Publications

In chronological order | Google Scholar | DBLP

Conference Papers

2025
• [C120] Can LLMs Beat Humans on Discerning Human-written and LLM-generated Science News? by D. Soós, M. Jiang, J. Wu. ACM Conference on Hypertext and Social Media (HT), 2025.
• [C119] CodeTaxo: Enhancing Taxonomy Expansion with Limited Examples via Code Language Prompts by Q. Zeng, Y. Bai, Z. Tan, Z. Wu, S. Feng, M. Jiang. Findings of Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C118] QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation by B. Nguyen, T. Du, M. Yu, L. Angrave, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C117] Optimizing Decomposition for Optimal Claim Verification by Y. Lu, N. Ziems, H. Dang, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C116] Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models by Z. Liu, G. Dou, X. Yuan, C. Zhang, Z. Tan, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C115] Disentangling Biased Knowledge from Reasoning in Large Language Models via Machine Unlearning by Z. Liu, S. Maharjan, F. Wu, R. Parikh, B. Bayar, S. Sengamedu, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C114] Aligning Large Language Models with Implicit Preferences from User-Generated Content by Z. Tan, Z. Li, T. Liu, H. Wang, H. Yun, M. Zeng, P. Chen, Z. Zhang, Y. Gao, R. Wang, P. Nigam, B. Yin, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C113] Enhancing Mathematical Reasoning in LLMs by Stepwise Correction by Z. Wu, Q. Zeng, Z. Zhang, Z. Tan, C. Shen, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C112] UniConv: Unifying Retrieval and Response Generation for Large Language Model in Conversation by F. Mo, Y. Gao, C. Meng, X. Liu, Z. Wu, K. Mao, Z. Wang, P. Chen, Z. Li, X. Li, B. Yin, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C111] Cross-Lingual Pitfalls: Automatic Probing Cross-Lingual Weakness of Multilingual Large Language Models by Z. Xu, Y. Wang, Y. Huang, X. Chen, J. Zhao, M. Jiang, X. Zhang. Annual Meetings of the Association for Computational Linguistics (ACL), 2025.
• [C110] Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Experts by G. Xu, Y. Duan, Z. Liu, X. Li, M. Jiang, M. Lemmon, W. Jin, Y. Shi. Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.
• [C109] Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench by Z. Liu, G. Dou, M. Jia, Z. Tan, Q. Zeng, Y. Yuan, M. Jiang. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025. [DOI]
• [C108] IHEval: Evaluating Language Models on Following the Instruction Hierarchy by Z. Zhang, S. Li, Z. Zhang, X. Liu, H. Jiang, X. Tang, Y. Gao, Z. Li, H. Wang, Z. Tan, Y. Li, Q. Yin, B. Yin, M. Jiang. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025. [DOI]
• [C107] MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problems by Z. Zhu, M. Jia, Z. Zhang, L. Li, M. Jiang. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025. [DOI]
• [C106] Benchmarking Language Model Creativity: A Case Study on Code Generation by Y. Lu, D. Wang, T. Li, D. Jiang, S. Khudanpur, M. Jiang, D. Khashabi. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025. [DOI]
• [C105] Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning by G. Liu, M. Sun, W. Matusik, M. Jiang, J. Chen. International Conference on Learning Representations (ICLR), 2025.
• [C104] Learning Molecular Representation in a Cell by G. Liu, S. Seal, J. Arevalo, Z. Liang, A. Carpenter, M. Jiang, S. Singh. International Conference on Learning Representations (ICLR), 2025.
• [C103] Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasks by A. Szymanski, N. Ziems, T. Li, M. Jiang, R. Metoyer. ACM Conference on Intelligent User Interfaces (IUI), 2025. [DOI]
• [C102] Learning Attribute as Explicit Relation for Sequential Recommendation by G. Liu, F. Yang, Y. Jiao, A.B. Garakani, T. Tong, Y. Gao, M. Jiang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2025. [DOI]
2024
• [C101] Motif-aware Attribute Masking for Molecular Graph Pre-training by E. Inae, G. Liu, M. Jiang. Learning on Graphs Conference (LoG), 2024.
• [C100] ShopBench: A Massive Multi-Task Online Shopping Benchmark for Large Language Models by Y. Jin, and many others including M. Jiang. Conference on Neural Information Processing Systems (NeurIPS), 2024. (Dataset and Benchmark track)
• [C99] Graph Diffusion Transformer for Multi-Conditional Molecular Generation by G. Liu, J. Xu, T. Luo, M. Jiang. Conference on Neural Information Processing Systems (NeurIPS), 2024. (Oral) [project]
• [C98] Large Language Models Can Self-Correct with Key Condition Verification by Z. Wu, Q. Zeng, Z. Zhang, Z. Tan, C. Shen, M. Jiang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [DOI]
• [C97] Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts by Z. Tan, Z. Liu, M. Jiang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [DOI]
• [C96] Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning by Z. Tan, Q. Zeng, Y. Tian, Z. Liu, B. Yin, M. Jiang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [DOI]
• [C95] Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning by Z. Zhang, T. Ge, Z. Liang, W. Yu, D. Yu, M. Jia, D. Yu, M. Jiang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [DOI]
• [C94] RAt: Injecting Implicit Bias for Text-To-Image Prompt Refinement Models by Z. Kou, S. Pei, M. Jiang, X. Zhang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [DOI]
• [C93] Reference-based Metrics Disprove Themselves in Question Generation by B. Nguyen, M. Yu, Y. Huang, M. Jiang. Findings of Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [DOI]
• [C92] TOWER: Tree Organized Weighting for Evaluating Complex Instructions by N. Ziems, Z. Zhang, M. Jiang. Findings of Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [DOI]
• [C91] Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples by Q. Zeng, Y. Bai, Z. Tan, S. Feng, Z. Liang, Z. Zhang, M. Jiang. ACM International Conference on Information and Knowledge Management (CIKM), 2024. [DOI]
• [C90] FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition by Z. Kou, Y. Tian, M. Jiang, X. Zhang. ACM International Conference on Information and Knowledge Management (CIKM), 2024. [DOI]
• [C89] PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning by Z. Zhang, D. Lee, Y. Fang, W. Yu, M. Jia, M. Jiang. Annual Meetings of the Association for Computational Linguistics (ACL), 2024. [DOI]
• [C88] Towards Safer Large Language Models through Machine Unlearning by Z. Liu, G. Dou, Z. Tan, Y. Tian, M. Jiang. Findings of Annual Meetings of the Association for Computational Linguistics (ACL), 2024. [DOI]
• [C87] TrustLLM: Trustworthiness in Large Language Models by L. Sun, and many others including M. Jiang. International Conference on Machine Learning (ICML), 2024. (Position paper)
• [C86] Enabling On-Device Self-Supervised LLM Personalization with Selective Synthetic Data by R. Qin, J. Xia, Z. Jia, M. Jiang, A. Abbasi, P. Zhou, J. Hu, Y. Shi. Design Automation Conference (DAC), 2024.
• [C85] Instructing Large Language Models to Identify and Ignore Irrelevant Conditions by Z. Wu, M. Jiang, C. Shen. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024. [DOI] [project]
• [C84] OpenFMNav: Towards Open-Set Zero-Shot Object Navigation via Vision-Language Foundation Models by Y. Kuang, H. Lin, M. Jiang. Findings of Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024. [DOI] [project]
• [C83] Get an A in Math: Progressive Rectification Prompting by Z. Wu, M. Jiang, C. Shen. AAAI Conference on Artificial Intelligence (AAAI), 2024. [DOI] [project]
2023
• [C82] Pre-training Language Models for Comparative Reasoning by M. Yu, Z. Zhang, W. Yu, M. Jiang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023. [DOI]
• [C81] IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions by W. Yu, M. Jiang, P. Clark, A. Sabharwal. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023. [DOI]
• [C80] Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models by Z. Zhang, S. Wang, W. Yu, Y. Xu, D. Iter, Q. Zeng, Y. Liu, C. Zhu, M. Jiang. Findings of Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023. [DOI]
• [C79] Data-Centric Learning from Unlabeled Graphs with Diffusion Model by G. Liu, E. Inae, T. Zhao, J. Xu, T. Luo, M. Jiang. Conference on Neural Information Processing Systems (NeurIPS), 2023.
• [C78] Semi-Supervised Graph Imbalanced Regression by G. Liu, T. Zhao, E. Inae, T. Luo, M. Jiang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023. [DOI]
• [C77] Large Language Models are Built-in Autoregressive Search Engines by N. Ziems, W. Yu, Z. Zhang, M. Jiang. Findings of Annual Meeting of the Association for Computational Linguistics (ACL), 2023. [DOI]
• [C76] Explaining AI-informed Network Intrusion Detection with Counterfactuals by G. Liu, M. Jiang. IEEE International Conference on Computer Communications (INFOCOM), 2023. [DOI]
• [C75] Generate rather than Retrieve: Large Language Models are Strong Context Generators by W. Yu, D. Iter, S. Wang, Y. Xu, M. Ju, S. Sanyal, C. Zhu, M. Zeng, M. Jiang. International Conference on Learning Representations (ICLR), 2023.
• [C74] A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods by Z. Zhang, W. Yu, M. Yu, Z. Guo, M. Jiang. Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2023. [DOI]
2022
• [C73] AutoGDA: Automated Graph Data Augmentation for Node Classification by T. Zhao, X. Tang, D. Zhang, H. Jiang, N. Rao, Y. Song, P. Agrawal, K. Subbian, B. Yin, M. Jiang. Learning on Graphs Conference (LoG), 2022.
• [C72] A Unified Encoder-Decoder Framework with Entity Memory by Z. Zhang, W. Yu, C. Zhu, M. Jiang. Empirical Methods on Natural Language Processing (EMNLP), 2022. [DOI]
• [C71] Retrieval Augmentation for Commonsense Reasoning: A Unified Approach by W. Yu, C. Zhu, Z. Zhang, S. Wang, Z. Zhang, Y. Fang, M. Jiang. Empirical Methods on Natural Language Processing (EMNLP), 2022. [DOI]
• [C70] Graph Rationalization with Environment-based Augmentations by G. Liu, T. Zhao, J. Xu, T. Luo, M. Jiang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022. [DOI]
• [C69] Automatic Controllable Product Copywriting for E-Commerce by X. Guo, Q. Zeng, M. Jiang, X. Yun, B. Long, L. Wu. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022. [DOI]
• [C68] Learning from Counterfactual Links for Link Prediction by T. Zhao, G. Liu, D. Wang, W. Yu, M. Jiang. International Conference on Machine Learning (ICML), 2022. [slides]
• [C67] Hardware/Software Co-Exploration for Graph Neural Architectures on FPGAs by Q. Lu, W. Jiang, M. Jiang, J. Hu, Y. Shi. IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2022. [DOI]
• [C66] A Bottom-Up End-User Intelligent Assistant Approach to Empower Gig Workers against AI Inequality by T. Li, Y. Lu, J. Clark, M. Chen, V. Cox, M. Jiang, Y. Yang, T. Kay, D. Wood, J. Brockman. Symposium on Human-Computer Interaction for Work (CHIWORK), 2022. [DOI]
• [C65] Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts by W. Yu, C. Zhu, L. Qin, T. Zhao, M. Jiang. Findings of Annual Meeting of the Association for Computational Linguistics (ACL), 2022. [DOI]
• [C64] Dict-BERT: Enhancing Language Model Pre-training with Dictionary by W. Yu, C. Zhu, Y. Fang, D. Yu, S. Wang, Y. Xu, M. Zeng, M. Jiang. Findings of Annual Meeting of the Association for Computational Linguistics (ACL), 2022. [DOI]
2021
• [C63] Multi-Round Parsing-based Multiword Rules for Scientific OpenIE by J. Kuebler, L. Tong, M. Jiang. International Conference on Big Knowledge (ICBK), 2021.
• [C62] Dynamic Attributed Graph Prediction with Conditional Normalizing Flows by D. Wang, T. Zhao, N.V. Chawla, M. Jiang. International Conference on Data Mining (ICDM), 2021. [DOI]
• [C61] Sentence-Permuted Paragraph Generation by W. Yu, C. Zhu, T. Zhao, Z. Guo, M. Jiang. Empirical Methods on Natural Language Processing (EMNLP), 2021. [DOI]
• [C60] Injecting Entity Types into Entity-Guided News Generation by X. Dong*, W. Yu*, C. Zhu, M. Jiang. Empirical Methods on Natural Language Processing (EMNLP), 2021. [DOI]
• [C59] Action Sequence Augmentation for Early Graph-based Anomaly Detection by T. Zhao, B. Ni, W. Yu, Z. Guo, N. Shah, M. Jiang. ACM International Conference on Information and Knowledge Management (CIKM), 2021. [DOI]
• [C58] Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations by Q. Zeng, J. Lin, W. Yu, J. Cleland-Huang, M. Jiang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021. [DOI]
• [C57] Cross-Network Learning with Partially Aligned Graph Convolutional Networks by M. Jiang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021. [DOI]
• [C56] Technical Question Answering across Tasks and Domains by W. Yu, L. Wu, Q. Zeng, Y. Deng, R. Mahindru, S. Guven, M. Jiang. Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HTL), 2021. [DOI]
• [C55] Enhancing Factual Consistency of Abstractive Summarization by C. Zhu, W. Hinthorn, R. Xu, Q. Zeng, M. Zeng, X. Huang, M. Jiang. Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT), 2021. [DOI]
• [C54] TCN: Table Convolutional Network for Web Table Interpretation by D. Wang, P. Shiralkar, C. Lockard, B. Huang, X.L. Dong, M. Jiang. The Web Conference (TheWebConf), 2021. [DOI]
• [C53] Few-Shot Graph Learning for Molecular Property Prediction by Z. Guo, C. Zhang, W. Yu, J. Herr, O. Wiest, M. Jiang, N.V. Chawla. The Web Conference (TheWebConf), 2021. [DOI]
• [C52] Traceability Transformed: Generating More Accurate Links with Pre-Trained BERT Models by J. Lin, Y. Liu, Q. Zeng, M. Jiang, J. Huang. International Conference on Software Engineering (ICSE), 2021. (ACM SIGSOFT Distinguished Paper Award) [DOI]
• [C51] Data Augmentation for Graph Neural Networks by T. Zhao, Y. Liu, L. Neves, O. Woodford, M. Jiang, N. Shah. AAAI Conference on Artificial Intelligence (AAAI), 2021. [DOI]
2020
• [C50] Imputing Growth Snapshot Similarity in Early Childhood Development: A Tensor Decomposition Approach by J. Schnur, R. Karl, A. Garcia-Martinez, M. Jiang, N.V. Chawla. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2020. [DOI]
• [C49] Use of Internal Knowledge: Biomedical Literature Search Liberated From External Resources by T. Jiang, N. Zhang, M. Liu, M. Jiang, T. Liu, B. Qin. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2020. [DOI]
• [C48] Overcoming Data Sparsity in Predicting User Characteristics from Behavior through Graph Embeddings by M. Syed, D. Wang, M. Jiang, O. Conway, V. Juneja, S. Subramanian, N.V. Chawla. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2020. [DOI]
• [C47] A Technical Question Answering System with Transfer Learning by W. Yu, L. Wu, Y. Deng, R. Mahindru, Q. Zeng, S. Guven, M. Jiang. Findings of Empirical Methods on Natural Language Processing (EMNLP), 2020. [DOI]
• [C46] Tri-Train: Automatic Pre-fine Tuning between Pre-training and Fine-tune Training for SciNER by Q. Zeng, W. Yu, M. Yu, T. Jiang, T. Weninger, M. Jiang. Findings of Empirical Methods on Natural Language Processing (EMNLP), 2020. [DOI]
• [C45] Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases by C. Zhang, L. Yu, M. Saebi, M. Jiang, N. Chawla. Findings of Empirical Methods on Natural Language Processing (EMNLP), 2020. [DOI]
• [C44] GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction by Z. Guo, W. Yu, C. Zhang, M. Jiang, N. Chawla. ACM International Conference on Information and Knowledge Management (CIKM), 2020. [DOI]
• [C43] Error-bounded Graph Anomaly Loss for GNNs by T. Zhao, C. Deng, K. Yu, T. Jiang, D. Wang, M. Jiang. ACM International Conference on Information and Knowledge Management (CIKM), 2020. [DOI]
• [C42] Towards Semantically Guided Traceability by Y. Liu, J. Lin, Q. Zeng, M. Jiang, J. Cleland-Huang. IEEE International Requirements Engineering Conference (RE), 2020. [DOI]
• [C41] Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors by D. Wang, M. Jiang, M. Syed, O. Conway, V. Juneja, S. Subramanian, N. Chawla. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020. [DOI]
• [C40] Crossing Variational Autoencoders for Answer Retrieval by W. Yu, L. Wu, Q. Zeng, S. Tao, Y. Deng, M. Jiang. Annual Meeting of the Association for Computational Linguistics (ACL), 2020. [DOI]
• [C39] Improving Situational Awareness with Collective Artificial Intelligence over Knowledge Graphs by M. Jiang. Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II in SPIE Defense + Commercial Sensing Symposium, 2020. [DOI]
• [C38] Identifying Referential Intention with Heterogeneous Contexts by W. Yu, M. Yu, T. Zhao, M. Jiang. The Web Conference (TheWebConf), 2020. [DOI]
• [C37] Experimental Evidence Extraction in Data Science with Hybrid Table Features and Ensemble Learning by W. Yu, W. Peng, Y. Shu, Q. Zeng, M. Jiang. The Web Conference (TheWebConf), 2020. [DOI]
• [C36] Multi-label Patent Categorization with Non-local Attention-based Graph Convolutional Network by P. Tang, M. Jiang, N. Xia, J. Pitera, J. Welser, N. Chawla. AAAI Conference on Artificial Intelligence (AAAI), 2020. [DOI]
• [C35] Few-Shot Knowledge Graph Completion by C. Zhang, H. Yao, M. Jiang, Z. Li, N. Chawla. AAAI Conference on Artificial Intelligence (AAAI), 2020. [DOI]
• [C34] Graph Few-shot Learning via Knowledge Transfer by H. Yao, C. Zhang, Y. Wei, M. Jiang, S. Wang, N. Chawla, Z. Li. AAAI Conference on Artificial Intelligence (AAAI), 2020. [DOI]
2019
• [C33] Preserving Composition and Crystal Structure Information of Chemical Compounds in Atomic Embedding by Y. Ding, D. Wang, T. Weninger, M. Jiang. IEEE International Conference on Big Data (BigData), 2019. [DOI]
• [C32] CTGA: Graph-based Biomedical Literature Search by T. Jiang, Z. Zhang, T. Zhao, B. Qin, T. Liu, N. Chawla, M. Jiang. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019. [DOI]
• [C31] Multi-input Multi-output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text by T. Jiang, T. Zhao, B. Qin, T. Liu, N. Chawla, M. Jiang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019. [DOI]
• [C30] MSU-Net: Multiscale Statistical U-Net forReal-time 3D Cardiac MRI Video Segmentation by T. Wang, X. Xu, J. Xiong, M. Jiang, Y. Shi. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. [DOI]
• [C29] The Role of 'Condition': A Novel Scientific Knowledge Graph Representation and Construction Model by T. Jiang, T. Zhao, B. Qin, T. Liu, N. Chawla, M. Jiang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019. [DOI]
• [C28] TUBE: Embedding Behavior Outcomes for Predicting Success by D. Wang, T. Jiang, N. Chawla, M. Jiang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019. [DOI]
• [C27] Tablepedia: Automating PDF Table Reading in an Experimental Evidence Exploration and Analytic System by W. Yu, Z. Li, Q. Zeng, M. Jiang. The Web Conference (TheWebConf), 2019. [DOI]
• [C26] A Novel Unsupervised Approach for Precise Temporal Slot Filling from Incomplete and Noisy Temporal Contexts by X. Wang, H. Zhang, Q. Li, Y. Shi, M. Jiang. The Web Conference (TheWebConf), 2019. [DOI]
2018
• [C25] Actionable Objective Optimization for Suspicious Behavior Detection on Large Bipartite Graphs by T. Zhao, M. Malir, M. Jiang. IEEE International Conference on Big Data (BigData), 2018. [DOI]
• [C24] Doc2Cube: Allocating Documents to Text Cube without Labeled Data by F. Tao, C. Zhang, X. Chen, M. Jiang, T. Hanratty, L. Kaplan, J. Han. IEEE International Conference on Data Mining (ICDM), 2018. [DOI]
• [C23] Optimizing Boiler Control in Real-Time with Machine Learning for Sustainability by Y. Ding, J. Liu, J. Xiong, M. Jiang, Y. Shi. ACM International Conference on Information and Knowledge Management (CIKM), 2018. [DOI]
• [C22] CausalTriad: Toward Pseudo Causal Relation Discovery and Hypotheses Generation from Medical Text Data by S. Zhao, M. Jiang, M. Liu, B. Qin, T. Liu. ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB), 2018. [DOI]
• [C21] A Project Showcase for Planning Research Work towards Publishable Success by D. Wang, M. Jiang, X. Wang, T. Zhao, Q. Zeng, N.V. Chawla. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018. [DOI]
• [C20] TaxoGen: Constructing Topical Concept Taxonomy by Adaptive Term Embedding and Clustering by C. Zhang, F. Tao, X. Chen, J. Shen, M. Jiang, B. Sadler, M. Vanni, J. Han. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018. [DOI]
• [C19] TruePIE: Discovering Reliable Patterns in Pattern-Based Information Extraction by M. Jiang*, Q. Li*, X. Zhang, M. Qu, T. Hanratty, J. Gao, J. Han. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018. (* for equal contribution) [DOI]
• [C18] Multi-Type Itemset Embedding for Learning Behavior Success by D. Wang, M. Jiang, Q. Zeng, Z. Eberhart, N.V. Chawla. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018. [DOI]
2017
• [C17] LifeNet: A Structured Network-Based Knowledge Exploration and Analytics System for Life Sciences by X. Ren, J. Shen, M. Qu, X. Wang, Z. Wu, Q. Zhu, M. Jiang, F. Tao, S. Sinha, D. Liem, P. Ping, R. Weinshilboum, J. Han. Annual Meeting of the Association for Computational Linguistics (ACL), 2017.
• [C16] MetaPAD: Meta Patten Discovery from Massive Text Corpora by M. Jiang, J. Shang, T. Cassidy, X. Ren, L. Kaplan, T. Hanratty, J. Han. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. [DOI]
• [C15] Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing by K. Kuang, P. Cui, B. Li, M. Jiang, S. Yang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. [DOI]
• [C14] ContextCare: Incorporating Contextual Information Networks to Representation Learning in Medical Forum Data by S. Zhao, M. Jiang, Q. Yuan, B. Qin, T. Liu, C.X. Zhai. International Joint Conference on Artificial Intelligence (IJCAI), 2017. [DOI]
• [C13] Treatment Effect Estimation with Data-Driven Variable Decomposition by K. Kuang, P. Cui, B. Li, M. Jiang, S. Yang, F. Wang. AAAI Conference on Artificial Intelligence (AAAI), 2017.
2016
• [C12] Steering Social Media Promotions with Effective Strategies by K. Kuang, M. Jiang, P. Cui, S. Yang. IEEE International Conference on Data Mining (ICDM), 2016. [DOI]
• [C11] Large-Scale Embedding Learning in Heterogeneous Event Data by H. Gui, J. Liu, F. Tao, M. Jiang, B. Norick, J. Han. IEEE International Conference on Data Mining (ICDM), 2016. [DOI]
• [C10] CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors by M. Jiang, C. Faloutsos, J. Han. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016. [DOI]
• [C9] Little is Much: Bridging Cross-Platform Behaviors through Overlapped Crowds by M. Jiang, P. Cui, N. J. Yuan, X. Xie, S. Yang. AAAI Conference on Artificial Intelligence (AAAI), 2016. [DOI]
2010-2015
• [C8] A General Suspiciousness Metric for Dense Blocks in Multimodal Data by M. Jiang, A. Beutel, P. Cui, B. Hooi, S. Yang, C. Faloutsos. IEEE International Conference on Data Mining (ICDM), 2015. [DOI]
• [C7] FEMA: Flexible Evolutionary Multi-Faceted Analysis for Dynamic Behavioral Pattern Discovery by M. Jiang, P. Cui, F. Wang, X. Xu, W. Zhu, S. Yang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2014. [DOI]
• [C6] CatchSync: Catching Synchronized Behavior in Large Directed Graphs by M. Jiang, P. Cui, A. Beutel, C. Faloutsos, S. Yang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2014. (Best Paper Finalist) [DOI]
• [C5] Inferring Strange Behavior from Connectivity Pattern in Social Networks by M. Jiang, P. Cui, A. Beutel, C. Faloutsos, S. Yang. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2014. [DOI]
• [C4] Detecting Suspicious Following Behavior in Multimillion-Node Social Networks by M. Jiang, P. Cui, A. Beutel, C. Faloutsos, S. Yang. International Conference on World Wide Web (WWW), 2014. [DOI]
• [C3] Social Recommendation across Multiple Relational Domains by M. Jiang, P. Cui, F. Wang, Q. Yang, W. Zhu, S. Yang. ACM International Conference on Information and Knowledge Management (CIKM), 2012. [DOI]
• [C2] Social Contextual Recommendation by M. Jiang, P. Cui, R. Liu, Q. Yang, F. Wang, W. Zhu, S. Yang. ACM International Conference on Information and Knowledge Management (CIKM), 2012. [DOI]
• [C1] Mining Topic-Level Influence in Heterogeneous Networks by L. Liu, J. Tang, J. Han, M. Jiang, S. Yang. ACM International Conference on Information and Knowledge Management (CIKM), 2010. [DOI]

Journal Papers

2025
• [J45] Leopard: A Vision Language Model for Text-Rich Multi-Image Tasks by M. Jia, W. Yu, K. Ma, T. Fang, Z. Zhang, S. Ouyang, H. Zhang, D. Yu, M. Jiang. Transactions on Machine Learning Research (TMLR), May 2025.
• [J44] Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices by R. Qin, D. Liu, C. Xu, Z. Yan, Z. Tan, Z. Jia, A. Nassereldine, J. Li, M. Jiang, A. Abbasi, J. Xiong, Y. Shi. ACM Transactions on Design Automation of Electronic Systems (TODAES), May 2025.
2024
• [J43] Transcend the Boundaries: Machine Learning for Designing Polymeric Membrane Materials for Gas Separation by J. Xu, A. Suleiman, G. Liu, R. Zhang, M. Jiang, R. Guo, T. Luo. Chemical Physics Reviews, December 2024. [DOI]
• [J42] Large Language Models on Graphs: A Comprehensive Survey by B. Jin, G. Liu, C. Han, M. Jiang, H. Ji, J. Han. IEEE Transactions on Knowledge and Data Engineering (TKDE), December 2024. [DOI]
• [J41] Current and Future Directions in Network Biology by M. Zitnik, and many others including M. Jiang. Bioinformatics Advances, August 2024. [DOI]
• [J40] Superior Polymeric Gas Separation Membrane Designed by Explainable Graph Machine Learning by J. Xu, A. Suleiman, G. Liu, M. Perez, R. Zhang, M. Jiang, R. Guo, T. Luo. Cell Reports Physical Science, June 2024. [DOI]
• [J39] Autonomous Output-Oriented Aerosol Jet Printing Enabled by Hybrid Machine Learning by Y. Du, M. Jiang, Y. Zhang. Advanced Materials Technologies, February 2024. [DOI]
• [J38] Rationalizing Graph Neural Networks with Data Augmentation by G. Liu, E. Inae, T. Luo, M. Jiang. ACM Transactions on Knowledge Discovery from Data (TKDD), February 2024. [DOI]
2023
• [J37] User Modeling in the Era of Large Language Models by Z. Tan, M. Jiang. IEEE Data Engineering Bulletin, December 2023.
• [J36] Deep Multimodal Complementarity Learning by D. Wang, T. Zhao, W. Yu, N.V. Chawla, M. Jiang. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), December 2023. [DOI]
• [J35] Transfer Learning across Graph Convolutional Networks: Methods, Theory, and Applications by M. Jiang. ACM Transactions on Knowledge Discovery from Data (TKDD), October 2023. [DOI]
• [J34] Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions by Z. Zhang, W. Yu, Z. Ning, M. Ju, M. Jiang. Transactions of the Association for Computational Linguistics (TACL), August 2023. [DOI]
• [J33] Graph Data Augmentation for Graph Machine Learning: A Survey by T. Zhao, W. Jin, Y. Liu, Y. Wang, G. Liu, S. Gunnemann, N. Shah, M. Jiang. IEEE Data Engineering Bulletin, June 2023. [Readlist]
• [J32] Modeling Co-evolution of Attributed and Structural Information in Graph Sequence by D. Wang, Z. Zhang, Y. Ma, T. Zhao, T. Jiang, N.V. Chawla, M. Jiang. IEEE Transactions on Knowledge and Data Engineering (TKDE), February 2023. [DOI]
2022
• [J31] A Survey on Data-Driven Network Intrusion Detection by D. Chou, M. Jiang. ACM Computing Surveys (CSUR), December 2022. [DOI]
• [J30] Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning by M. Saebi, S. Kreig, C. Zhang, M. Jiang, T. Kajdanowicz, N.V. Chawla. Information Fusion, December 2022. [DOI]
• [J29] A Survey of Knowledge-Enhanced Text Generation by W. Yu, C. Zhu, Z. Li, Z. Hu, Q. Wang, H. Ji, M. Jiang. ACM Computing Surveys (CSUR), November 2022. [DOI]
• [J28] Leveraging Low-Fidelity Data to Improve Machine Learning of Sparse High-Fidelity Thermal Conductivity Data via Transfer Learning by Z. Liu, M. Jiang, T. Luo. Materials Today Physics, November 2022. [DOI]
• [J27] Structural and Textual Information Fusion for Symptom and Disease Representation Learning by S. Zhao, M. Jiang, B. Qin, T. Liu, C.X. Zhai, F. Wang. IEEE Transactions on Knowledge and Data Engineering (TKDE), September 2022. [DOI]
• [J26] A Synergistic Approach for Graph Anomaly Detection with Pattern Mining and Feature Learning by T. Zhao, T. Jiang, N. Shah, M. Jiang. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), June 2022. [DOI]
• [J25] Federated Dynamic Graph Neural Networks with Secure Aggregation for Video-based Distributed Surveillance by M. Jiang, T. Jung, R. Karl, T. Zhao. ACM Transactions on Intelligent Systems and Technology (TIST), May 2022. [DOI]
• [J24] Modeling Multi-scale Data via a Network of Networks by S. Gu, M. Jiang, P.H. Guzzi, T. Milenkovic. Bioinformatics, March 2022. [DOI]
2021
• [J23] Unified Representation of Twitter and Online News using Graph and Entities by M. Syed, D. Wang, M. Jiang, O. Conway, V. Juneja, S. Subramanian, N.V. Chawla. Frontiers in Big Data, section Big Data Networks, August 2021. [DOI]
• [J22] Modeling Complementarity in Behavior Data with Multi-Type Itemset Embedding by D. Wang, Q. Zeng, N.V. Chawla, M. Jiang. ACM Transactions on Intelligent Systems and Technology (TIST), August 2021. [DOI]
• [J21] Biomedical Knowledge Graphs Construction from Conditional Statements by T. Jiang, Q. Zeng, T. Zhao, B. Qin, T. Liu, N. Chawla, M. Jiang. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), May-June 2021. [DOI]
• [J20] Inductive Contextual Relation Learning for Personalization by C. Zhang, H. Yao, L. Yu, C. Huang, D. Song, M. Jiang, H. Chen, N.V. Chawla. ACM Transactions on Information Systems (TOIS), May 2021. [DOI]
2020
• [J19] Binarizing Weights Wisely for Edge Intelligence: Guide for Partial Binarization of Deconvolution-Based Generators by J. Liu, X. Xu, M. Jiang, Y. Shi. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCADICS), December 2020. [DOI]
• [J18] Leverage Electron Properties to Predict Phonon Properties via Transfer Learning for Semiconductors by Z. Liu, M. Jiang, T. Luo. Science Advances, November 2020. [DOI]
• [J17] Combined Heat and Power System Intelligent Economic Dispatch: A Deep Reinforcement Learning Approach by S. Zhou, Z. Hu, W. Gu, M. Jiang, M. Chen, Q. Hong, C. Booth. International Journal of Electrical Power and Energy System, September 2020. [DOI]
• [J16] Precise Temporal Slot Filling via Truth Finding with Data-Driven Commonsense by X. Wang, M. Jiang. Knowledge and Information Systems, July 2020. [DOI]
• [J15] Phrase-level Pairwise Topic Modeling to Uncover Helpful Peer Responses to Online Suicidal Crises by M. Jiang, B.A. Ammerman, Q. Zeng, R. Jacobucci, A. Brodersen. Nature Humanities and Social Sciences Communications, July 2020. [DOI]
2019
• [J14] Treatment Effect Estimation via Differentiated Confounder Balancing and Regression by K. Kuang, P. Cui, B. Li, M. Jiang, S. Yang. Transactions on Knowledge Discovery from Data (TKDD), December 2019. [DOI]
• [J13] An Integrated Energy System Operating Scenarios Generator based on Generative Adversarial Network by S. Zhou, Z. Hu, Z. Zhong, D. He, M. Jiang. Sustainability, November 2019. [DOI]
• [J12] Artificial Intelligence based Smart Energy Community Management: A Reinforcement Learning Approach by S. Zhou, Z. Hu, W. Gu, M. Jiang, X. Zhang. CSEE Journal of Power and Energy Systems, March 2019. [DOI]
2018
• [J11] Effective Promotional Strategies Selection in Social Media: A Data-Driven Approach by K. Kuang, M. Jiang, P. Cui, J. Sun, S. Yang. IEEE Transactions on Big Data (TBD), December 2018. [DOI]
• [J10] Automated Phrase Mining from Massive Text Corpora by J. Shang, J. Liu, M. Jiang, X. Ren, C. R. Voss, J. Han. IEEE Transactions on Knowledge and Data Engineering (TKDE), October 2018. [DOI]
• [J9] DPPred: An Effective Prediction Framework with Concise Discriminative Patterns by J. Shang, M. Jiang, W. Tong, J. Xiao, J. Peng, J. Han. IEEE Transactions on Knowledge and Data Engineering (TKDE), July 2018. [DOI]
2012-2017
• [J8] Embedding Learning with Events in Heterogeneous Information Networks by H. Gui, J. Liu, F. Tao, M. Jiang, B. Norick, L. Kaplan, J. Han. IEEE Transactions on Knowledge and Data Engineering (TKDE), July 2017. [DOI]
• [J7] Inferring Lockstep Behavior from Connectivity Pattern in Large Graphs by M. Jiang, P. Cui, A. Beutel, C. Faloutsos, S. Yang. Knowledge and Information Systems (KAIS), August 2016. [DOI]
• [J6] Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach by M. Jiang, P. Cui, A. Beutel, C. Faloutsos, S. Yang. Special Issue on the Best of SIGKDD 2014, ACM Transactions on Knowledge Discovery from Data (TKDD), July 2016. [DOI]
• [J5] Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms by M. Jiang, A. Beutel, P. Cui, B. Hooi, S. Yang, C. Faloutsos. IEEE Transactions on Knowledge and Data Engineering (TKDE), April 2016. [DOI]
• [J4] Suspicious Behavior Detection: Current Trends and Future Directions by M. Jiang, P. Cui, C. Faloutsos. Special Issue on Online Behavioral Analysis and Modeling, IEEE Intelligent Systems (IS), January 2016. [DOI]
• [J3] Social Recommendation with Cross-Domain Transferable Knowledge by M. Jiang, P. Cui, X. Chen, F. Wang, W. Zhu, S. Yang. IEEE Transactions on Knowledge and Data Engineering (TKDE), November 2015. [DOI]
• [J2] Scalable Recommendation with Social Contextual Information by M. Jiang, P. Cui, F. Wang, W. Zhu, S. Yang. IEEE Transactions on Knowledge and Data Engineering (TKDE), November 2014. [DOI]
• [J1] Mining Diversity on Social Media Networks by L. Liu, F. Zhu, M. Jiang, J. Han, L. Sun, S. Yang. Multimedia Tools and Applications (MTA), January 2012. [DOI]

Workshop Papers

2025
• [W37] Spectral Manifold Harmonization for Graph Imbalanced Regression by B. Nogueira, G. Gomes, M. Jiang, N.V. Chawla, N. Moniz. Workshop of Machine Learning on Graphs in the Era of Generative Artificial Intelligence (MLoG-GenAI) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2025.
• [W36] Spectral Manifold Harmonization for Graph Imbalanced Regression by B. Nogueira, G. Gomes, M. Jiang, N.V. Chawla, N. Moniz. Workshop of Data in Generative Models - The Bad, the Ugly, and the Greats (DIG-BUG) at International Conference on Machine Learning (ICML), 2025.
2024
• [W35] Learning Molecular Representation in a Cell by G. Liu, S. Seal, J. Arevalo, Z. Liang, A.E. Carpenter, M. Jiang, S. Singh. Workshop on AI for New Drug Modalities (AIDrugX) at Conference on Neural Information Processing Systems (NeurIPS), 2024.
• [W34] Leveraging Historical Turns for Retrieval-Augmented Generation in Conversational Search by F. Mo, Y. Gao, X. Liu, Z. Wu, P. Chen, Z. Li, Z. Wang, X. Li, M. Jiang, J. Nie. Workshop on AI Agent for Information Retrieval (Agent4IR) at ACM International Conference on Information and Knowledge Management (CIKM), 2024.
• [W33] OpenFMNav: Towards Open-Set Zero-Shot Object Navigation via Vision-Language Foundation Models by Y. Kuang, H. Lin, M. Jiang. Workshop on Large Language Model Agents (LLMAgent) at International Conference on Learning Representations (ICLR), 2024.
2023
• [W32] Semi-Supervised Graph Imbalanced Regression by G. Liu, T. Zhao, E. Inae, T. Luo, M. Jiang. Workshop on New Frontiers in Graph Learning (GLFrontiers) at Conference on Neural Information Processing Systems (NeurIPS), 2023.
• [W31] Motif-aware Attribute Masking for Molecular Graph Pre-training by E. Inae, G. Liu, M. Jiang. Workshop on New Frontiers in Graph Learning (GLFrontiers) at Conference on Neural Information Processing Systems (NeurIPS), 2023.
• [W30] Explaining Tree Model Decisions in Natural Language for Network Intrusion Detection by N. Ziems, G. Liu, J. Flanagan, M. Jiang. Workshop on XAI in Action: Past, Present, and Future Applications (XAIA) at Conference on Neural Information Processing Systems (NeurIPS), 2023.
• [W29] A Quantitative Review on Language Model Efficiency Research by M. Jiang, H. Dang, L. Tong. Large Language Model Symposium at International Joint Conference on Artificial Intelligence (IJCAI), 2023.
• [W28] Transfer Learning with Diffusion Model for Polymer Property Prediction by G. Liu, M. Jiang. Workshop on Deep Learning on Graphs: Methods and Applications (DLG) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023.
• [W27] Investigating Cross-Domain Behaviors of BERT in Review Understanding by A. Lu, M. Jiang. Workshop on e-Commerce and NLP (ECNLP) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023.
• [W26] Completing Taxonomies with Relation-Aware Mutual Attentions by Q. Zeng, Z. Zhang, J. Lin, M. Jiang. Workshop on Mining and Learning with Graphs (MLG) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023.
• [W25] Embedding Mental Health Discourse for Community Recommendation by H. Dang, B. Nguyen, N. Ziems, M. Jiang. Workshop on Computational Approaches to Discourse (CDOI) at Annual Meeting of the Association for Computational Linguistics (ACL), 2023.
• [W24] Transfer Learning with Diffusion Model for Polymer Property Prediction by G. Liu, M. Jiang. ICLR Workshop on ML4Materials: from Molecules to Materials (ML4Materials) at International Conference on Learning Representations (ICLR), 2023.
• [W23] Creative Research Question Generation for Human-Computer Interaction Research by Y. Liu, M. Yu, M. Jiang, Y. Huang. Workshop on Human-AI Co-Creation with Generative Models (HAI-GEN) at Annual Conference on Intelligent User Interfaces (IUI), 2023.
• [W22] Improving Mental Health Support Response Generation with Event-based Knowledge Graph by L. Tong, Q. Liu, W. Yu, M. Yu, Z. Zhang, M. Jiang. Workshop on Knowledge-Augmented Methods for NLP (KnowledgeNLP) at AAAI Conference on Artificial Intelligence (AAAI), 2023.
• [W21] Feature Instability Search for Multi-Way Explainability by S. Kelly, M. Jiang. Workshop on Representation Learning for Responsible Human-Centric AI (R2HCAI) at AAAI Conference on Artificial Intelligence (AAAI), 2023.
2022
• [W20] Investigating Relationships between Accuracy and Diversity in Multi-Reference Text Generation by W. Fang, M. Jiang. Undergraduate Consortium (UC) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022.
• [W19] Sampling Directed Graphs with Linearly Rescaled Degree Matrices by Y. Yan, M. Jiang. Undergraduate Consortium (UC) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022.
• [W18] Scientific Comparative Argument Generation by M. Yu, W. Yu, M. Jiang. Third Document Intelligence Workshop (DI) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022.
• [W17] On the Relationship between Counterfactual Explainer and Recommender by G. Liu, Z. Zhang, Z. Ning, M. Jiang. First Workshop on Data Science and Artificial Intelligence on Responsible Recommendation (DSAI4RRS) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022.
• [W16] Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts by W. Yu, C. Zhu, L. Qin, T. Zhao, M. Jiang. Workshop of Deep Learning on Graphs for Natural Language Processing (DLG4NLP) at North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
2021
• [W15] Validating Label Consistency in NER Data Annotation by Q. Zeng, M. Yu, W. Yu, T. Jiang, M. Jiang. Workshop on Evaluation and Comparison of NLP Systems (Eval4NLP) at Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021. [DOI]
• [W14] Evolutionary Graph Normalizing Flows by D. Wang, T. Zhao, N.V. Chawla, M. Jiang. International Workshop on Deep Learning on Graphs: Methods and Applications (DLG) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021.
2020
• [W13] SmartFund: Predicting Research Outcomes with Machine Learning and Natural Language Processing by A. Alaphat, M. Jiang. International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD) at IEEE International Conference on Big Data (BigData), 2020. (Regular paper, 10 pages. Mr. Alaphat was a frenshman undergraduate when he finished the work.) [DOI]
• [W12] Learning Attribute-Structure Co-Evolutions in Dynamic Graphs by D. Wang, Z. Zhang, Y. Ma, T. Zhao, T. Jiang, N.V. Chawla, M. Jiang. International Workshop on Deep Learning on Graphs: Methods and Applications (DLG) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020. (Best Paper Award)
• [W11] Early Fraud Detection with Augmented Graph Learning by T. Zhao, N. Bo, W. Yu, M. Jiang. International Workshop on Deep Learning on Graphs: Methods and Applications (DLG) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020.
• [W10] GNN-based Graph Anomaly Detection with Graph Anomaly Loss by T. Zhao, C. Deng, K. Yu, T. Jiang, D. Wang, M. Jiang. International Workshop on Deep Learning on Graphs: Methods and Applications (DLG) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020.
• [W9] A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction by Y. Zhou, T. Zhao, M. Jiang. Workshop on Fact Extraction and Verification (FEVER) at Annual Meeting of the Association for Computational Linguistics (ACL), 2020. [DOI]
• [W8] Generating Helpful Responses for Intelligent Tech Support by W. Yu, L. Wu, S. Tao, Y. Deng, Q. Zeng, M. Jiang. Reasoning for Complex QA Workshop (RCQA) at AAAI Conference on Artificial Intelligence (AAAI), 2020.
2019
• [W7] Graph Few-shot Learning via Knowledge Transfer by H. Yao, C. Zhang, Y. Wei, M. Jiang, S. Wang, N.V. Chawla, Z. Li. Graph Representation Learning Workshop (GRL) at Conference on Neural Information Processing Systems (NeurIPS), 2019.
• [W6] Faceted Hierarchy: A New Graph Type to Organize Scientific Concepts and a Construction Method by Q. Zeng, M. Yu, W. Yu, J. Xiong, Y. Shi, M. Jiang. Workshop on Graph-Based Natural Language Processing (TextGraphs) at Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019. [DOI]
• [W5] A Study of Person Entity Extraction and Profiling from Classical Chinese Historiography by Y. Ma, Q. Zeng, T. Jiang, L. Cai, M. Jiang. International Workshop on EntitY REtrieval (EYRE) at ACM International Conference on Information and Knowledge Management (CIKM), 2019.
• [W4] Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements by T. Jiang, T. Zhao, B. Qin, T. Liu, N.V. Chawla, M. Jiang. International Workshop on Data Mining in Bioinformatics (BioKDD) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019.
2016-2018
• [W3] Multifaceted Event Analysis on Cross-Media Network Data by D. Wang, M. Jiang, X. Wang, N. Chawla, and P. Brunts. International Workshop on Heterogeneous Networks Analysis and Mining (HeteroNAM) at ACM Conference on Web Search and Data Mining (WSDM), 2018.
• [W2] Integrating Knowledge from Latent and Explicit Features for Triple Scoring—Team Radicchio's Triple Scorer at WSDM Cup 2017 by L.W. Chen, B. Mangipudi, J. Bandlamudi, R. Sehgal, Y. Hao, M. Jiang, H. Gui. The 10th ACM Conference on Web Search and Data Mining (WSDM) Notebook Papers, 2017.
• [W1] Catching Social Media Advertisers with Strategy Analysis by M. Jiang. The First International Workshop on Computational Methods for CyberSafety at ACM International Conference on Information and Knowledge Management (CIKM), 2016. [DOI]

Books and Book Chapters

• [B6] Modeling Polymers with Neural Networks by E. Inae, Y. Liu, Y. Zhu, J. Xu, G. Liu, R. Zhang, T. Luo, M. Jiang. American Chemical Society, 2025.
• [B5] Deep Learning for Polymer Discovery: Foundation and Advances by G. Liu, E. Inae, M. Jiang. Synthesis Lectures on Data Mining and Knowledge Discovery, Springer, 2025.
• [B4] Knowledge-augmented Methods for Natural Language Processing by M. Jiang, B. Lin, S. Wang, Y. Xu, W. Yu, C. Zhu. In Springer, 2024.
• [B3] Editorial: Computational Behavioral Modeling for Big User Data by M. Jiang, C. Zhang, X. Zhang, N. Shah. In Frontiers in Big Data, section Big Data Networks, 2022.
• [B2] Behavior Modeling in Social Networks by M. Jiang. In Encyclopedia of Social Network Analysis and Mining, 2nd edition, Springer, 2017.
• [B1] Mining User Behaviors in Large Social Networks by M. Jiang and P. Cui. Book Chapter in Big Data in Complex and Social Networks, Chapman and Hall/CRC Big Data Series, 2016. [Amazon]

Patent

• [P1] System and Method for Technical Question Answering across Tasks and Domains by W. Yu, L. Wu, Y. Deng, Q. Zeng, R. Mahindru, S. Guven, M. Jiang. October 24, 2023. (Ref: P202100237, ID: 96545251)

Online Demonstrations

• Ru's Social Networks in China's Han Dynasty by M. Jiang. 2018.
• Flexible Evolutionary Multi-faceted Analysis by M. Jiang and X. Xu. 2014.