49 citations · 81 across the 7 of their papers we have counts for
7 papers
Large Language Model Distilling Medication Recommendation Model
Qidong Liu, Xian Wu, Xiangyu Zhao +4
The recommendation of medication is a vital aspect of intelligent healthcare systems, as it involves prescribing the most suitable drugs based on a patient's specific health needs.…
Enhancing Traffic Prediction with Learnable Filter Module
Yuanshao Zhu, Yongchao Ye, Xiangyu Zhao +1
Modeling future traffic conditions often relies heavily on complex spatial-temporal neural networks to capture spatial and temporal correlations, which can overlook the inherent no…
When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications
Qidong Liu, Xian Wu, Xiangyu Zhao +4
The recent surge in Large Language Models (LLMs) has garnered significant attention across numerous fields. Fine-tuning is often required to fit general LLMs for a specific domain,…
DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model
Yuanshao Zhu, Yongchao Ye, Shiyao Zhang +2
Pervasive integration of GPS-enabled devices and data acquisition technologies has led to an exponential increase in GPS trajectory data, fostering advancements in spatial-temporal…
Traffic Prediction with Transfer Learning: A Mutual Information-based Approach
Yunjie Huang, Xiaozhuang Song, Yuanshao Zhu +2
In modern traffic management, one of the most essential yet challenging tasks is accurately and timely predicting traffic. It has been well investigated and examined that deep lear…
AutoDenoise: Automatic Data Instance Denoising for Recommendations
Weilin Lin, Xiangyu Zhao, Yejing Wang +2
Historical user-item interaction datasets are essential in training modern recommender systems for predicting user preferences. However, the arbitrary user behaviors in most recomm…
Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis
Yi Liu, Yuanshao Zhu, James J. Q. Yu
Efficient collaboration between collaborative machine learning and wireless communication technology, forming a Federated Edge Learning (FEEL), has spawned a series of next-generat…