3 citations · 3 across the 5 of their papers we have counts for
5 papers
Dynamic Positional Attention Modulation for Parameter-Efficient Fine-Tuning of Large Language Models
Dayan Pan, Jingyuan Wang, Xie Yu
Parameter-efficient fine-tuning (PEFT) has become a standard approach for adapting large language models to downstream tasks. However, most existing PEFT methods rely on uniform an…
HieraMix: A Hierarchical MLP-Mixer for Large-Scale Traffic Forecasting
Yongyao Wang, Xie Yu, Jingyuan Wang +2
Traffic forecasting task is significant to modern urban management. Recently, there is growing attention on large-scale forecasting, as it better reflects the complexity of real-wo…
AI-Driven Adaptive Air Transit Network with Modular Aerial Pods
Amir Shafiee, Alireza Yazdiani, Hanieh Rastegar +9
This paper presents an adaptive air transit network leveraging modular aerial pods and artificial intelligence (AI) to address urban mobility challenges. Passenger demand, forecast…
Bridging Traffic State and Trajectory for Dynamic Road Network and Trajectory Representation Learning
Chengkai Han, Jingyuan Wang, Yongyao Wang +4
Effective urban traffic management is vital for sustainable city development, relying on intelligent systems with machine learning tasks such as traffic flow prediction and travel…
BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis
Xie Yu, Jingyuan Wang, Yifan Yang +2
Typical dynamic ST data includes trajectory data (representing individual-level mobility) and traffic state data (representing population-level mobility). Traditional studies often…