10 papers
From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction
Shuhao Li, Weidong Yang, Yue Cui +4
Efficient acquisition, storage, and utilization of traffic data are critical challenges in spatio-temporal data management. Most traffic data systems collect and store observations…
PseudoBridge: Pseudo Code as the Bridge for Better Semantic and Logic Alignment in Code Retrieval
Yixuan Li, Xinyi Liu, Weidong Yang +4
Code retrieval aims to find relevant code snippets matching natural language queries within massive codebases, playing a vital role in software development. Recent advances leverag…
LogReasoner: Empowering LLMs with Expert-like Coarse-to-Fine Reasoning for Automated Log Analysis
Lipeng Ma, Yixuan Li, Weidong Yang +7
Log analysis is crucial for monitoring system health and diagnosing failures in complex systems. Recent advances in large language models (LLMs) offer new opportunities for automat…
Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generation
Shuhao Li, Weidong Yang, Yue Cui +4
Fine-grained traffic management and prediction are fundamental to key applications such as autonomous driving, lane change guidance, and traffic signal control. However, obtaining…
MGSR: 2D/3D Mutual-boosted Gaussian Splatting for High-fidelity Surface Reconstruction under Various Light Conditions
Qingyuan Zhou, Yuehu Gong, Weidong Yang +6
Novel view synthesis (NVS) and surface reconstruction (SR) are essential tasks in 3D Gaussian Splatting (3D-GS). Despite recent progress, these tasks are often addressed independen…
Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baseline
Shuhao Li, Yue Cui, Jingyi Xu +5
Traffic prediction has long been a focal and pivotal area in research, witnessing both significant strides from city-level to road-level predictions in recent years. With the advan…