80 citations · 178 across the 60 of their papers we have counts for
12 papers · 1 filter
Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity
Yide Ran, Wentao Guo, Jingwei Sun +7
Federated Learning enables collaborative fine-tuning of Large Language Models (LLMs) across decentralized Non-Independent and Identically Distributed (Non-IID) clients, but such mo…
MMD-Newton Method for Multi-objective Optimization
Hao Wang, Chenyu Shi, Angel E. Rodriguez-Fernandez +1
Maximum mean discrepancy (MMD) has been widely employed to measure the distance between probability distributions. In this paper, we propose using MMD to solve continuous multi-obj…
ServerlessLoRA: Minimizing Latency and Cost in Serverless Inference for LoRA-Based LLMs
Yifan Sui, Hao Wang, Hanfei Yu +2
Serverless computing has grown rapidly for serving Large Language Model (LLM) inference due to its pay-as-you-go pricing, fine-grained GPU usage, and rapid scaling. However, our an…
Geographical Information Alignment Boosts Traffic Analysis via Transpose Cross-attention
Xiangyu Jiang, Xiwen Chen, Hao Wang +1
Traffic accident prediction is crucial for enhancing road safety and mitigating congestion, and recent Graph Neural Networks (GNNs) have shown promise in modeling the inherent grap…
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning
Jianqing Zhang, Yang Hua, Hao Wang +5
Federated Learning (FL) is popular for its privacy-preserving and collaborative learning capabilities. Recently, personalized FL (pFL) has received attention for its ability to add…
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data
Youlong Ding, Xueyang Wu, Hao Wang +1
The Transformer has emerged as a versatile and effective architecture with broad applications. However, it still remains an open problem how to efficiently train a Transformer mode…