2025
TrustGLM: Evaluating the Robustness of GraphLLMs Against Prompt, Text, and Structure Attacks.
CoRR, June, 2025
Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning.
CoRR, June, 2025
MLaGA: Multimodal Large Language and Graph Assistant.
CoRR, June, 2025
Concept-Centric Token Interpretation for Vector-Quantized Generative Models.
CoRR, June, 2025
GRAPHGPT-O: Synergistic Multimodal Comprehension and Generation on Graphs.
CoRR, February, 2025
UniGLM: Training One Unified Language Model for Text-Attributed Graphs Embedding.
Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025
GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025
DimCL: Dimension-Aware Augmentation in Contrastive Learning for Recommendation.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025
2024
Graph Contrastive Learning With Personalized Augmentation.
IEEE Trans. Knowl. Data Eng., November, 2024
DIRECT: Dual Interpretable Recommendation with Multi-aspect Word Attribution.
ACM Trans. Intell. Syst. Technol., October, 2024
Integrating Entity Attributes for Error-Aware Knowledge Graph Embedding.
IEEE Trans. Knowl. Data Eng., April, 2024
Collaborative Graph Neural Networks for Attributed Network Embedding.
IEEE Trans. Knowl. Data Eng., March, 2024
Understanding Different Design Choices in Training Large Time Series Models.
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CoRR, 2024
MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction.
CoRR, 2024
UniGLM: Training One Unified Language Model for Text-Attributed Graphs.
CoRR, 2024
GraphFM: A Comprehensive Benchmark for Graph Foundation Model.
CoRR, 2024
Better Late Than Never: Formulating and Benchmarking Recommendation Editing.
CoRR, 2024
Towards a Unified Framework of Clustering-based Anomaly Detection.
CoRR, 2024
E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classification.
CoRR, 2024
Retrieval-Enhanced Knowledge Editing for Multi-Hop Question Answering in Language Models.
CoRR, 2024
DCAI: Data-centric Artificial Intelligence.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
Gradient Rewiring for Editable Graph Neural Network Training.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
Reasoning Like a Doctor: Improving Medical Dialogue Systems via Diagnostic Reasoning Process Alignment.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant.
CoRR, 2023
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint.
CoRR, 2023
Towards Personalized Preprocessing Pipeline Search.
CoRR, 2023
Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs.
Proceedings of the ACM Web Conference 2023, 2023
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023
S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023
Active Ensemble Learning for Knowledge Graph Error Detection.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023
Interest Driven Graph Structure Learning for Session-Based Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation.
Proceedings of the IEEE International Conference on Data Mining, 2023
Graph Neural Networks with Non-Recursive Message Passing.
Proceedings of the IEEE International Conference on Data Mining, 2023
ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs.
Proceedings of the IEEE International Conference on Data Mining, 2023
Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection.
Proceedings of the IEEE International Conference on Data Mining, 2023
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Homophily-enhanced Structure Learning for Graph Clustering.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
2022
MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs.
CoRR, 2022
Unseen Anomaly Detection on Networks via Multi-Hypersphere Learning.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022
DreamShard: Generalizable Embedding Table Placement for Recommender Systems.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Analysis Of Acknowledgments of Libraries in the Journal Literature Using Machine Learning.
Proceedings of the Crisis, Transition, Resilience: Re-imagining an information resilient society, 2022
2021
Individuality- and Commonality-Based Multiview Multilabel Learning.
IEEE Trans. Cybern., 2021
Sparse-Interest Network for Sequential Recommendation.
Proceedings of the WSDM '21, 2021
Temporal Augmented Graph Neural Networks for Session-Based Recommendations.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021
Subtractive Aggregation for Attributed Network Anomaly Detection.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021
Dynamic Memory based Attention Network for Sequential Recommendation.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Learning to Hash with Graph Neural Networks for Recommender Systems.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020
2019
Deep Representation Learning for Social Network Analysis.
Frontiers Big Data, 2019
Weighted samples based semi-supervised classification.
Appl. Soft Comput., 2019
Is a Single Vector Enough?: Exploring Node Polysemy for Network Embedding.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
2018
Multi-view Weak-label Learning based on Matrix Completion.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018
Incomplete Multi-View Weak-Label Learning.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
2017
Multi-Label Classification Based on Low Rank Representation for Image Annotation.
Remote. Sens., 2017
Semi-supervised multi-label classification using incomplete label information.
Neurocomputing, 2017
Semi-Supervised Multi-Label Dimensionality Reduction Based on Dependence Maximization.
IEEE Access, 2017