2 citations · 4 across the 26 of their papers we have counts for
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3 papers · 1 filter
cs.CL2024★ 1 cited
Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning
Wenke Huang, Jian Liang, Zekun Shi +6
Multimodal Large Language Model (MLLM) have demonstrated strong generalization capabilities across diverse distributions and tasks, largely due to extensive pre-training datasets.…
cs.LG2024★ 2 cited
FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference
Zihan Tan, Guancheng Wan, Wenke Huang +1
Personalized Federated Graph Learning (pFGL) facilitates the decentralized training of Graph Neural Networks (GNNs) without compromising privacy while accommodating personalized re…
cs.LG2024★ 1 cited
Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity
Yuhang Chen, Wenke Huang, Mang Ye
Federated learning (FL) has emerged as a new paradigm for privacy-preserving collaborative training. Under domain skew, the current FL approaches are biased and face two fairness p…