An Zhang

发表

Reinforced Causal Explainer for Graph Neural Networks

Y. Wu, Xiangnan He, Xiang Wang, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Differentiable Invariant Causal Discovery

Xiangnan He, Xiang Wang, Tat-Seng Chua, 2022, ArXiv.

Adversarial Causal Augmentation for Graph Covariate Shift

Xiangnan He, Xiang Wang, Yongduo Sui, 2022, ArXiv.

Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering

Xiang Wang, An Zhang, Tat-Seng Chua, 2022, ArXiv.

Discovering Invariant Rationales for Graph Neural Networks

Xiangnan He, Xiang Wang, Tat-Seng Chua, 2022, ICLR.

Cooperative Explanations of Graph Neural Networks

Xiangnan He, Xiang Wang, Tat-Seng Chua, 2023, WSDM.

Deconfounding to Explanation Evaluation in Graph Neural Networks

Xiangnan He, Xiang Wang, Fuli Feng, 2022, ArXiv.

Towards Multi-Grained Explainability for Graph Neural Networks

Xiangnan He, Xiang Wang, Tat-Seng Chua, 2021, NeurIPS.

Disentangled Graph Collaborative Filtering

Xiangnan He, Tat-Seng Chua, Tong Xu, 2020, SIGIR.

Let Invariant Rationale Discovery Inspire Graph Contrastive Learning

Y. Wu, Xiangnan He, Xiang Wang, 2022, ICML.

Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering

Xiang Wang, Tat-Seng Chua, An Zhang, 2022, NeurIPS.

CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation

Xiang Wang, Yunshan Ma, Tat-Seng Chua, 2022, KDD.

Discovering Dynamic Causal Space for DAG Structure Learning

Xiang Wang, F. Liu, Yueqi Duan, 2023, ArXiv.

Invariant Collaborative Filtering to Popularity Distribution Shift

Yancheng Yuan, Xiang Wang, An Zhang, 2023, WWW.

Boosting Causal Discovery via Adaptive Sample Reweighting

Xiang Wang, Tat-Seng Chua, An Zhang, 2023, ICLR.

Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation

Xiang Wang, Yin-wei Wei, An Zhang, 2023, ACM Multimedia.

Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting

Xiang Wang, Tat-Seng Chua, An Zhang, 2023, ArXiv.

Discovering Dynamic Causal Space for DAG Structure Learning

Xiang Wang, F. Liu, Yueqi Duan, 2023, KDD.

Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss

An Zhang, Leheng Sheng, Zhibo Cai, 2023, NeurIPS.

Large Language Model Can Interpret Latent Space of Sequential Recommender

Jiancan Wu, An Zhang, Jizhi Zhang, 2023, ArXiv.

Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift

Xiangnan He, Xiang Wang, Yongduo Sui, 2022, NeurIPS.

Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules

An Zhang, Zhiyuan Liu, Xiang Wang, 2023, NeurIPS.

Redundancy-aware Transformer for Video Question Answering

Xiang Wang, An Zhang, Xun Yang, 2023, ACM Multimedia.

Towards Goal-oriented Intelligent Tutoring Systems in Online Education

An Zhang, Zifeng Ren, Tat-Seng Chua, 2023, ArXiv.

On Generative Agents in Recommendation

An Zhang, Leheng Sheng, Xiang Wang, 2023, arXiv.org.

ProtT3: Protein-to-Text Generation for Text-based Protein Understanding

An Zhang, Zhiyuan Liu, Hao Fei, 2024, 2405.12564.

Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis

An Zhang, Junfeng Fang, Xiangnan He, 2023, NeurIPS.

Robust Collaborative Filtering to Popularity Distribution Shift

An Zhang, Wenchang Ma, Tat-seng Chua, 2023, ACM Trans. Inf. Syst..

Invariant Collaborative Filtering to Popularity Distribution Shift

Yancheng Yuan, Xiang Wang, An Zhang, 2023, WWW.

CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation

Xiang Wang, Yunshan Ma, An Zhang, 2022, KDD.

ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining

An Zhang, Zhiyuan Liu, Xiang Wang, 2024, arXiv.org.

ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction

An Zhang, Zhiyuan Liu, Xiang Wang, 2023, EMNLP.

ALI-Agent: Assessing LLMs' Alignment with Human Values via Agent-based Evaluation

An Zhang, Tat-Seng Chua, Jingnan Zheng, 2024, ArXiv.

Large Language Model Powered Agents in the Web

An Zhang, Yang Deng, Tat-Seng Chua, 2024, WWW.

General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout

An Zhang, Wenchang Ma, Leheng Sheng, 2024, WWW.

Disentangling Masked Autoencoders for Unsupervised Domain Generalization

An Zhang, Xiang Wang, Tat-Seng Chua, 2024, ArXiv.