2 citations · 2 across the 4 of their papers we have counts for
6 papers
Risk-aware Road-network Trajectory Synthesis under Local Differential Privacy
Hongzhen Xiang, Chenxu Wang, Yumeng Song +5
Road-network trajectory synthesis under local differential privacy (LDP) enables mobility data analysis without uploading raw trajectories to an untrusted server. Existing locally…
GAPL: Grounded Action-effect Policy Learning for LLM-Based Trajectory Planning
Zhihong Cui, Hengyu Liu, Zhangkai Wu +5
Trajectory planning for autonomous driving requires both high-level reasoning and precise low-level control. Large Language Models (LLMs) offer semantic-rich planning capabilities,…
DepTGL: A Parallel Framework for Memory-based TGNN Training with Adaptive Temporal Data Dependency Management
Linfang Chen, Zhen Song, Lei Liu +6
Memory-based Temporal Graph Neural Networks (M-TGNNs) maintain recursively updated node states to capture fine-grained temporal interactions. However, existing distributed framewor…
C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving
Zhihong Cui, Haoran Tang, Tianyi Li +4
Trajectory planning for autonomous driving increasingly leverages large language models (LLMs) for commonsense reasoning, yet LLM outputs are inherently unreliable, posing risks in…
Quantifying Point Contributions: A Lightweight Framework for Efficient and Effective Query-Driven Trajectory Simplification
Yumeng Song, Yu Gu, Tianyi Li +3
As large volumes of trajectory data accumulate, simplifying trajectories to reduce storage and querying costs is increasingly studied. Existing proposals face three main problems.…
UniTE: A Survey and Unified Pipeline for Pre-training Spatiotemporal Trajectory Embeddings
Yan Lin, Zeyu Zhou, Yicheng Liu +8
Spatiotemporal trajectories are sequences of timestamped locations, which enable a variety of analyses that in turn enable important real-world applications. It is common to map tr…