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09/20/2023
Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting
With the acceleration of urbanization, traffic forecasting has become an...
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09/18/2023
PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction
In the era of information explosion, spatio-temporal data mining serves ...
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07/05/2023
Recommender Systems in the Era of Large Language Models (LLMs)
With the prosperity of e-commerce and web applications, Recommender Syst...
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05/10/2023
Multi-Prompt with Depth Partitioned Cross-Modal Learning
In recent years, soft prompt learning methods have been proposed to fine...
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10/17/2022
Test-Time Training for Graph Neural Networks
Graph Neural Networks (GNNs) have made tremendous progress in the graph ...
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09/21/2022
A Comprehensive Survey on Trustworthy Recommender Systems
As one of the most successful AI-powered applications, recommender syste...
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05/21/2022
Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
Knowledge graphs (KGs) facilitate a wide variety of applications due to ...
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02/16/2022
HousE: Knowledge Graph Embedding with Householder Parameterization
The effectiveness of knowledge graph embedding (KGE) largely depends on ...
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12/14/2021
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering
Graph neural networks (GNNs) have been widely applied in the recommendat...
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10/25/2021
Gophormer: Ego-Graph Transformer for Node Classification
Transformers have achieved remarkable performance in a myriad of fields ...
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08/10/2021
Localized Graph Collaborative Filtering
User-item interactions in recommendations can be naturally de-noted as a...
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07/12/2021
Trustworthy AI: A Computational Perspective
In the past few decades, artificial intelligence (AI) technology has exp...
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07/05/2021
Elastic Graph Neural Networks
While many existing graph neural networks (GNNs) have been proven to per...
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11/19/2020
Node Similarity Preserving Graph Convolutional Networks
Graph Neural Networks (GNNs) have achieved tremendous success in various...
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09/28/2020
Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning
Dialogue systems play an increasingly important role in various aspects ...
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06/28/2020
Graph Convolutional Networks against Degree-Related Biases
In recent years, Graph Convolutional Networks (GCNs) show competitive pe...
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06/17/2020
Self-supervised Learning on Graphs: Deep Insights and New Direction
The success of deep learning notoriously requires larger amounts of cost...
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05/22/2020
Non-IID Graph Neural Networks
Graph classification is an important task on graph-structured data with ...
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03/02/2020