Publications

Pre-training Epidemic Time Series Forecasters with Compartmental Prototypes

Zewen Liu, Juntong Ni, Bohan Wang, Max S. Y. Lau, Wei Jin

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Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents

Tianxin Wei, Zhan Shi, Minhua Lin, Bing He, Zewen Liu, Yisi Sang, Yuanchen Bei, Xuying Ning, Jiaru Zou, Ting-Wei Li, Xiao Lin, Yanjun Zhao, Chi Wang, Benoit Dumoulin, Dakuo Wang, Jingrui He, Hanqing Lu

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EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering and Reasoning

Mingyang Wei, Dehai Min, Zewen Liu, Yuzhang Xie, Guanchen Wu, Ziyang Zhang, Carl Yang, Max S. Y. Lau, Qi He, Lu Cheng, Wei Jin

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SymbolBench: Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series?

Zewen Liu, Juntong Ni, Xianfeng Tang, Max S. Y. Lau, Qi He, Wenpeng Yin, Wei Jin

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Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks

Bohan Wang, Zewen Liu, Lu Lin, Hui Liu, Li Xiong, Ming Jin, Wei Jin

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TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation

Juntong Ni, Zewen Liu, Shiyu Wang, Ming Jin, Wei Jin

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Higher-order Interaction Matters: Modeling Epidemics via Dynamic Hypergraph Neural Networks

Songyuan Liu, Shengbo Gong, Tianning Feng, Zewen Liu, Max S. Y. Lau, Wei Jin

pdf·arxiv

EARTH: Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph

Guancheng Wan, Zewen Liu, Xiaojun Shan, Max S. Y. Lau, B. Aditya Prakash, Wei Jin

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Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks

Zewen Liu, Xiaoda Wang, Bohan Wang, Zijie Huang, Carl Yang, Wei Jin

pdf·acm dl·paper list

Efficient Epidemic Intervention Generation: A Graph Adversarial Attack Perspective

Yunxiao Li, Mingyang Wei, Zewen Liu, Max S. Y. Lau, Wei Jin

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EpiLearn: A Python Library for Machine Learning in Epidemic Modeling

Zewen Liu, Yunxiao Li, Mingyang Wei, Guancheng Wan, Max S. Y. Lau, Wei Jin

pdf·code·docs

A Review of Graph Neural Networks in Epidemic Modeling

Zewen Liu^*, Guancheng Wan^*, B. Aditya Prakash, Max S. Y. Lau, Wei Jin

pdf·reading list

Toward AI Foundation Models for Epidemics: Promise, Challenges, and Paths Forward

Max S. Y. Lau, C. Jessica E. Metcalf, Zewen Liu, Bryan T. Grenfell, Wei Jin

paper

GANSamples-ac4C: Enhancing ac4C Site Prediction via Generative Adversarial Networks and Transfer Learning

Fei Li, Jiale Zhang, Kewei Li, Yu Peng, Haotian Zhang, Yiping Xu, Yue Yu, Yuteng Zhang, Zewen Liu, Ying Wang, Lan Huang, Fengfeng Zhou

paper

Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams

Zewen Liu, Zhan Shi, Yisi Sang, Bing He, Minhua Lin, Tianxin Wei, Dakuo Wang, Benoit Dumoulin, Wei Jin, Hanqing Lu

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Harness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM Agents

Minhua Lin, Juncheng Wu, Zijun Wang, Zhan Shi, Yisi Sang, Bing He, Zewen Liu, Tianxin Wei, Zongyu Wu, Zhiwei Zhang, Dakuo Wang, Xiang Zhang, Benoit Dumoulin, Cihang Xie, Yuyin Zhou, Suhang Wang, Hanqing Lu

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Large Language Models at Population Scale: A Survey and Taxonomy of Public Health Applications

Zhengxu Tang^*, Bohan Wang^*, Yiming Lu^*, Zewen Liu, Max S. Y. Lau, Wei Jin

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EpiLearn: From Cross-Paradigm Comparison to Regime-Aware Deployment of Epidemic Forecasting Models

Zewen Liu, Max S. Y. Lau, Wei Jin

Vaccination Restructures the Spatial Geometry of Measles Transmission

Zewen Liu, Bryan T. Grenfell, C. Jessica E. Metcalf, Wei Jin, Max S. Y. Lau

U-Cast: Learning Hierarchical Structures for High-Dimensional Time Series Forecasting

Juntong Ni^*, Shiyu Wang^*, Zewen Liu, Xiaoming Shi, Xinyue Zhong, Zhou Ye, Wei Jin

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Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signals

Saurabh Kataria, Yi Wu, Zhaoliang Chen, Hyunjung Gloria Kwak, Yuhao Xu, Lovely Yeswanth Panchumarthi, Ran Xiao, Jiaying Lu, Ayca Ermis, Anni Zhao, Runze Yan, Alex Federov, Zewen Liu, Xu Wu, Wei Jin, Carl Yang, Jocelyn Grunwell, Stephanie R. Brown, Amit Shah, Craig Jabaley, Tim Buchman, Sivasubramanium V. Bhavani, Randall J. Lee, Xiao Hu

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Learning on Graphs with Large Language Models (LLMs): A Deep Dive into Model Robustness

Kai Guo^*, Zewen Liu^*, Zhikai Chen, Hongzhi Wen, Wei Jin, Jiliang Tang, Yi Chang

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