6 citations · 11 across the 5 of their papers we have counts for
5 papers
NH-CROP: Robust Pricing for Governed Language Data Assets under Cost Uncertainty
Xu Zheng, Feiyu Wu, Zhuocheng Wang +2
Language data are increasingly acquired and governed as assets, yet platforms often price candidate resources before knowing their true privacy or access costs. We study online pri…
Preventing Rank Collapse in Federated Low-Rank Adaptation with Client Heterogeneity
Fei Wu, Jia Hu, Geyong Min +1
Federated low-rank adaptation (FedLoRA) has facilitated communication-efficient and privacy-preserving fine-tuning of foundation models for downstream tasks. In practical federated…
Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation
Fei Wu, Jia Hu, Geyong Min +1
Driven by the rapid growth of model parameters, parameter-efficient fine-tuning (PEFT) has become essential for adapting large models to diverse downstream tasks under constrained…
Adaptive Rank Allocation for Federated Parameter-Efficient Fine-Tuning of Language Models
Fei Wu, Jia Hu, Geyong Min +1
Pre-trained Language Models (PLMs) have demonstrated their superiority and versatility in modern Natural Language Processing (NLP), effectively adapting to various downstream tasks…
Federated Continual Learning for Edge-AI: A Comprehensive Survey
Zi Wang, Fei Wu, Feng Yu +3
Edge-AI, the convergence of edge computing and artificial intelligence (AI), has become a promising paradigm that enables the deployment of advanced AI models at the network edge,…