Full Publications

Google Scholar

Underlined names indicate Ph.D. students in our lab.

Recent Preprints

• From Signals to Semantics: A Survey on Time Series Explainability through a Human-Cognitive Lens
  Zhuomin Chen, Gabriel Lucchesi, Qingkai Dong, Xu Zheng, Dongjin Song, Qingsong Wen, Wei Cheng, Jingchao Ni, Dongsheng Luo
  Preprint, 2026


• Trajectory Graph Copilot: Pre-Action Error Diagnosis in LLM Agents
  Xu Zheng, Zhuomin Chen, Chaohao Lin, Hua Wei, Haifeng Chen, Wei Cheng, Dongsheng Luo
  Preprint, 2025


• L2motifs: An Explainable Framework for Machine-Generated Texts Detection
  Xu Zheng, Zhuomin Chen, Esteban Schafir, Sipeng Chen, Hojat Allah Salehi, Haifeng Chen, Farhad Shirani, Wei Cheng, Dongsheng Luo
  Arxiv, 2025


• SF2Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida
  Xu Zheng, Chaohao Lin, Sipeng Chen, Zhuomin Chen, Jimeng Shi, Wei Cheng, Jayantha Obeysekera, Jason Liu, Dongsheng Luo
  Preprint, 2025


• PAC Learnability under Explanation-Preserving Graph Perturbations
  Xu Zheng, Farhad Shirani, T. Wang, S. Gao, W. Dong, W. Cheng, and Dongsheng Luo
  Arxiv, 2024


• SVTime: Small Time Series Forecasting Models Informed by "Physics" of Large Vision Model Forecasters
  ChengAo Shen, Ziming Zhao, Hanghang Tong, Dongjin Song, Dongsheng Luo, Qingsong Wen, Jingchao Ni
  ArXiv:2510.09780, 2025


• GraphGhost: Tracing Structures Behind Large Language Models
  Xinnan Dai, Xianxuan Long, Chung-Hsiang Lo, Kai Guo, Shenglai Zeng, Dongsheng Luo, Jiliang Tang
  Arxiv, 2025


• Deep Reinforcement Learning for MIMO Communication with Low-Resolution ADCs
  Marian Temprana Alonso, Dongsheng Luo, Farhad Shirani
  Arxiv, 2025


• Spectral GNN via Two-dimensional (2-D) Graph Convolution
  Guoming Li, Jian Yang, Shangsong Liang, and Dongsheng Luo
  arxiv:2404.04559


• Large Language Multimodal Models for 5-Year Chronic Disease Cohort Prediction Using EHR Data
  Jun-En Ding, Phan Nguyen Minh Thao, Wen-Chih Peng, Jian-Zhe Wang, Chun-Cheng Chug, Min-Chen Hsieh, Yun-Chien Tseng, Ling Chen, Dongsheng Luo, Chi-Te Wang, Pei-fu Chen, Feng Liu, Fang-Ming Hung
  arxiv:2403.04785

2026

• Addressing Structural Distribution Shift in Explanations for Graph Neural Networks
  Zhuomin Chen, Hojat Allah Salehi, Esteban Schafir, Xu Zheng, Jiaxing Zhang, Hua Wei, Jingchao Ni, Farhad Shirani, Dongsheng Luo
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026


• Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning
  Zhuomin Chen, Jingchao Ni, Hojat Allah Salehi, Xu Zheng, Esteban Schafir, Farhad Shirani, Dongsheng Luo
  The AAAI Conference on Artificial Intelligence (AAAI), 2026


• MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters
  Aitian Ma, Dongsheng Luo, and Mo Sha
  The International Conference on Learning Representations (ICLR), 2026


• LUMOS: Democratizing SciML Workflows with L0-Regularized Learning for Unified Feature and Parameter Adaptation
  Shouwei Gao, Xu Zheng, Dongsheng Luo, Sheng Di, Wenqian Dong
  The 40th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2026


• KORAL: Knowledge Graph Guided LLM Reasoning for SSD Operational Analysis
  Mayur Akewar, Sandeep Madireddy, Dongsheng Luo, Janki Bhimani
  The 40th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2026


• MMFNet: Multi-Scale Frequency Masking Neural Network for Multivariate Time Series Forecasting
  Aitian Ma, Dongsheng Luo, and Mo Sha
  ACM Symposium On Applied Computing (SAC), 2026


• Enabling Large Language Model based Data Synthesis in Wireless Mesh Network Configuration for Internet of Things
  Aitian Ma, Jean Marco Cruz, Dongsheng Luo, and Mo Sha
  IEEE Computers, Software, and Applications Conference (COMPSAC), 2026


• Configuring Industrial Wireless Mesh Network via Dual-Mind Reasoning
  Aitian Ma, Dongsheng Luo, Ali Maatouk, Rex Ying, and Mo Sha
  IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), 2026


• CURENet: Combining Unified Representations for Efficient Chronic Disease Prediction
  Cong-Tinh Dao, Nguyen Minh Thao Phan, Jun-En Ding, Chenwei Wu, David Restrepo, Dongsheng Luo, Fanyi Zhao, Chun-Chieh Liao, Wen-Chih Peng, Chi-Te Wang, Pei-Fu Chen, Ling Chen, Xinglong Ju, Feng Liu, Fang-Ming Hung
  Expert Systems with Applications, 2026

2025

• F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
  Xu Zheng, Farhad Shirani, Zhuomin Chen, Chaohao Lin, Wei Cheng, Wenbo Guo, Dongsheng Luo
  The International Conference on Learning Representations (ICLR), 2025


• Elevating Spectral GNNs through Enhanced Band-pass Filter Approximation
  Guoming Li, Jian Yang, Shangsong Liang, and Dongsheng Luo
  Proceedings of The Web Conference (WWW), 2025


• Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
  Tiejin Chen, Wenwang Huang, Linsey Pang, Dongsheng Luo, Hua Wei
  ACM SIGKDD Explorations Newsletter, 2025


• Reasoning with Knowledge Graphs for Trustworthy Course Recommendation
  Md Akib Zabed Khan, Dongsheng Luo, Agoritsa Polyzou
  IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA), 2025


• MedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation
  Hsin-Ling Hsu, Cong-Tinh Dao, Luning Wang, Zitao Shuai, Thao Nguyen Minh Phan, Jun-En Ding, Chun-Chieh Liao, Pengfei Hu, Xiaoxue Han, Chih-Ho Hsu, Dongsheng Luo, Wen-Chih Peng, Feng Liu, Fang-Ming Hung, Chenwei Wu
  The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025


• Exploring Multi-Modal Integration with Tool-Augmented LLM Agents for Precise Causal Discovery
  ChengAo Shen, Zhengzhang Chen, Dongsheng Luo, Dongkuan Xu, Haifeng Chen, Jingchao Ni
  The 63rd Annual Meeting of the Association for Computational Linguistics Findings (ACL Findings), 2025


• Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
  Jiaxing Zhang, Xiaoou Liu, Dongsheng Luo, Hua Wei
  Proceedings of the 31st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025


• NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders
  Jun-En Ding, Dongsheng Luo, Anna Zilverstand, Feng Liu
  The International Conference on Machine Learning (ICML), 2025


• Harnessing Vision Models for Time Series Analysis: A Survey
  Jingchao Ni, Ziming Zhao, ChengAo Shen, Hanghang Tong, Dongjin Song, Wei Cheng, Dongsheng Luo, Haifeng Chen
  International Joint Conference on Artificial Intelligence, Survey Track (IJCAI), 2025


• 3DGraphX: Explaining 3D Molecular Graph Models via Incorporating Chemical Priors
  Xufeng Liu, Dongsheng Luo, Wenhan Gao, Yi Liu
  Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025


• Sensorless Air Temperature Sensing Using LoRa Link Characteristics
  Aitian Ma, Jean Tonday Rodriguez, Mo Sha, and Dongsheng Luo
  IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), 2025


• DyExplainer: Self-explainable Dynamic Graph Neural Network with Sparse Attentions
  Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang
  The ACM Transactions on Knowledge Discovery from Data (TKDD), 2025


• Lake Water Temperature Modeling Using Physics-Informed Neural Networks
  Trieu Vo, Cuong Nguyen, Dongsheng Luo, Leonardo Bobadilla
  Tackling Climate Change with Machine Learning Workshop at ICLR 2025


• Adaptive Dice Loss for Extremely Imbalanced Segmentation in Wetland Delineation
  Sipeng Chen, Xu Zheng, Zeda Yin, Qiang Chen, Yuepeng Li, Jason Liu, Dongsheng Luo
  Tackling Climate Change with Machine Learning Workshop at ICLR 2025


• GitTemporalAI: Leveraging Temporal Knowledge Graphs and LLMs for Multi-Agent Repository Intelligence
  Dongsheng Luo, Raju Rangaswami, Amir Rahmati, Erez Zadok
  The First MARW: Multi-Agent AI in the Real World Workshop at AAAI 2025


• LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation
  Jiaxing Zhang, Jiayi Liu, Dongsheng Luo, Jennifer Neville, Hua Wei
  AI Agent for Information Retrieval Workshop at SIGKDD 2025


• Uncovering Graph Reasoning in Decoder-only Transformers with Circuit Tracing
  Xinnan Dai, Chung-Hsiang Lo, Kai Guo, Shenglai Zeng, Dongsheng Luo, Jiliang Tang
  Workshop on Efficient Reasoning at NeurIPS 2025


• ICeTEA: Mixture of Detectors for Metric-Log Anomaly Detection
  Junxiang Wang, Xu Zheng, Zhengzhang Chen, Masanao Natsumeda, Jun Nishioka, Dongsheng Luo, Haifeng Chen
  The 11th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs, 2025

2024

• RegExplainer: Generating Explanations for Graph Neural Networks in Regression Task
  Jiaxing Zhang, Zhuomin Chen, Hao Mei, Dongsheng Luo, Hua Wei
  Proceedings of Neural Information Processing Systems (NeurIPS), 2024


• Rank Supervised Contrastive Learning for Time Series Classification
  Qianying Ren, Dongsheng Luo, Dongjin Song
  Proceedings of IEEE International Conference on Data Mining (ICDM), 2024


• Large Language Multimodal Models for New-Onset Type 2 Diabetes Prediction using Five-Year Cohort Electronic Health Records
  Jun-En Ding, Phan Nguyen Minh Thao, Wen-Chih Peng, Jian-Zhe Wang, Chun-Cheng Chu, Min-Chen Hsieh, Yun-Chien Tseng, Ling Chen, Dongsheng Luo, Chenwei Wu, Chi-Te Wang, Chih-Ho Hsu, Yi-Tui Chen, Pei-Fu Chen, Feng Liu, and Fang-Ming Hung
  Scientific Reports, 2024


• Shape-aware Graph Spectral Learning
  Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang and Suhang Wang
  Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024


• Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling
  Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, and Suhang Wang
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024


• Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks
  Zhuomin Chen, J. Zhang, J. Ni, X. Li, Y. Bian, Md Islam, A. Mondal, H. Wei, and Dongsheng Luo
  The International Conference on Machine Learning (ICML), 2024
  Also Present at WWW Workshop: TrustLOG, 2024
  [html][code]


• TimeX++: Learning Time-Series Explanations with Information Bottleneck
  Zichuan Liu, T. Wang, J. Shi, Xu Zheng, Zhuomin Chen, L. Song, W. Dong, J. Obeysekera, Farhad Shirani and Dongsheng Luo
  The International Conference on Machine Learning (ICML), 2024
  [html][code]


• Parametric Augmentation for Time Series Contrastive Learning
  Xu Zheng, T. Wang, W. Cheng, A. Ma, H. Chen, M. Sha, and Dongsheng Luo
  The International Conference on Learning Representations (ICLR), 2024
  Also Present at IJCAI Workshop: AI4TS, 2023 (Best Paper Award)
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• Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
  Xu Zheng, Farhad Shirani, T. Wang, W. Cheng, Zhuomin Chen, H. Chen, H. Wei, Dongsheng Luo
  The International Conference on Learning Representations (ICLR), 2024
  Also Present at 2nd Workshop on TrustLOG @ WWW, 2024 (Best Paper Award Runner-Up)
  [html][code]


• Explaining Time Series via Contrastive and Locally Sparse Perturbations
  Zichuan Liu, Y. Zhang, T. Wang, Z. Wang, Dongsheng Luo, M. Du, M. Wu, Y. Wang, C. Chen, L. Fan, Qingsong Wen
  The International Conference on Learning Representations (ICLR), 2024


• Towards Inductive and Efficient Explanations for Graph Neural Networks
  Dongsheng Luo, T. Zhao, W. Cheng, D. Xu, F. Han, W. Yu, X. Liu, H. Chen, Xiang Zhang
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
  [html]


• Factorized Explainer for Graph Neural Networks
  Rundong Huang, Farhad Shirani, Dongsheng Luo
  The AAAI Conference on Artificial Intelligence (AAAI), 2024
  [html][poster]


• Breaking the Bot Barrier: Evaluating the Effectiveness of Adversarial AI Techniques Against Multi-Modal Defense Models
  Behzad Ousat, Dongsheng Luo, Amin Kharraz
  Short Paper Track in International World Wide Web Conference (WWW), 2024


• MOGAT: An Improved Multi-Omics Integration Framework Using Graph Attention Networks
  Raihanul Bari Tanvir, Md Mezbahul Islam, Masrur Sobhan, Dongsheng Luo, Ananda Mohan Mondal
  International Journal of Molecular Sciences (IJMS), 2024
  The 15th RECOMB Satellite Workshop on Computational Cancer Biology (RECOMB-CCB), 2023


• Chiseling the Graph: An Edge-Sculpting Method for Explaining Graph Neural Networks
  Tianchun Wang, Farhad Shirani, Xu Zheng, Wei Cheng, Haifeng Chen, Dongsheng Luo, Xiang Zhang
  Preprint, 2024

2023

• MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
  Jiaxing Zhang, Dongsheng Luo, Hua Wei
  Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023


• Time Series Contrastive Learning with Information-Aware Augmentations
  Dongsheng Luo, W. Cheng, Y. Wang, D. Xu, J. Ni, W. Yu, X. Zhang, Y. Liu, Y. Chen, H. Chen, Xiang Zhang
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2023
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• Shedding Light on Random Dropping and Oversmoothing
  Han Xuanyuan, Tianxiang Zhao, and Dongsheng Luo
  NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023


• Random Walk on Multiple Networks
  Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiong Yu, Jun Huan, Xiao Liu, Xiang Zhang
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
  [html][code]


• CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning
  Minghao Lin, Minghao Cheng, Dongsheng Luo, Yueqi Chen
  Workshop on Security of Space and Satellite Systems (SpaceSec@NDSS), 2023


• Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment
  Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
  ACM Transactions on Intelligent Systems and Technology (TIST), 2023


• Unsafe Behavior Detection with Adaptive Contrastive Learning in Industrial Control Systems
  Xu Zheng, Tianchun Wang, Samin Yasar Chowdhury, Ruimin Sun, Dongsheng Luo
  IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), 2023


• Towards Faithful and Consistent Explanations for Graph Neural Networks
  Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
  Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM), 2023


• Self-Explainable Graph Neural Networks for Link Prediction
  Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang
  Arxiv, 2023

2022

• A Collective Approach to Scholar Name Disambiguation
  Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, and Jinpeng Huai
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
  Extend Abstract at IEEE International Conference on Data Engineering (ICDE), 2021
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• Personalized Federated Learning via Heterogeneous Modular Networks
  Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, Xiang Zhang
  IEEE International Conference on Data Mining (ICDM), 2022


• TopoImb: Toward Topology-level Imbalance in Learning from Graphs
  Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
  Learning on Graphs Conference (LOG), 2022

2021 and Before

• Learning to Drop: Robust Graph Neural Network via Topological Denoising
  Dongsheng Luo^E, Wei Cheng^E, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen, Xiang Zhang
  Proceedings of 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021
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• InfoGCL: Information-aware Graph Contrastive Learning
  Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang
  Proceedings of Advances in Neural Information Processing Systems (NeurIPS), 2021


• Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection
  Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang
  Proceedings of the SIAM International Conference on Data Mining (SDM), 2021


• Attentive Social Recommendation: Towards User and Item Diversities
  Dongsheng Luo, Yuchen Bian, Xiang Zhang, Jun Huan
  Workshop of Deep Learning on Graphs: Method and Applications (DLG-AAAI), 2021


• Unsupervised Document Embedding via Contrastive Augmentation
  Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang
  Arxiv, 2021


• Parameterized Explainer for Graph Neural Network
  Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang
  Proceedings of 34th Conference on Neural Information Processing Systems (NeurIPS), 2020
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• Local Community Detection in Multiple Networks
  Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang
  Proceedings of 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020
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• Deep Multi-Graph Clustering via Attentive Cross-Graph Association
  Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu, Xiang Zhang
  Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2020
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• Memory-based Random Walk for Multi-Query Local Community Detection
  Yuchen Bian, Dongsheng Luo, Yaowei Yan, Wei Cheng, Wei Wang, and Xiang Zhang
  Knowledge and Information Systems (KAIS), 2020


• Adaptive Neural Network for Node Classification in Dynamic Networks
  Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, Xiang Zhang
  IEEE International Conference on Data Mining (ICDM), 2019


• Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs
  Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiang Zhang
  International Joint Conference on Artificial Intelligence (IJCAI), 2019


• Constrained Local Graph Clustering by Colored Random Walk
  Yaowei Yan, Yuchen Bian, Dongsheng Luo, Dongwon Lee, Xiang Zhang
  The Web Conference (WWW), 2019


• On Multi-Query Local Community Detection
  Yuchen Bian, Yaowei Yan, Wei Cheng, Wei Wang, Dongsheng Luo, Xiang Zhang
  IEEE International Conference on Data Mining (ICDM), 2018


• Query Independent Scholarly Article Ranking
  Shuai Ma, Chen Gong, Renjun Hu, Dongsheng Luo, Chunming Hu, Jinpeng Huai
  IEEE 34th International Conference on Data Engineering (ICDE), 2018


• Local Graph Clustering by Multi-Network Random Walk with Restart
  Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Yu, John Yen, Xiang Zhang
  Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018


• Ensemble Enabled Weighted PageRank
  Dongsheng Luo, Chen Gong, Renjun Hu, Liang Duan, and Shuai Ma
  The WSDM Cup 2016 - Entity Ranking Challenge (WSDM CUP), 2016