TATC: Predicting Alzheimer's Disease with Actigraphy Data. - Jia Li 009; Yu Rong 001; Helen Meng; Zhihui Lu 003; Timothy C. Y. Kwok; Hong Cheng 001 (KDD, 2018)

Predicting Path Failure In Time-Evolving Graphs. - Jia Li 009; Zhichao Han 003; Hong Cheng 001; Jiao Su; Pengyun Wang; Jianfeng Zhang; Lujia Pan (KDD, 2019)

Semi-Supervised Graph Classification: A Hierarchical Graph Perspective. - Jia Li 009; Yu Rong 001; Hong Cheng 001; Helen Meng; Wen-bing Huang 001; Junzhou Huang (WWW, 2019)

Dirichlet Graph Variational Autoencoder. - Jia Li 009; Jianwei Yu; Jiajin Li; Honglei Zhang; Kangfei Zhao; Yu Rong 001; Hong Cheng 001; Junzhou Huang (NeurIPS, 2020)

Adversarial Attack on Community Detection by Hiding Individuals. - Jia Li 009; Honglei Zhang; Zhichao Han 003; Yu Rong 001; Hong Cheng 001; Junzhou Huang (WWW, 2020)

Dirichlet Graph Variational Autoencoder. - Jia Li 009; Tomas Yu; Jiajin Li; Honglei Zhang; Kangfei Zhao; Yu Rong 001; Hong Cheng 001; Junzhou Huang (CoRR, 2020)

Graph Autoencoders with Deconvolutional Networks. - Jia Li 009; Tomas Yu; Da-Cheng Juan; Arjun Gopalan; Hong Cheng 001; Andrew Tomkins (CoRR, 2020)

Deconvolutional Networks on Graph Data. - Jia Li 009; Jiajin Li; Yang Liu 165; Jianwei Yu; Yueting Li; Hong Cheng 001 (NeurIPS, 2021)

Mask-GVAE: Blind Denoising Graphs via Partition. - Jia Li 009; Mengzhou Liu; Honglei Zhang; Pengyun Wang; Yong Wen; Lujia Pan; Hong Cheng 001 (WWW, 2021)

Rethinking Graph Neural Networks for Anomaly Detection. - Jianheng Tang; Jiajin Li; Ziqi Gao; Jia Li 009 (ICML, 2022)

Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Learning. - Jiajin Li; Jianheng Tang; Lemin Kong; Huikang Liu; Jia Li 009; Anthony Man-Cho So; Jose H. Blanchet (CoRR, 2022)

Latent Augmentation For Better Graph Self-Supervised Learning. - Jiashun Cheng; Man Li 003; Jia Li 009; Fugee Tsung (CoRR, 2022)

ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. - Lanqing Li; Liang Zeng 002; Ziqi Gao; Shen Yuan; Yatao Bian; Bingzhe Wu; Hengtong Zhang; Chan Lu; Yang Yu 010; Wei Liu 005; Hongteng Xu; Jia Li 009; et al. (CoRR, 2022)

What would Harry say? Building Dialogue Agents for Characters in a Story. - Nuo Chen 001; Yan Wang 060; Haiyun Jiang; Deng Cai 002; Ziyang Chen; Jia Li 009 (CoRR, 2022)

Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning. - Jiashun Cheng; Man Li 003; Jia Li 009; Fugee Tsung (AAAI, 2023)

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. - Ziqi Gao; Yifan Niu; Jiashun Cheng; Jianheng Tang; Lanqing Li; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009 (AAAI, 2023)

Human Mobility Modeling during the COVID-19 Pandemic via Deep Graph Diffusion Infomax. - Yang Liu 165; Yu Rong 001; Zhuoning Guo; Nuo Chen 001; Tingyang Xu; Fugee Tsung; Jia Li 009 (AAAI, 2023)

Alleviating Over-smoothing for Unsupervised Sentence Representation. - Nuo Chen 001; Linjun Shou; Jian Pei 001; Ming Gong 001; Bowen Cao; Jianhui Chang; Jia Li 009; Daxin Jiang (ACL (1), 2023)

Structural Contrastive Pretraining for Cross-Lingual Comprehension. - Nuo Chen 001; Linjun Shou; Tengtao Song; Ming Gong 001; Jian Pei 001; Jianhui Chang; Daxin Jiang; Jia Li 009 (ACL (Findings), 2023)

A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment. - Jianheng Tang; Kangfei Zhao; Jia Li 009 (ACL (Findings), 2023)

A Co-training Approach for Noisy Time Series Learning. - Weiqi Zhang; Jianfeng Zhang; Jia Li 009; Fugee Tsung (CIKM, 2023)

Natural Response Generation for Chinese Reading Comprehension. - Nuo Chen 001; Hongguang Li; Yinan Bao; Baoyuan Wang; Jia Li 009 (EMNLP (Findings), 2023)

Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension. - Nuo Chen 001; Hongguang Li; Junqing He; Yinan Bao; Xinshi Lin; Qi Yang; Jianfeng Liu 002; Ruyi Gan; Jiaxing Zhang 001; Baoyuan Wang; Jia Li 009 (EMNLP (Findings), 2023)

Large Language Models Meet Harry Potter: A Dataset for Aligning Dialogue Agents with Characters. - Nuo Chen 001; Yan Wang 060; Haiyun Jiang; Deng Cai 002; Yuhan Li 001; Ziyang Chen; Longyue Wang; Jia Li 009 (EMNLP (Findings), 2023)

Decision Support System for Chronic Diseases Based on Drug-Drug Interactions. - Tian Bian; Yuli Jiang; Jia Li 009; Tingyang Xu; Yu Rong 001; Yi Su; Timothy C. Y. Kwok; Helen Meng; Hong Cheng 001 (ICDE, 2023)

Robust Attributed Graph Alignment via Joint Structure Learning and Optimal Transport. - Jianheng Tang; Weiqi Zhang; Jiajin Li; Kangfei Zhao; Fugee Tsung; Jia Li 009 (ICDE, 2023)

A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data. - Jiajin Li; Jianheng Tang; Lemin Kong; Huikang Liu; Jia Li 009; Anthony Man-Cho So; Jose H. Blanchet (ICLR, 2023)

All in One: Multi-Task Prompting for Graph Neural Networks. - Xiangguo Sun; Hong Cheng 001; Jia Li 009; Bo Liu 004; Jihong Guan (KDD, 2023)

Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. - Jiawen Zhang 001; Shun Zheng 001; Wei Cao 007; Jiang Bian 002; Jia Li 009 (KDD, 2023)

GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection. - Jianheng Tang; Fengrui Hua; Ziqi Gao; Peilin Zhao; Jia Li 009 (NeurIPS, 2023)

Deep Insights into Noisy Pseudo Labeling on Graph Data. - Botao Wang; Jia Li 009; Yang Liu 165; Jiashun Cheng; Yu Rong 001; Wenjia Wang; Fugee Tsung (NeurIPS, 2023)

Knowledge Graph Completion with Counterfactual Augmentation. - Heng Chang; Jie Cai; Jia Li 009 (WWW, 2023)

Bridge the Gap between Language models and Tabular Understanding. - Nuo Chen 001; Linjun Shou; Ming Gong 001; Jian Pei 001; Chenyu You; Jianhui Chang; Daxin Jiang; Jia Li 009 (CoRR, 2023)

Missing Data Imputation with Graph Laplacian Pyramid Network. - Weiqi Zhang; Guanlve Li; Jianheng Tang; Jia Li 009; Fugee Tsung (CoRR, 2023)

Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation. - Yang Liu 165; Jiashun Cheng; Haihong Zhao; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009; Yu Rong 001 (CoRR, 2023)

ProbTS: A Unified Toolkit to Probe Deep Time-series Forecasting. - Jiawen Zhang 001; Xumeng Wen; Shun Zheng 001; Jia Li 009; Jiang Bian 002 (CoRR, 2023)

Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations. - Nuo Chen 001; Zinan Zheng; Ning Wu; Linjun Shou; Ming Gong 001; Yangqiu Song; Dongmei Zhang 001; Jia Li 009 (CoRR, 2023)

Graph Prompt Learning: A Comprehensive Survey and Beyond. - Xiangguo Sun; Jiawen Zhang 001; Xixi Wu; Hong Cheng 001; Yun Xiong; Jia Li 009 (CoRR, 2023)

Is Bigger and Deeper Always Better? Probing LLaMA Across Scales and Layers. - Nuo Chen 001; Ning Wu; Shining Liang; Ming Gong 001; Linjun Shou; Dongmei Zhang 001; Jia Li 009 (CoRR, 2023)

Semi-Supervised Hierarchical Graph Classification. - Jia Li 009; Yongfeng Huang; Heng Chang; Yu Rong 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Self-Supervised Hypergraph Representation Learning for Sociological Analysis. - Xiangguo Sun; Hong Cheng 001; Bo Liu 004; Jia Li 009; Hongyang Chen; Guandong Xu; Hongzhi Yin (IEEE Trans. Knowl. Data Eng., 2023)

Hierarchical Graph Latent Diffusion Model for Conditional Molecule Generation. - Tian Bian; Yifan Niu; Heng Chang; Divin Yan; Junzhou Huang; Yu Rong 001; Tingyang Xu; Jia Li 009; Hong Cheng 001 (CIKM, 2024)

Data Imputation from the Perspective of Graph Dirichlet Energy. - Weiqi Zhang; Guanlue Li; Jianheng Tang; Jia Li 009; Fugee Tsung (CIKM, 2024)

Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations. - Nuo Chen 001; Zinan Zheng; Ning Wu; Ming Gong 001; Dongmei Zhang 001; Jia Li 009 (EMNLP (Findings), 2024)

ControlMath: Controllable Data Generation Promotes Math Generalist Models. - Nuo Chen 001; Ning Wu; Jianhui Chang; Linjun Shou; Jia Li 009 (EMNLP, 2024)

Deep Reinforcement Learning for Modelling Protein Complexes. - Ziqi Gao; Tao Feng; Jiaxuan You; Chenyi Zi; Yan Zhou; Chen Zhang; Jia Li 009 (ICLR, 2024)

Protein Multimer Structure Prediction via Prompt Learning. - Ziqi Gao; Xiangguo Sun; Zijing Liu; Yu Li 003; Hong Cheng 001; Jia Li 009 (ICLR, 2024)

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases. - Yang Liu 165; Jiashun Cheng; Haihong Zhao; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009; Yu Rong 001 (ICLR, 2024)

Parameter-Efficient Fine-Tuning with Discrete Fourier Transform. - Ziqi Gao; Qichao Wang; Aochuan Chen; Zijing Liu; Bingzhe Wu; Liang Chen 001; Jia Li 009 (ICML, 2024)

A Survey of Graph Meets Large Language Model: Progress and Future Directions. - Yuhan Li 001; Zhixun Li; Peisong Wang; Jia Li 009; Xiangguo Sun; Hong Cheng 001; Jeffrey Xu Yu (IJCAI, 2024)

All in One: Multi-task Prompting for Graph Neural Networks (Extended Abstract). - Xiangguo Sun; Hong Cheng 001; Jia Li 009; Bo Liu 004; Jihong Guan (IJCAI, 2024)

GraphWiz: An Instruction-Following Language Model for Graph Computational Problems. - Nuo Chen 001; Yuhan Li 001; Jianheng Tang; Jia Li 009 (KDD, 2024)

ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs. - Yuhan Li 001; Peisong Wang; Zhixun Li; Jeffrey Xu Yu; Jia Li 009 (KDD, 2024)

Path-based Explanation for Knowledge Graph Completion. - Heng Chang; Jiangnan Ye 003; Alejo Lopez-Avila; Jinhua Du; Jia Li 009 (KDD, 2024)

Graph Intelligence with Large Language Models and Prompt Learning. - Jia Li 009; Xiangguo Sun; Yuhan Li 001; Zhixun Li; Hong Cheng 001; Jeffrey Xu Yu (KDD, 2024)

All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining. - Haihong Zhao; Aochuan Chen; Xiangguo Sun; Hong Cheng 001; Jia Li 009 (KDD, 2024)

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Broad Physical Dynamics Learning. - Zinan Zheng; Yang Liu 245; Jia Li 009; Jianhua Yao 001; Yu Rong 001 (KDD, 2024)

GLBench: A Comprehensive Benchmark for Graph with Large Language Models. - Yuhan Li 001; Peisong Wang; Xiao Zhu; Aochuan Chen; Haiyun Jiang; Deng Cai 002; Wai Kin (Victor) Chan; Jia Li 009 (NeurIPS, 2024)

Towards Stable Representations for Protein Interface Prediction. - Ziqi Gao; Zijing Liu; Yu Li 003; Jia Li 009 (NeurIPS, 2024)

UniGAD: Unifying Multi-level Graph Anomaly Detection. - Yiqing Lin; Jianheng Tang; Chenyi Zi; H. Vicky Zhao; Yuan Yao; Jia Li 009 (NeurIPS, 2024)

ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons. - Jiawen Zhang 001; Xumeng Wen; Zhenwei Zhang; Shun Zheng 001; Jia Li 009; Jiang Bian 002 (NeurIPS, 2024)

ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer. - Jiawen Zhang 001; Shun Zheng 001; Xumeng Wen; Xiaofang Zhou; Jiang Bian 002; Jia Li 009 (NeurIPS, 2024)

ProG: A Graph Prompt Learning Benchmark. - Chenyi Zi; Haihong Zhao; Xiangguo Sun; Yiqing Lin; Hong Cheng 001; Jia Li 009 (NeurIPS, 2024)

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. - Amit Roy; Juan Shu; Jia Li 009; Carl Yang 001; Olivier Elshocht; Jeroen Smeets; Pan Li 005 (WSDM, 2024)

Weakly Supervised Anomaly Detection via Knowledge-Data Alignment. - Haihong Zhao; Chenyi Zi; Yang Liu 245; Chen Zhang; Yan Zhou; Jia Li 009 (WWW, 2024)

From Good to Great: Improving Math Reasoning with Tool-Augmented Interleaf Prompting. - Nuo Chen 001; Hongguang Li; Baoyuan Wang; Jia Li 009 (CoRR, 2024)

Weakly Supervised Anomaly Detection via Knowledge-Data Alignment. - Haihong Zhao; Chenyi Zi; Yang Liu 165; Chen Zhang; Yan Zhou; Jia Li 009 (CoRR, 2024)

Compress to Impress: Unleashing the Potential of Compressive Memory in Real-World Long-Term Conversations. - Nuo Chen 001; Hongguang Li; Juhua Huang; Baoyuan Wang; Jia Li 009 (CoRR, 2024)

GraphWiz: An Instruction-Following Language Model for Graph Problems. - Nuo Chen 001; Yuhan Li 001; Jianheng Tang; Jia Li 009 (CoRR, 2024)

A Survey of Time Series Foundation Models: Generalizing Time Series Representation with Large Language Model. - Jiexia Ye; Weiqi Zhang; Ke Yi 003; Yongzi Yu; Ziyue Li 002; Jia Li 009; Fugee Tsung (CoRR, 2024)

One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient Deployments. - Ke Yi 003; Yuhui Xu; Heng Chang; Chen Tang; Yuan Meng; Tong Zhang 015; Jia Li 009 (CoRR, 2024)

DualTime: A Dual-Adapter Multimodal Language Model for Time Series Representation. - Weiqi Zhang; Jiexia Ye; Ziyue Li 002; Jia Li 009; Fugee Tsung (CoRR, 2024)

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning. - Zinan Zheng; Yang Liu 165; Jia Li 009; Jianhua Yao 001; Yu Rong 001 (CoRR, 2024)

GraphArena: Benchmarking Large Language Models on Graph Computational Problems. - Jianheng Tang; Qifan Zhang; Yuhan Li 001; Jia Li 009 (CoRR, 2024)

Parameter-Efficient Fine-Tuning via Circular Convolution. - Aochuan Chen; Ziqi Gao; Zijing Liu; Yu Li 003; Jia Li 009 (CoRR, 2024)

ControlMath: Controllable Data Generation Promotes Math Generalist Models. - Nuo Chen 001; Ning Wu; Jianhui Chang; Jia Li 009 (CoRR, 2024)

Graph Pre-Training Models Are Strong Anomaly Detectors. - Jiashun Cheng; Zinan Zheng; Yang Liu 165; Jianheng Tang; Hongwei Wang; Yu Rong 001; Jia Li 009; Fugee Tsung (CoRR, 2024)

Equivariant Graph Learning for High-density Crowd Trajectories Modeling. - Yang Liu 245; Zinan Zheng; Yu Rong 001; Jia Li 009 (Trans. Mach. Learn. Res., 2024)

One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient Deployments. - Ke Yi 003; Yuhui Xu; Heng Chang; Yuan Meng; Tong Zhang 015; Jia Li 009 (ACL (1), 2025)

Parameter-Efficient Fine-Tuning via Circular Convolution. - Aochuan Chen; Jiashun Cheng; Zijing Liu; Ziqi Gao; Fugee Tsung; Yu Li 003; Jia Li 009 (ACL (Findings), 2025)

Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps. - Jiashun Cheng; Aochuan Chen; Nuo Chen 001; Ziqi Gao; Yuhan Li 001; Jia Li 009; Fugee Tsung (ACL (Findings), 2025)

RelEdit: Evaluating Conceptual Knowledge Editing in Language Models via Relational Reasoning. - Yifan Niu; Miao Peng; Nuo Chen 001; Yatao Bian; Tingyang Xu; Jia Li 009 (ACL (Findings), 2025)

Compress to Impress: Unleashing the Potential of Compressive Memory in Real-World Long-Term Conversations. - Nuo Chen 001; Hongguang Li; Jianhui Chang; Juhua Huang; Baoyuan Wang; Jia Li 009 (COLING, 2025)

CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer. - Yang Liu 165; Zinan Zheng; Jiashun Cheng; Fugee Tsung; Deli Zhao; Yu Rong 001; Jia Li 009 (ICLR, 2025)

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization. - Yifan Niu; Ziqi Gao; Tingyang Xu; Yang Liu 165; Yatao Bian; Yu Rong 001; Junzhou Huang; Jia Li 009 (ICLR, 2025)

Heterophilic Graph Neural Networks Optimization with Causal Message-passing. - Botao Wang; Jia Li 009; Heng Chang; Keli Zhang; Fugee Tsung (WSDM, 2025)

G-Refer: Graph Retrieval-Augmented Large Language Model for Explainable Recommendation. - Yuhan Li 001; Xinni Zhang; Linhao Luo; Heng Chang; Yuxiang Ren; Irwin King; Jia Li 009 (WWW, 2025)

A Survey of Cross-domain Graph Learning: Progress and Future Directions. - Haihong Zhao; Chenyi Zi; Aochuan Chen; Jia Li 009 (CoRR, 2025)

Sparseformer: a Transferable Transformer with Multi-granularity Token Sparsification for Medical Time Series Classification. - Jiexia Ye; Weiqi Zhang; Ziyue Li 002; Jia Li 009; Fugee Tsung (CoRR, 2025)

A Pre-Training and Adaptive Fine-Tuning Framework for Graph Anomaly Detection. - Yunhui Liu 002; Jiashun Cheng; Jia Li 009; Fugee Tsung; Hongzhi Yin; Tieke He (CoRR, 2025)

Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey. - Zhixun Li; Bin Cao; Rui Jiao; Liang Wang 056; Ding Wang; Yang Liu 003; Dingshuo Chen; Jia Li 009; Qiang Liu 006; Yu Rong 001; Liang Wang 001; Tong-yi Zhang; et al. (CoRR, 2025)

Can LLMs Alleviate Catastrophic Forgetting in Graph Continual Learning? A Systematic Study. - Ziyang Cheng; Zhixun Li; Yuhan Li 001; Yixin Song; Kangyi Zhao; Dawei Cheng; Jia Li 009; Jeffrey Xu Yu (CoRR, 2025)

Are Time-Series Foundation Models Deployment-Ready? A Systematic Study of Adversarial Robustness Across Domains. - Jiawen Zhang 001; Zhenwei Zhang; Shun Zheng 001; Xumeng Wen; Jia Li 009; Jiang Bian 002 (CoRR, 2025)