Explanipedia

MUSEKG: A Knowledge Graph Over Museum Collections Open

Jinhao Li, Jianzhong Qi, Soyeon Caren Han · 2025

Digital transformation in the cultural heritage sector has produced vast yet fragmented collections of artefact data. Existing frameworks for museum information systems struggle to integrate heterogeneous metadata, unstructured documents, …

Understanding the Geospatial Reasoning Capabilities of LLMs: A Trajectory Recovery Perspective Open

Thinh Hung Truong, Jey Han Lau, Jianzhong Qi · 2025

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 recovery as a proxy task, which requires models to reconstr…

Approximate Graph Propagation Revisited: Dynamic Parameterized Queries, Tighter Bounds and Dynamic Updates Open

Zhuowei Zhao, Zhuo Zhang, Hanzhi Wang, Junhao Gan, Zhifeng Bao , et al. · 2025

We revisit Approximate Graph Propagation (AGP), a unified framework which captures various graph propagation tasks, such as PageRank, feature propagation in Graph Neural Networks (GNNs), and graph-based Retrieval-Augmented Generation (RAG)…

Generalising Traffic Forecasting to Regions without Traffic Observations Open

Xinyu Su, Majid Sarvi, Feng Liu, Jianzhong Qi · 2025

Traffic forecasting is essential for intelligent transportation systems. Accurate forecasting relies on continuous observations collected by traffic sensors. However, due to high deployment and maintenance costs, not all regions are equipp…

Dynamic Structural Clustering Unleashed: Flexible Similarities, Versatile Updates and for All Parameters Open

Zhuowei Zhao, Junhao Gan, Boyu Ruan, Zhifeng Bao, Jianzhong Qi , et al. · 2025

<span>FlexiReg:</span> Flexible Urban Region Representation Learning Open

Fengze Sun, Yanchuan Chang, Egemen Tanin, Shanika Karunasekera, Jianzhong Qi · 2025

Research on state monitoring and diagnosis models for multi-state systems based on Petri nets Open

H. H. Liu, Jianzhong Qi, Feng Hong, Mingyu Fan · 2025

Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction Open

Zesheng Ye, Chengyi Cai, Ruijiang Dong, Jianzhong Qi, Lei Feng , et al. · 2025

As large-scale pre-trained foundation models continue to expand in size and capability, efficiently adapting them to specific downstream tasks has become increasingly critical. Despite substantial progress, existing adaptation approaches h…

Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts Open

Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu · 2025

Model reprogramming adapts pretrained models to downstream tasks by modifying only the input and output spaces. Visual reprogramming (VR) is one instance for vision tasks that adds a trainable noise pattern (i.e., a visual prompt) to input…

Unseen Fake News Detection Through Casual Debiasing Open

Shuzhi Gong, Richard Sinnott, Jianzhong Qi, Cécile Paris · 2025

Accurate and Regret-Aware Numerical Problem Solver for Tabular Question Answering Open

Yuxiang Wang, Jianzhong Qi, Junhao Gan · 2025

Question answering on free-form tables (a.k.a. TableQA) is a challenging task because of the flexible structure and complex schema of tables. Recent studies use Large Language Models (LLMs) for this task, exploiting their capability in und…

FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning Open

Renqiang Luo, Huafei Huang, Ivan Lee, Chengpei Xu, Jianzhong Qi , et al. · 2025

Recent studies have highlighted significant fairness issues in Graph Transformer (GT) models, particularly against subgroups defined by sensitive features. Additionally, GTs are computationally intensive and memory-demanding, limiting thei…

ACE: A Cardinality Estimator for Set-Valued Queries Open

Yufan Sheng, Xin Cao, Kaiqi Zhao, Yixiang Fang, Jianzhong Qi , et al. · 2025

Cardinality estimation is a fundamental functionality in database systems. Most existing cardinality estimators focus on handling predicates over numeric or categorical data. They have largely omitted an important data type, set-valued dat…

FlexiReg: Flexible Urban Region Representation Learning Open

Fengze Sun, Yanchuan Chang, Egemen Tanin, Shanika Karunasekera, Jianzhong Qi · 2025

The increasing availability of urban data offers new opportunities for learning region representations, which can be used as input to machine learning models for downstream tasks such as check-in or crime prediction. While existing solutio…

Unseen Fake News Detection Through Casual Debiasing Open

Richard Sinnott, Jianzhong Qi · 2025

The widespread dissemination of fake news on social media poses significant risks, necessitating timely and accurate detection. However, existing methods struggle with unseen news due to their reliance on training data from past events and…

SemaSK: Answering Semantics-aware Spatial Keyword Queries with Large Language Models Open

Zhengyu Zhang, Jianzhong Qi, Xin Cao · 2025

Geo-textual objects, i.e., objects with both spatial and textual attributes, such as points-of-interest or web documents with location tags, are prevalent and fuel a range of location-based services. Existing spatial keyword querying metho…

Towards Question Answering over Large Semi-structured Tables Open

Yuxiang Wang, Junhao Gan, Jianzhong Qi · 2025

Table Question Answering (TableQA) attracts strong interests due to the prevalence of web information presented in the form of semi-structured tables. Despite many efforts, TableQA over large tables remains an open challenge. This is becau…

Beyond Seen Data: Improving KBQA Generalization Through Schema-Guided Logical Form Generation Open

Shengxiang Gao, Jey Han Lau, Jianzhong Qi · 2025

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 unseen knowledge base elements at test time,we introduce SG-KB…

CLEAR: Cluster-based Prompt Learning on Heterogeneous Graphs Open

Feiyang Wang, Zhongbao Zhang, Junda Ye, Li Sun, Jianzhong Qi · 2025

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 prompting typically use feature prompts to modify node featur…

K Nearest Neighbor-Guided Trajectory Similarity Learning Open

Yanchuan Chang, Cai Xu, Christian S. Jensen, Jianzhong Qi · 2025

Trajectory similarity is fundamental to many spatio-temporal data mining applications. Recent studies propose deep learning models to approximate conventional trajectory similarity measures, exploiting their fast inference time once traine…

Attribute-based Visual Reprogramming for Vision-Language Models Open

Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu · 2025

Visual reprogramming (VR) reuses pre-trained vision models for downstream image classification tasks by adding trainable noise patterns to inputs. When applied to vision-language models (e.g., CLIP), existing VR approaches follow the same …

Beyond Seen Data: Improving KBQA Generalization Through Schema-Guided Logical Form Generation Open

Shengxiang Gao, Jey Han Lau, Jianzhong Qi · 2025

Research on State Monitoring and Diagnosis Models for Multi-State Systems Based on Petri Nets Open

H. H. Liu, Jianzhong Qi, Feng Hong, Mingyu Fan · 2025

FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning Open

Renqiang Luo, Huafei Huang, Ivan Lee, Chengpei Xu, Jianzhong Qi , et al. · 2024

Recent studies have highlighted significant fairness issues in Graph Transformer (GT) models, particularly against subgroups defined by sensitive features. Additionally, GTs are computationally intensive and memory-demanding, limiting thei…

DualCast: A Model to Disentangle Aperiodic Events from Traffic Series Open

Xinyu Su, Feng Liu, Yanchuan Chang, Egemen Tanin, Majid Sarvi , et al. · 2024

Traffic forecasting is crucial for transportation systems optimisation. Current models minimise the mean forecasting errors, often favouring periodic events prevalent in the training data, while overlooking critical aperiodic ones like tra…

Dynamic Structural Clustering Unleashed: Flexible Similarities, Versatile Updates and for All Parameters Open

Zhuowei Zhao, Junhao Gan, Boyu Ruan, Zhifeng Bao, Jianzhong Qi , et al. · 2024

We study structural clustering on graphs in dynamic scenarios, where the graphs can be updated by arbitrary insertions or deletions of edges/vertices. The goal is to efficiently compute structural clustering results for any clustering para…

Less is More: Unseen Domain Fake News Detection via Causal Propagation Substructures Open

Shuzhi Gong, Richard Sinnott, Jianzhong Qi, Cécile Paris · 2024

The spread of fake news on social media poses significant threats to individuals and society. Text-based and graph-based models have been employed for fake news detection by analysing news content and propagation networks, showing promisin…

Bayesian-guided Label Mapping for Visual Reprogramming Open

Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu · 2024

Visual reprogramming (VR) leverages the intrinsic capabilities of pretrained vision models by adapting their input or output interfaces to solve downstream tasks whose labels (i.e., downstream labels) might be totally different from the la…

Beyond the Commute: Unlocking the Potential of Electric Vehicles as Future Energy Storage Solutions (Vision Paper) Open

Muhammad Aamir Cheema, Hao Wang, Wei Wang, Adel N. Toosi, Egemen Tanin , et al. · 2024

Electric vehicles (EVs) have the potential to serve as energy storage solutions through bidirectional charging technology, which allows them to both draw power from and feed power back into the grid, homes, or other vehicles. This capabili…

Federated Graph Learning for Cross-Domain Recommendation Open

Ziqi Yang, Zhaopeng Peng, Zihui Wang, Jianzhong Qi, Chaochao Chen , et al. · 2024

Cross-domain recommendation (CDR) offers a promising solution to the data sparsity problem by enabling knowledge transfer across source and target domains. However, many recent CDR models overlook crucial issues such as privacy as well as …

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