3 citations · 3 across the 5 of their papers we have counts for
6 papers
Scene-Conditioned Relation Routing for urban cellular activity forecasting
Qingzhong Li, Jingye Lin, Hui Ma +4
Urban cellular activity forecasting requires jointly modeling heterogeneous spatiotemporal signals, including SMS usage, mobile network traffic, and call activity. Existing methods…
Multimodal Spatiotemporal-Frequency Fusion with Peak Enhancement for Cellular Traffic Forecasting
Qingzhong Li, Yue Hu, Hui Ma +4
Accurate forecasting of cellular network traffic is essential for network planning, resource allocation, and quality-of-service assurance in modern mobile communication systems. Re…
GraFSTNet: Graph-based Frequency SpatioTemporal Network for Cellular Traffic Prediction
Ziyi Li, Hui Ma, Fei Xing +2
With rapid expansion of cellular networks and the proliferation of mobile devices, cellular traffic data exhibits complex temporal dynamics and spatial correlations, posing challen…
AsynDBT: Asynchronous Distributed Bilevel Tuning for efficient In-Context Learning with Large Language Models
Hui Ma, Shaoyu Dou, Ya Liu +3
With the rapid development of large language models (LLMs), an increasing number of applications leverage cloud-based LLM APIs to reduce usage costs. However, since cloud-based mod…
An Adaptive Differentially Private Federated Learning Framework
Jin Wang, Hui Ma, Yajun Zhang +4
Federated learning enables collaborative model training across distributed clients while preserving data privacy. However, in practical deployments, device heterogeneity and non-in…
MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data
Meng Fang, Xiangpeng Wan, Fei Lu +2
Large language models (LLMs) have significantly advanced natural language understanding and demonstrated strong problem-solving abilities. Despite these successes, most LLMs still…