2 citations · 2 across the 16 of their papers we have counts for
18 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…
Robustness Analysis of Agentic AI to Inconsistent and Incomplete Tool Responses
Jiachen Xu, Torben Bach Pedersen, Zhongming Yao +2
Tool-using agents increasingly rely on external tools to complete multi-step tasks, but tool returns can fail in different ways and require different recovery actions. Existing rob…
VTRQ: Enabling Verifiable Trajectory Range Queries in Hybrid-Storage Blockchains
Zhongming Yao, Junchang Xin, Yumeng Song +7
Due to their increasingly large volumes, outsourcing of trajectory storage and querying to third-party service providers has become attractive. However, in such outsourced environm…
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…
Reliable AI Needs to Externalize Implicit Knowledge: A Human-AI Collaboration Perspective
Hengyu Liu, Tianyi Li, Zhihong Cui +5
This position paper argues that reliable AI requires infrastructure for human validation of implicit knowledge. AI learns from both explicit knowledge (papers, documentation, struc…
AegisTS: A Hierarchical Agentic AI System with Reinforcement Learning for Multivariate Time Series Data Cleaning
Yuhan Shi, Yuanyuan Yao, Lu Chen +3
Multivariate time series (MTS) are frequently affected by co-occurring quality issues, such as missing values, outliers, and constraint violations, which significantly undermine do…
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…
CLEAR: A Knowledge-Centric Vessel Trajectory Analysis Platform
Hengyu Liu, Tianyi Li, Haoyu Wang +5
Vessel trajectory data from the Automatic Identification System (AIS) is used widely in maritime analytics. Yet, analysis is difficult for non-expert users due to the incompletenes…
FEAT: A Linear-Complexity Foundation Model for Extremely Large Structured Data
Zhenghang Song, Tang Qian, Lu Chen +7
Structured data is widely used in domains such as healthcare, finance, and scientific data management. Recent studies on structured data foundation models (SFMs) aim to support dat…
VISTA: Knowledge-Driven Vessel Trajectory Imputation with Repair Provenance
Hengyu Liu, Tianyi Li, Haoyu Wang +4
Repairing incomplete trajectory data is essential for downstream spatio-temporal applications. Yet, existing repair methods focus solely on reconstruction without documenting the r…
TCRL: Temporal-Coupled Adversarial Training for Robust Constrained Reinforcement Learning in Worst-Case Scenarios
Wentao Xu, Zhongming Yao, Weihao Li +4
Constrained Reinforcement Learning (CRL) aims to optimize decision-making policies under constraint conditions, making it highly applicable to safety-critical domains such as auton…
Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detection
Yuanyuan Yao, Yuhan Shi, Lu Chen +5
Multivariate time series (MTS) anomaly detection identifies abnormal patterns where each timestamp contains multiple variables. Existing MTS anomaly detection methods fall into thr…
Advancing Knowledge Tracing by Exploring Follow-up Performance Trends
Hengyu Liu, Yushuai Li, Minghe Yu +6
Intelligent Tutoring Systems (ITS), such as Massive Open Online Courses, offer new opportunities for human learning. At the core of such systems, knowledge tracing (KT) predicts st…
MH-GIN: Multi-scale Heterogeneous Graph-based Imputation Network for AIS Data (Extended Version)
Hengyu Liu, Tianyi Li, Yuqiang He +3
Location-tracking data from the Automatic Identification System, much of which is publicly available, plays a key role in a range of maritime safety and monitoring applications. Ho…
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.…
Digital Twin-Empowered Voltage Control for Power Systems
Jiachen Xu, Yushuai Li, Torben Bach Pedersen +3
Emerging digital twin technology has the potential to revolutionize voltage control in power systems. However, the state-of-the-art digital twin method suffers from low computation…
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…