3 citations · 8 across the 7 of their papers we have counts for
7 papers
Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization
Xuxi Chen, Zhendong Wang, Daouda Sow +5
In the rapidly advancing arena of large language models (LLMs), a key challenge is to enhance their capabilities amid a looming shortage of high-quality training data. Our study st…
MPPN: Multi-Resolution Periodic Pattern Network For Long-Term Time Series Forecasting
Xing Wang, Zhendong Wang, Kexin Yang +4
Long-term time series forecasting plays an important role in various real-world scenarios. Recent deep learning methods for long-term series forecasting tend to capture the intrica…
Optimizing Workflow for Elite Developers: Perspectives on Leveraging SE Bots
Zhendong Wang, Yi Wang, David Redmiles
Small-scale automation services in Software Engineering, known as SE Bots, have gradually infiltrated every aspect of daily software development with the goal of enhancing producti…
Collaborative Multi-BS Power Management for Dense Radio Access Network using Deep Reinforcement Learning
Yuchao Chang, Wen Chen, Jun Li +4
Network energy efficiency is a main pillar in the design and operation of wireless communication systems. In this paper, we investigate a dense radio access network (dense-RAN) cap…
Adaptive Hybrid Spatial-Temporal Graph Neural Network for Cellular Traffic Prediction
Xing Wang, Kexin Yang, Zhendong Wang +4
Cellular traffic prediction is an indispensable part for intelligent telecommunication networks. Nevertheless, due to the frequent user mobility and complex network scheduling mech…
Demystifying Arch-hints for Model Extraction: An Attack in Unified Memory System
Zhendong Wang, Xiaoming Zeng, Xulong Tang +3
The deep neural network (DNN) models are deemed confidential due to their unique value in expensive training efforts, privacy-sensitive training data, and proprietary network chara…