most citedFlowDistill: Scalable Traffic Flow Prediction via Distillation from LLMs

2 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20251 cited

FUSE-Traffic: Fusion of Unstructured and Structured Data for Event-aware Traffic Forecasting

Chenyang Yu, Xinpeng Xie, Yan Huang +1

Accurate traffic forecasting is a core technology for building Intelligent Transportation Systems (ITS), enabling better urban resource allocation and improved travel experiences.…

cs.LG20252 cited

FlowDistill: Scalable Traffic Flow Prediction via Distillation from LLMs

Chenyang Yu, Xinpeng Xie, Yan Huang +1

Accurate traffic flow prediction is vital for optimizing urban mobility, yet it remains difficult in many cities due to complex spatio-temporal dependencies and limited high-qualit…

cs.CR2025

A Decade of Metric Differential Privacy: Advancements and Applications

Xinpeng Xie, Chenyang Yu, Yan Huang +2

Metric Differential Privacy (mDP) builds upon the core principles of Differential Privacy (DP) by incorporating various distance metrics, which offer adaptable and context-sensitiv…

cs.CR20241 cited

Protecting Vehicle Location Privacy with Contextually-Driven Synthetic Location Generation

Sourabh Yadav, Chenyang Yu, Xinpeng Xie +2

Geo-obfuscation is a Location Privacy Protection Mechanism used in location-based services that allows users to report obfuscated locations instead of exact ones. A formal privacy…

cs.AI2024

Harnessing LLMs for Cross-City OD Flow Prediction

Chenyang Yu, Xinpeng Xie, Yan Huang +1

Understanding and predicting Origin-Destination (OD) flows is crucial for urban planning and transportation management. Traditional OD prediction models, while effective within sin…