8 citations · 14 across the 3 of their papers we have counts for
3 papers
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.LG2023★ 8 cited
Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark
Wenke Huang, Mang Ye, Zekun Shi +4
Federated learning has emerged as a promising paradigm for privacy-preserving collaboration among different parties. Recently, with the popularity of federated learning, an influx…
cs.LG2023★ 5 cited
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning
Wenke Huang, Mang Ye, Zekun Shi +1
Federated learning is an important privacy-preserving multi-party learning paradigm, involving collaborative learning with others and local updating on private data. Model heteroge…