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07/19/2023
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
Modeling customer shopping intentions is a crucial task for e-commerce, ...
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07/07/2023
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
Learning on Graphs has attracted immense attention due to its wide real-...
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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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06/18/2023
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
Link prediction attempts to predict whether an unseen edge exists based ...
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06/11/2023
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
Molecule discovery plays a crucial role in various scientific fields, ad...
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06/02/2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Recent studies on Graph Neural Networks(GNNs) provide both empirical and...
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05/25/2023
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
Recently, Generative Diffusion Models (GDMs) have showcased their remark...
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05/24/2023
Sharpness-Aware Data Poisoning Attack
Recent research has highlighted the vulnerability of Deep Neural Network...
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03/01/2023
Single-Cell Multimodal Prediction via Transformers
The recent development of multimodal single-cell technology has made the...
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02/10/2023
Toward Degree Bias in Embedding-Based Knowledge Graph Completion
A fundamental task for knowledge graphs (KGs) is knowledge graph complet...
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02/06/2023
Generative Diffusion Models on Graphs: Methods and Applications
Diffusion models, as a novel generative paradigm, have achieved remarkab...
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10/19/2022
Whole Page Unbiased Learning to Rank
The page presentation biases in the information retrieval system, especi...
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10/18/2022
Transferable Unlearnable Examples
With more people publishing their personal data online, unauthorized dat...
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10/18/2022
Towards Fair Classification against Poisoning Attacks
Fair classification aims to stress the classification models to achieve ...
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10/17/2022
Probabilistic Categorical Adversarial Attack Adversarial Training
The existence of adversarial examples brings huge concern for people to ...
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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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10/07/2022
Empowering Graph Representation Learning with Test-Time Graph Transformation
As powerful tools for representation learning on graphs, graph neural ne...
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08/30/2022
Learning Representations for Hyper-Relational Knowledge Graphs
Knowledge graphs (KGs) have gained prominence for their ability to learn...
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07/07/2022
A Large Scale Search Dataset for Unbiased Learning to Rank
The unbiased learning to rank (ULTR) problem has been greatly advanced b...
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06/23/2022
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models
Knowledge tracing (KT) is the task of using students' historical learnin...
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06/15/2022
Condensing Graphs via One-Step Gradient Matching
As training deep learning models on large dataset takes a lot of time an...
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06/15/2022
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
Recent years have witnessed remarkable success achieved by graph neural ...
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06/01/2022
Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Federated learning is considered as an effective privacy-preserving lear...
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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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05/02/2022
Enhancing Adversarial Training with Feature Separability
Deep Neural Network (DNN) are vulnerable to adversarial attacks. As a co...
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04/18/2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Graph Neural Networks (GNNs) have made rapid developments in the recent ...
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04/03/2022
Graph Enhanced BERT for Query Understanding
Query understanding plays a key role in exploring users' search intents ...
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03/03/2022
Graph Neural Networks for Multimodal Single-Cell Data Integration
Recent advances in multimodal single-cell technologies have enabled simu...
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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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09/20/2021
What Truly Matters? Using Linguistic Cues for Analyzing the #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020
Since the fatal shooting of 17-year old Black teenager Trayvon Martin in...
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08/12/2021
Graph Trend Networks for Recommendations
Recommender systems aim to provide personalized services to users and ar...
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08/10/2021
Decentralized Composite Optimization with Compression
Decentralized optimization and communication compression have exhibited ...
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08/07/2021
Jointly Attacking Graph Neural Network and its Explanations
Graph Neural Networks (GNNs) have boosted the performance for many graph...
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07/28/2021
Imbalanced Adversarial Training with Reweighting
Adversarial training has been empirically proven to be one of the most e...
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07/15/2021
Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models
Sentence completion (SC) questions present a sentence with one or more b...
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07/15/2021
Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models
In this work, we study computational approaches to detect online dialogi...
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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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06/12/2021
AutoLoss: Automated Loss Function Search in Recommendations
Designing an effective loss function plays a crucial role in training de...
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06/11/2021
Is Homophily a Necessity for Graph Neural Networks?
Graph neural networks (GNNs) have shown great prowess in learning repres...
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06/10/2021
Automated Self-Supervised Learning for Graphs
Graph self-supervised learning has gained increasing attention due to it...
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06/09/2021
Towards the Memorization Effect of Neural Networks in Adversarial Training
Recent studies suggest that “memorization” is one important factor for o...
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05/10/2021
Graph Feature Gating Networks
Graph neural networks (GNNs) have received tremendous attention due to t...
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05/06/2021
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification
It is evident that deep text classification models trained on human data...
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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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10/31/2020
Personalized Multimodal Feedback Generation in Education
The automatic evaluation for school assignments is an important applicat...
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10/13/2020
To be Robust or to be Fair: Towards Fairness in Adversarial Training
Adversarial training algorithms have been proven to be reliable to impro...
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10/05/2020
A Unified View on Graph Neural Networks as Graph Signal Denoising
Graph Neural Networks (GNNs) have risen to prominence in learning repres...
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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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09/23/2020
