b'Jiliang Tang'

research

∙ 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, ...

0 Wei Jin, et al. ∙

research

∙ 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-...

0 Zhikai Chen, et al. ∙

research

∙ 07/05/2023

Recommender Systems in the Era of Large Language Models (LLMs)

With the prosperity of e-commerce and web applications, Recommender Syst...

0 Wenqi Fan, et al. ∙

research

∙ 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 ...

8 Juanhui Li, et al. ∙

research

∙ 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...

6 Jiatong Li, et al. ∙

research

∙ 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...

20 Haitao Mao, et al. ∙

research

∙ 05/25/2023

DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models

Recently, Generative Diffusion Models (GDMs) have showcased their remark...

0 Yingqian Cui, et al. ∙

research

∙ 05/24/2023

Sharpness-Aware Data Poisoning Attack

Recent research has highlighted the vulnerability of Deep Neural Network...

0 Pengfei He, et al. ∙

research

∙ 03/01/2023

Single-Cell Multimodal Prediction via Transformers

The recent development of multimodal single-cell technology has made the...

13 Wenzhuo Tang, et al. ∙

research

∙ 02/10/2023

Toward Degree Bias in Embedding-Based Knowledge Graph Completion

A fundamental task for knowledge graphs (KGs) is knowledge graph complet...

6 Harry Shomer, et al. ∙

research

∙ 02/06/2023

Generative Diffusion Models on Graphs: Methods and Applications

Diffusion models, as a novel generative paradigm, have achieved remarkab...

3 Wenqi Fan, et al. ∙

research

∙ 10/19/2022

Whole Page Unbiased Learning to Rank

The page presentation biases in the information retrieval system, especi...

7 Haitao Mao, et al. ∙

research

∙ 10/18/2022

Transferable Unlearnable Examples

With more people publishing their personal data online, unauthorized dat...

5 Jie Ren, et al. ∙

research

∙ 10/18/2022

Towards Fair Classification against Poisoning Attacks

Fair classification aims to stress the classification models to achieve ...

5 Han Xu, et al. ∙

research

∙ 10/17/2022

Probabilistic Categorical Adversarial Attack Adversarial Training

The existence of adversarial examples brings huge concern for people to ...

15 Pengfei He, et al. ∙

research

∙ 10/17/2022

Test-Time Training for Graph Neural Networks

Graph Neural Networks (GNNs) have made tremendous progress in the graph ...

3 Yiqi Wang, et al. ∙

research

∙ 10/07/2022

Empowering Graph Representation Learning with Test-Time Graph Transformation

As powerful tools for representation learning on graphs, graph neural ne...

28 Wei Jin, et al. ∙

research

∙ 08/30/2022

Learning Representations for Hyper-Relational Knowledge Graphs

Knowledge graphs (KGs) have gained prominence for their ability to learn...

7 Harry Shomer, et al. ∙

research

∙ 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...

3 Lixin Zou, et al. ∙

research

∙ 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...

28 Zitao Liu, et al. ∙

research

∙ 06/15/2022

Condensing Graphs via One-Step Gradient Matching

As training deep learning models on large dataset takes a lot of time an...

12 Wei Jin, et al. ∙

research

∙ 06/15/2022

Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective

Recent years have witnessed remarkable success achieved by graph neural ...

11 Wei Jin, et al. ∙

research

∙ 06/01/2022

Defense Against Gradient Leakage Attacks via Learning to Obscure Data

Federated learning is considered as an effective privacy-preserving lear...

5 Yuxuan Wan, et al. ∙

research

∙ 05/21/2022

Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?

Knowledge graphs (KGs) facilitate a wide variety of applications due to ...

15 Juanhui Li, et al. ∙

research

∙ 05/02/2022

Enhancing Adversarial Training with Feature Separability

Deep Neural Network (DNN) are vulnerable to adversarial attacks. As a co...

2 Yaxin Li, et al. ∙

research

∙ 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 ...

12 Enyan Dai, et al. ∙

research

∙ 04/03/2022

Graph Enhanced BERT for Query Understanding

Query understanding plays a key role in exploring users' search intents ...

0 Juanhui Li, et al. ∙

research

∙ 03/03/2022

Graph Neural Networks for Multimodal Single-Cell Data Integration

Recent advances in multimodal single-cell technologies have enabled simu...

35 Hongzhi Wen, et al. ∙

research

∙ 12/14/2021

An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering

Graph neural networks (GNNs) have been widely applied in the recommendat...

4 Yiqi Wang, et al. ∙

research

∙ 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...

0 Jamell Dacon, et al. ∙

research

∙ 08/12/2021

Graph Trend Networks for Recommendations

Recommender systems aim to provide personalized services to users and ar...

13 Wenqi Fan, et al. ∙

research

∙ 08/10/2021

Decentralized Composite Optimization with Compression

Decentralized optimization and communication compression have exhibited ...

0 Yao Li, et al. ∙

research

∙ 08/07/2021

Jointly Attacking Graph Neural Network and its Explanations

Graph Neural Networks (GNNs) have boosted the performance for many graph...

23 Wenqi Fan, et al. ∙

research

∙ 07/28/2021

Imbalanced Adversarial Training with Reweighting

Adversarial training has been empirically proven to be one of the most e...

0 Wentao Wang, et al. ∙

research

∙ 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...

0 Qiongqiong Liu, et al. ∙

research

∙ 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...

0 Yang Hao, et al. ∙

research

∙ 07/12/2021

Trustworthy AI: A Computational Perspective

In the past few decades, artificial intelligence (AI) technology has exp...

35 Haochen Liu, et al. ∙

research

∙ 07/05/2021

Elastic Graph Neural Networks

While many existing graph neural networks (GNNs) have been proven to per...

0 Xiaorui Liu, et al. ∙

research

∙ 06/12/2021

AutoLoss: Automated Loss Function Search in Recommendations

Designing an effective loss function plays a crucial role in training de...

11 Xiangyu Zhao, et al. ∙

research

∙ 06/11/2021

Is Homophily a Necessity for Graph Neural Networks?

Graph neural networks (GNNs) have shown great prowess in learning repres...

0 Yao Ma, et al. ∙

research

∙ 06/10/2021

Automated Self-Supervised Learning for Graphs

Graph self-supervised learning has gained increasing attention due to it...

10 Wei Jin, et al. ∙

research

∙ 06/09/2021

Towards the Memorization Effect of Neural Networks in Adversarial Training

Recent studies suggest that “memorization” is one important factor for o...

17 Han Xu, et al. ∙

research

∙ 05/10/2021

Graph Feature Gating Networks

Graph neural networks (GNNs) have received tremendous attention due to t...

38 Wei Jin, et al. ∙

research

∙ 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...

11 Haochen Liu, et al. ∙

research

∙ 11/19/2020

Node Similarity Preserving Graph Convolutional Networks

Graph Neural Networks (GNNs) have achieved tremendous success in various...

26 Wei Jin, et al. ∙

research

∙ 10/31/2020

Personalized Multimodal Feedback Generation in Education

The automatic evaluation for school assignments is an important applicat...

0 Haochen Liu, et al. ∙

research

∙ 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...

0 Han Xu, et al. ∙

research

∙ 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...

0 Yao Ma, et al. ∙

research

∙ 09/28/2020

Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning

Dialogue systems play an increasingly important role in various aspects ...

7 Haochen Liu, et al. ∙

research

∙ 09/23/2020

Representation Learning from Limited Educational Data with Crowdsourced Labels

Representation learning has been proven to play an important role in the...

1 Wentao Wang, et al. ∙

Jiliang Tang

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