6 citations · 8 across the 8 of their papers we have counts for
8 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…
VisualNeo: Bridging the Gap between Visual Query Interfaces and Graph Query Engines
Kai Huang, Houdong Liang, Chongchong Yao +5
Visual Graph Query Interfaces (VQIs) empower non-programmers to query graph data by constructing visual queries intuitively. Devising efficient technologies in Graph Query Engines…
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…
Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists
Yue Cui, Liuyi Yao, Shuchang Tao +4
Large language models (LLMs) have significantly advanced natural language processing, particularly through the integration of external tools and APIs. However, their effectiveness…
Efficient Leave-one-out Approximation in LLM Multi-agent Debate Based on Introspection
Yue Cui, Liuyi Yao, Zitao Li +3
Multi-agent systems based on large language models (LLMs) advance automatic task completion in various fields, where debate is a common cooperation form for agents to solve complic…
A Survey on Contribution Evaluation in Vertical Federated Learning
Yue Cui, Chung-ju Huang, Yuzhu Zhang +4
Vertical Federated Learning (VFL) has emerged as a critical approach in machine learning to address privacy concerns associated with centralized data storage and processing. VFL fa…
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…
An Auction-based Marketplace for Model Trading in Federated Learning
Yue Cui, Liuyi Yao, Yaliang Li +3
Federated learning (FL) is increasingly recognized for its efficacy in training models using locally distributed data. However, the proper valuation of shared data in this collabor…