Publications

2025

Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language
Zhiqiang Zhong, Simon Sataa-Yu Larsen, Haoyu Guo, Tao Tang, Kuangyu Zhou, Davide Mottin.
The Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL’25) [Paper] [Code]

Exploring Graph Structure Comprehension Ability of Multimodal Large Language Models: Case Studies
Zhiqiang Zhong, Davide Mottin.
Learning on Graphs Conference (LoG’24) [Paper] [Code]
Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding
Zhiqiang Zhong, Davide Mottin.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’24) [Paper] [Code]
Harnessing Large Language Models as Post-hoc Correctors
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin.
The Annual Meeting of the Association for Computational Linguistics (ACL’24) [Paper] [Code]
Benchmarking Large Language Models for Molecule Prediction Tasks.
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin.
Preprint on arxiv [Paper] [Code]
Hierarchical Bipartite Graph Convolutional Network for Recommendation
Yi Wei Cheng, Zhiqiang Zhong, Jun Pang, Cheng-Te Li.
IEEE Computational Intelligence Magazine (CIM) [Paper] [Code]
Bridging Performance of X (formerly known as Twitter) Users: A Predictor of Subjective Well-Being During the Pandemic
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang.
ACM Transactions on the Web [Paper] [Code]
A tale of two roles: exploring topic-specific susceptibility and influence in cascade prediction
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
Journal of Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD [Paper]

On the Robustness of Post-hoc GNN Explainers to Label Noise.
Zhiqiang Zhong, Yangqianzi Jiang, Davide Mottin
Learning on Graphs Conference (LoG’23) [Paper] [Code]
How Faithful are Self-Explainable GNNs?
Marc Christiansen, Lea Villadsen, Zhiqiang Zhong, Stefano Teso, Davide Mottin.
Learning on Graphs Conference (LoG’23) [Paper] [Code]
Tutorial: Knowledge-augmented Graph Machine Learning for Drug Discovery: From Precision to Interpretability
Zhiqiang Zhong, Davide Mottin
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’23) [Paper] [Web Page]
Multi-grained Semantics-aware Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
IEEE Transactions on Knowledge and Data Engineering (TKDE) [Paper] [Code]
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability
Zhiqiang Zhong, Anastasia Barkova, Davide Mottin
Preprint on arxiv [Paper] [GitHub Page]
Hierarchical Message-Passing Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
Journal of Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD [Paper] [Code]

Unsupervised Network Embedding Beyond Homophily
Zhiqiang Zhong, Guadalupe Gonzalez, Daniele Grattarola, Jun Pang
Transactions on Machine Learning Research (TMLR) [Paper] [Code]
Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation
Zhiqiang Zhong, Sergey Ivanov, Jun Pang
Transactions on Machine Learning Research (TMLR) [Paper] [Code]
The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users during the COVID-19 Pandemic
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’22) [Paper]
Leveraging Graph Machine Learning for Social Network Analysis
Zhiqiang Zhong
PhD. Degree Thesis Published at orbilu.uni.lu [Paper]
Personalised Meta-path Generation for Heterogeneous Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
Journal of Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD [Paper [Code]
Exploring Spillover Effects for COVID-19 Cascade Prediction
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
Journal of Entropy [Paper]

From #Jobsearch to #Mask: Improving COVID-19 Cascade Prediction with Spillover Effects
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
ACM/IEEE International Conference on Social Network Analysis and Mining (ASONAM’21) [Paper]
An Exploratory Study of COVID-19 Information on Twitter in the Greater Region
Ninghan Chen, Zhiqiang Zhong, Jun Pang
Journal of Big Data and Cognitive Computing [Paper]

NeuLP: An End-to-end Deep-learning Model for Link Prediction
Zhiqiang Zhong, Yang Zhang, Jun Pang
In Proceedings of the 21th International Conference on Web Information Systems Engineering (WISE’20) [Paper] [Code]

A Graph-based Approach to Explore Relationship between Hashtags and Images
Zhiqiang Zhong, Yang Zhang, Jun Pang
In Proceedings of the 20th International Conference on Web Information Systems Engineering (WISE’19) [Paper]