existing wor…
Watch the Watcher! Backdoor Attacks on Security-Enhancing Diffusion Models
Changjiang Li, Ren Pang, Bochuan Cao +4
Thanks to their remarkable denoising capabilities, diffusion models are increasingly being employed as defensive tools to reinforce the security of other models, notably in purifyi…