1 citations · 2 across the 12 of their papers we have counts for
12 papers
GPSBench: Do Large Language Models Understand GPS Coordinates?
Thinh Hung Truong, Jey Han Lau, Jianzhong Qi
Large Language Models (LLMs) are increasingly deployed in applications that interact with the physical world, such as navigation, robotics, or mapping, making robust geospatial rea…
UrbanVerse: Learning Urban Region Representation Across Cities and Tasks
Fengze Sun, Egemen Tanin, Shanika Karunasekera +3
Recent advances in urban region representation learning have enabled a wide range of applications in urban analytics, yet existing methods remain limited in their capabilities to g…
ML-ECS: Heterogeneity-Aware Collaborative Multimodal Learning for Edge-Cloud Synergies
Yuze Liu, Shibo Chu, Tiehua Zhang +5
Edge-cloud synergies provide a promising paradigm for privacy-preserving deployment of foundation models in heterogeneous web environments, enabling lightweight edge models to supp…
MUSEKG: A Knowledge Graph Over Museum Collections
Jinhao Li, Jianzhong Qi, Soyeon Caren Han +1
Digitisation in the cultural heritage sector has produced large but fragmented repositories of museum collection data, spanning structured catalogue records, images, and unstructur…
rareboost3d: a synthetic lidar dataset with enhanced rare classes
Shutong Lin, Zhengkang Xiang, Jianzhong Qi +1
Real-world point cloud datasets have made significant contributions to the development of LiDAR-based perception technologies, such as object segmentation for autonomous driving. H…
Understanding the Geospatial Reasoning Capabilities of LLMs: A Trajectory Recovery Perspective
Thinh Hung Truong, Jey Han Lau, Jianzhong Qi
We explore the geospatial reasoning capabilities of Large Language Models (LLMs), specifically, whether LLMs can read road network maps and perform navigation. We frame trajectory…
Synthesizing Tabular Data Using Selectivity Enhanced Generative Adversarial Networks
Youran Zhou, Jianzhong Qi
As E-commerce platforms face surging transactions during major shopping events like Black Friday, stress testing with synthesized data is crucial for resource planning. Most recent…
CLEAR: Cluster-based Prompt Learning on Heterogeneous Graphs
Feiyang Wang, Zhongbao Zhang, Junda Ye +2
Prompt learning has attracted increasing attention in the graph domain as a means to bridge the gap between pretext and downstream tasks. Existing studies on heterogeneous graph pr…
Beyond Seen Data: Improving KBQA Generalization Through Schema-Guided Logical Form Generation
Shengxiang Gao, Jey Han Lau, Jianzhong Qi
Knowledge base question answering (KBQA) aims to answer user questions in natural language using rich human knowledge stored in large KBs. As current KBQA methods struggle with uns…
FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning
Renqiang Luo, Huafei Huang, Ivan Lee +3
Recent studies have highlighted significant fairness issues in Graph Transformer (GT) models, particularly against subgroups defined by sensitive features. Additionally, GTs are co…
Learned Indexes with Distribution Smoothing via Virtual Points
Kasun Amarasinghe, Farhana Choudhury, Jianzhong Qi +1
Recent research on learned indexes has created a new perspective for indexes as models that map keys to their respective storage locations. These learned indexes are created to app…
Factual Dialogue Summarization via Learning from Large Language Models
Rongxin Zhu, Jey Han Lau, Jianzhong Qi
Factual consistency is an important quality in dialogue summarization. Large language model (LLM)-based automatic text summarization models generate more factually consistent summa…