Publications
Note: "*" indicates authors with equal contributions. "_" indicates supervised students as the leading authors.
Note: "*" indicates authors with equal contributions. "_" indicates supervised students as the leading authors.
[Arxiv-2025] Data Value in the Age of Scaling: Understanding LLM Scaling Dynamics Under Real–Synthetic Data Mixtures. [PDF]
Haohui Wang, Jingyuan Qi, Jianpeng Chen, Jun Wu, Lifu Huang, Lecheng Zheng, Kevin Choi, Balaji Veeramani, Edward Bowen, Alison Hu, Tyler Cody, Dawei Zhou.
[Arxiv-2025] NTK-S3: A Unified Framework for Characterizing Data-Driven and Reasoning-Driven Hallucinations in LLMs. [PDF]
Xinyue Zeng, Junhong Lin, Yujun Yan, Feng Guo, Liang Shi, Jun Wu, Dawei Zhou.
[Arxiv-2025] MetaSymbO: Language‑Guided Metamaterial Discovery via Symbolic-Driven Latent Optimization. [PDF]
Jianpeng Chen, Wangzhi Zhan, Dongqi Fu, Junkai Zhang, Zian Jia, Ling Li, Wei Wang, Dawei Zhou.
[Arxiv-2025] VoxPlorer: Towards Novel Metamaterial Design Discovery via Latent Space Constraint and Exploration. [PDF]
Wangzhi Zhan, Jianpeng Chen, Dongqi Fu, Dawei Zhou.
[Arxiv-2025] Plan and Budget: Effective and Efficient Test-Time Scaling on Reasoning Large Language Models. [PDF]
Junhong Lin*, Xinyue Zeng*, Jie Zhu, Song Wang, Julian Shun, Jun Wu, Dawei Zhou. (*Equal contribution)
[Arxiv-2025] DISPROTBENCH: A Disorder-Aware, Task-Rich Benchmark for Evaluating Protein Structure Prediction in Realistic Biological Contexts. [PDF]
Xinyue Zeng, Tuo Wang, Adithya Kulkarni, Alexander Lu, Alexandra Ni, Phoebe Xing, Junhan Zhao, Siwei Chen, Dawei Zhou.
[Arxiv-2025] HypRQ-VAE: Long-Tail-Aware Item Indexing for Generative Recommender Systems. [PDF]
Longfeng Wu, Tong Zeng, Giovanni Seni, Zhimin Peng, Bhanu Pratap Singh Rawat, Si Zhang, Yao Zhou, Bowen Xu, Lecheng Zheng, Bo Ji, Yujun Yan, Dawei Zhou.
[Arxiv-2025] PDMBench: A Standardized and Multi-Perspective Benchmark for Predictive Maintenance on Multi-Sensor Industrial Time-Series Data. [PDF]
Shuaicheng Zhang, Tuo Wang, Adithya Kulkarni, Stephen Adams, Sanmitra Bhattacharya, Sunil Reddy Tiyyagura, Edward Bowen, Balaji Veeramani, Dawei Zhou.
[NeurIPS-2025] HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations. [PDF][Code]
Shuaicheng Zhang*, Haohui Wang*, Junhong Lin, Xiaojie Guo, Yada Zhu, Si Zhang, Dongqi Fu, Dawei Zhou. (*Equal contribution)
Annual Conference on Neural Information Processing Systems, December 2025.
[EMNLP-2025] GENUINE: Graph Enhanced Multi-level Uncertainty Estimation for Large Language Models. [PDF][Code]
Tuo Wang, Adithya Kulkarni, Tyler Cody, Peter A. Beling, Yujun Yan, Dawei Zhou.
The 2025 Conference on Empirical Methods in Natural Language Processing 2025.
[EMNLP-2025] SciCompanion: Graph-Grounded Reasoning for Structured Evaluation of Scientific Arguments. [PDF][Code]
Joshua Alan Flashner, Adithya Kulkarni, Dawei Zhou.
The 2025 Conference on Empirical Methods in Natural Language Processing 2025.
[ICDM-2025] The End of Trial-and-Error: A Vision for Generative Intelligence in Metamaterial Design. [PDF][Code]
Adithya Kulkarni, Haohui Wang, Wangzhi Zhan, Jianpeng Chen, Dawei Zhou.
IEEE International Conference on Data Mining, November 2025
[ICDM-2025] Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search. [PDF][Code]
Longfeng Wu, Yao Zhou, Tong Zeng, Zhimin Peng, Bhanu Pratap Singh Rawat, Lecheng Zheng, Giovanni Seni, Dawei Zhou.
IEEE International Conference on Data Mining, November 2025
[ICML-2025] UniMate: A Unified Model for Mechanical Metamaterial Generation, Property Prediction, and Condition Confirmation. [PDF][Code]
Wangzhi Zhan, Jianpeng Chen, Dongqi Fu, Dawei Zhou.
International Conference on Machine Learning, 2025
[ICML-2025] LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection. [PDF][Code]
Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou.
International Conference on Machine Learning, 2025
[KDD-2025] MetamatBench: Integrating Heterogeneous Data, Computational Tools, and Visual Interface for Metamaterial Discovery. [PDF][Code]
Jianpeng Chen, Wangzhi Zhan, Haohui Wang, Zian Jia, Jingru Gan, Junkai Zhang, Jingyuan Qi, Tingwei Chen, Lifu Huang, Muhao Chen, Ling Li, Wei Wang, Dawei Zhou.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2025.
[KDD-2025] EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network. [PDF][Code]
Weijie Guan, Haohui Wang, Jian Kang, Lihui Liu, Dawei Zhou.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2025.
[KDD-2025] Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks. [PDF][Code]
Tuo Wang, Jian Kang, Yujun Yan, Adithya Kulkarni, Dawei Zhou.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2025.
[KDD-2025] MentorPDM: Learning Data-Driven Curriculum for Multi-Modal Predictive Maintenance. [PDF][Code]
Shuaicheng Zhang, Tuo Wang, Stephen Adams, Sanmitra Bhattacharya, Sunil Reddy Tiyyagura, Edward Bowen, Balaji Veeramani, Dawei Zhou.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2025.
[KDD-2025] Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video Understanding. [PDF][Code]
Tong Zeng, Longfeng Wu, Liang Shi, Dawei Zhou, Feng Guo.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2025.
[WWW-2025] Bridging Fairness and Uncertainty: Theoretical Insights and Practical Strategies for Equalized Coverage in GNNs. [PDF][Code]
Longfeng Wu, Yao Zhou, Jian Kang, Dawei Zhou.
The Web Conference, April 2025.
[SDM-2025] Heterogeneous Multi-Agent Framework for Dynamic Generalized Category Discovery. [PDF][Slides][Code]
Fatimah Alotaibi, Adithya Kulkarni, Dawei Zhou.
SIAM: SIAM International Conference on Data Mining, May 2025.
[NACCL-2025] MetaScientist: A Human-AI Synergistic Framework for Automated Mechanical Metamaterial Design. [PDF][Demo]
Jingyuan Qi, Minqian Liu, Zian Jia, Wangzhi Zhan, Junkai Zhang, Xiaofei Wen, Jingru Gan, Jianpeng Chen, Qin Liu, Mingyu Derek Ma, Bangzheng Li, Haohui Wang, Muhao Chen, Dawei Zhou, Ling Li, Wei Wang, Lifu Huang.
North American Chapter of the Association for Computational Linguistics 2025.
[BigData-2024] Graph of Logic: Enhancing LLM Reasoning with Graphs and Symbolic Logic [PDF]
Fatimah Alotaibi, Adithya Kulkarni, Dawei Zhou.
IEEE International Conference on Big Data, December, 2024.
[NeurIPS-2024] Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox. [PDF][Code]
Haohui Wang, Weijie Guan, Jianpeng Chen, Zi Wang, Dawei Zhou.
Annual Conference on Neural Information Processing Systems, December 2024.
[CIKM-2024] Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation. [PDF][Code]
Baoyu Jing, Dawei Zhou, Kan Ren, Carl Yang
ACM International Conference on Information and Knowledge Management, Oct 2024.
[KDD-2024] Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization. [PDF][Code]
Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Wei Cheng, Si Zhang, Yonghui Fan, Liqing Zhang, Dawei Zhou.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2024.
[ICML-2024] EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs. [PDF][Code]
Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou.
International Conference on Machine Learning, 2024
[ICML-2024] Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning. [PDF]
Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan
International Conference on Machine Learning, 2024
[Brief Bioinform-2024] A Systematic Evaluation of Computational Methods for Cell Segmentation. [PDF]
Yuxing Wang, Junhan Zhao, Hongye Xu, Cheng Han, Zhiqiang Tao, Dawei Zhou, Tong Geng, Dongfang Liu, Zhicheng Ji
Briefings in Bioinformatics, 2024
[IJCAI-2024] 3D-FuM: Benchmarking 3D Molecule Learning with Functional Groups [PDF][Github]
Tingwei Chen*, Jianpeng Chen*, Dawei Zhou. (*Equal contribution)
International Joint Conference on Artificial Intelligence (IJCAI), 2024.
[ICDE-2024] FairGen: Towards Fair Graph Generation. [PDF]
Lecheng Zheng*, Dawei Zhou*, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He. (*Equal contribution)
IEEE International Conference on Data Engineering (ICDE), 2024.
[BigData-2023] Towards Bi-Level Out-of-Distribution Logical Reasoning on Knowledge Graphs [PDF]
Fatimah Alotaibi, Dawei Zhou.
IEEE International Conference on Big Data, December, 2023.
[ICAIF-2023] TGEditor: Task-Guided Graph Editing for Augmenting Temporal Financial Transaction Networks [PDF]
Shuaicheng Zhang, Yada Zhu, Dawei Zhou.
ACM International Conference on AI in Finance, November 2023.
[CSUR-2023] Rare Category Analysis for Complex Data: A Review [PDF]
Dawei Zhou, Jingrui He.
ACM Computing Surveys, September 2023.
[KDD-2023] Towards Reliable Rare Category Analysis on Graphs via Individual Calibration. [PDF][Code]
Longfeng Wu, Bowen Lei, Dongkuan Xu, and Dawei Zhou.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2023.
[ICML-2023] Personalized Federated Learning under Mixture of Distributions. [PDF][Code]
Yue Wu*, Shuaicheng Zhang*, Wenchao Yu, Yanchi Liu, Quanquan Gu, Dawei Zhou, Haifeng Chen, Wei Cheng. (*Equal contribution)
International Conference on Machine Learning, 2023
[WWW-2023] Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs. [PDF][Code]
Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd and Jingrui He.
The Web Conference, April 2023.
[ICDM-2022] Towards High-Order Complementary Recommendation via Logical Reasoning Network. [PDF][Slides][Code]
Longfeng Wu, Yao Zhou, and Dawei Zhou.
IEEE International Conference on Data Mining, November 2022.
Yuzhen Mao, Jianhui Sun, and Dawei Zhou.
IEEE International Conference on Data Mining, November 2022.
Dawei Zhou*, Lecheng Zheng*, Dongqi Fu, Jiawei Han, Jingrui He. (*Equal contribution)
ACM International Conference on Information and Knowledge Management, Oct 2022.
[TMLR-2022] Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning. [PDF]
Linfeng Liu, Xu Han, Dawei Zhou, Liping Liu.
Transactions on Machine Learning Research, 2022.
[Thesis-2021] Harnessing rare category trinity for complex data. [PDF]
Dawei Zhou
[TKDD-2021] High-Order Structure Exploration on Massive Graphs: A Local Graph Clustering Perspective. [PDF]
Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong, Hasan Davulcu, Jingrui He.
ACM Transactions on Knowledge Discovery from Data, 2021.
[KDD-2020] A Data-Driven Graph Generative Model for Temporal Interaction Networks. [PDF][Slides][Video][Code]
Dawei Zhou, Lecheng Zheng, Jiawei Han, Jingrui He.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2020.
Dongqi Fu, Dawei Zhou, Jingrui He.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2020.
[WWW-2020] Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting. [PDF][Slides][Code] (Oral Presentation)
Dawei Zhou, Lecheng Zheng, Jianbo Li, Yada Zhu, Jingrui He.
The Web Conference, April 2020.
[AAAI-2020] Towards Fine-grained Temporal Network Representation via Time-Reinforced Random Walk. [PDF][Code]
Dawei Zhou*, Zhining Liu*, Yada Zhu, Jinjie Gu, Jingrui He. (*Equal contribution)
The Thirty-Fourth AAAI Conference on Artificial Intelligence, January 2020.
[CIKM-2019] Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention. [PDF][Code]
Dawei Zhou*, Zhining Liu*, Jingrui He. (*Equal contribution)
ACM International Conference on Information and Knowledge Management.
[KDD-2019] Rare Category Exploration, Exposition, Representation, and Interpretation. [PDF]
Dawei Zhou, Jingrui He.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2019.
Dawei Zhou*, Lecheng Zheng*, Jiejun Xu, Jingrui He. (*Equal contribution)
Frontier, 2019.
Jiacheng Pan, Dongming Han, Fangzhou Guo, Dawei Zhou, Nan Cao, Jingrui He, Mingliang Xu, Wei Chen.
Frontiers of Information Technology & Electronic Engineering, 2019.
[KDD-2018] SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization. [PDF][Video][Code]
Dawei Zhou, Jingrui He, Hongxia Yang, Wei Fan.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2018.
[BigData-2018] Motif-Preserving Dynamic Local Graph Cut. [PDF]
Dawei Zhou, Jingrui He, Hasan Davulcu, Ross Maciejewski.
IEEE International Conference on Big Data, December 2018.
[KDD-2017] A Local Algorithm for Structure-Preserving Graph Cut. [PDF][Video][Code](Oral Presentation, AC Rate = 8.6%)
Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong, Hasan Davulcu, Jingrui He.
ACM: SIGKDD Conference on Knowledge Discovery and Data Mining, August 2017.
[SDM-2017] HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection. [PDF][Slides][Code]
Si Zhang, Dawei Zhou, Mehmet Yigit Yildirim, Scott Alcorn, Jingrui He, Hasan Davulcu, Hanghang Tong.
SIAM: SIAM International Conference on Data Mining, April 2017.
[ICDM-2016] Bi-level Rare Temporal Pattern Detection. [PDF](Full Paper, AC Rate = 8.5%)
Dawei Zhou, Jingrui He, Yu Cao, Jae-sun Seo.
IEEE International Conference on Data Mining, December 2016.
[DMKD-2016] Discovering Rare Categories from Graph Streams. [PDF]
Dawei Zhou, Arun Karthikeyan, Kangyang Wang, Nan Cao, Jingrui He.
Data Mining and Knowledge Discovery, 2016.
[TKDD-2015] Jointly Modeling Label and Feature Heterogeneity in Medical Informatics. [PDF]
Pei Yang, Hongxia Yang, Haoda Fu, Dawei Zhou, Jieping Ye, Theodoros Lappas, Jingrui He.
ACM Transactions on Knowledge Discovery from Data, 2015.
[ICDM-2015] Rare Category Detection on Time-Evolving Graphs. [PDF][Code](Short Paper, AC Rate = 9.8%)
Dawei Zhou, Kangyang Wang, Nan Cao, Jingrui He.
IEEE International Conference on Data Mining, November 2015.
[IJCAI-2015] MUVIR: Multi-View Rare Category Detection. [PDF](Long Presentation)
Dawei Zhou, Jingrui He, K. Selcuk Candan, Hasan Davulcu.
The 24th International Joint Conference on Artificial Intelligence, July 2015.
[AAAI-2015] Tackling Mental Health by Integrating Unobtrusive Multimodal Sensing. [PDF]
Dawei Zhou, Jiebo Luo, Vincent Silenzio, Yun Zhou, Jile Hu, Glenn Currier, Henry Kautz.
The Twenty-Ninth AAAI Conference on Artificial Intelligence, January 2015.