activity
20242026
most citedFlowDistill: Scalable Traffic Flow Prediction via Distillation from LLMs

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR2026

Context-Aware Metric Differential Privacy for Vehicle Trajectory Data

Gaoyi Chen, Yan Huang, Chenxi Qiu

Metric Differential Privacy (mDP) generalizes differential privacy by allowing privacy guarantees to be expressed with respect to an arbitrary distance metric over secrets. While m…

cs.LG2026

Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption

Gaoyi Chen, Minghao Li, Weishi Shi +4

Metric differential privacy (mDP) strengthens local differential privacy (LDP) by scaling noise to semantic distance, but many machine learning (ML) systems are consumed under join…

cs.LG2025★ 1 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.LG2025★ 2 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.CR2024★ 1 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…