An Zhang

According to our database, An Zhang authored at least 49 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Robust Collaborative Filtering to Popularity Distribution Shift.

An Zhang, Wenchang Ma, Jingnan Zheng, Xiang Wang, Tat-Seng Chua

ACM Trans. Inf. Syst., May, 2024

Safe + Safe = Unsafe? Exploring How Safe Images Can Be Exploited to Jailbreak Large Vision-Language Models.

Chenhang Cui, Gelei Deng, An Zhang, Jingnan Zheng, Yicong Li, Lianli Gao, Tianwei Zhang, Tat-Seng Chua

CoRR, 2024

Large Language Models Empower Personalized Valuation in Auction.

Jie Sun, Tianyu Zhang, Houcheng Jiang, Kexin Huang, Chi Luo, Junkang Wu, Jiancan Wu, An Zhang, Xiang Wang

CoRR, 2024

Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment.

Chenhang Cui, An Zhang, Yiyang Zhou, Zhaorun Chen, Gelei Deng, Huaxiu Yao, Tat-Seng Chua

CoRR, 2024

Generate and Instantiate What You Prefer: Text-Guided Diffusion for Sequential Recommendation.

Guoqing Hu, Zhengyi Yang, Zhibo Cai, An Zhang, Xiang Wang

CoRR, 2024

Preference Diffusion for Recommendation.

Shuo Liu, An Zhang, Guoqing Hu, Hong Qian, Tat-Seng Chua

CoRR, 2024

Neuron-Level Sequential Editing for Large Language Models.

Houcheng Jiang, Junfeng Fang, Tianyu Zhang, An Zhang, Ruipeng Wang, Tao Liang, Xiang Wang

CoRR, 2024

Text-guided Diffusion Model for 3D Molecule Generation.

Yanchen Luo, Junfeng Fang, Sihang Li, Zhiyuan Liu, Jiancan Wu, An Zhang, Wenjie Du, Xiang Wang

CoRR, 2024

One-step Noisy Label Mitigation.

Hao Li, Jiayang Gu, Jingkuan Song, An Zhang, Lianli Gao

CoRR, 2024

MASKDROID: Robust Android Malware Detection with Masked Graph Representations.

Jingnan Zheng, Jiaohao Liu, An Zhang, Jun Zeng, Ziqi Yang, Zhenkai Liang, Tat-Seng Chua

CoRR, 2024

Customizing Language Models with Instance-wise LoRA for Sequential Recommendation.

Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, Xiangnan He

CoRR, 2024

Language Models Encode Collaborative Signals in Recommendation.

Leheng Sheng, An Zhang, Yi Zhang, Yuxin Chen, Xiang Wang, Tat-Seng Chua

CoRR, 2024

On Softmax Direct Preference Optimization for Recommendation.

Yuxin Chen, Junfei Tan, An Zhang, Zhengyi Yang, Leheng Sheng, Enzhi Zhang, Xiang Wang, Tat-Seng Chua

CoRR, 2024

Hello Again! LLM-powered Personalized Agent for Long-term Dialogue.

Hao Li, Chenghao Yang, An Zhang, Yang Deng, Xiang Wang, Tat-Seng Chua

CoRR, 2024

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

Jingnan Zheng, Han Wang, An Zhang, Tai D. Nguyen, Jun Sun, Tat-Seng Chua

CoRR, 2024

TrustLOG: The Second Workshop on Trustworthy Learning on Graphs.

Jingrui He, Jian Kang, Fatemeh Nargesian, Haohui Wang, An Zhang, Dawei Zhou

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Large Language Model Powered Agents in the Web.

Yang Deng, An Zhang, Yankai Lin, Xu Chen, Ji-Rong Wen, Tat-Seng Chua

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

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

An Zhang, Wenchang Ma, Pengbo Wei, Leheng Sheng, Xiang Wang

Proceedings of the ACM on Web Conference 2024, 2024

On Generative Agents in Recommendation.

An Zhang, Yuxin Chen, Leheng Sheng, Xiang Wang, Tat-Seng Chua

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Large Language Model Powered Agents for Information Retrieval.

An Zhang, Yang Deng, Yankai Lin, Xu Chen, Ji-Rong Wen, Tat-Seng Chua

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

MaskDroid: Robust Android Malware Detection with Masked Graph Representations.

Jingnan Zheng, Jiahao Liu, An Zhang, Jun Zeng, Ziqi Yang, Zhenkai Liang, Tat-Seng Chua

Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, 2024

Disentangling Masked Autoencoders for Unsupervised Domain Generalization.

An Zhang, Han Wang, Xiang Wang, Tat-Seng Chua

Proceedings of the Computer Vision - ECCV 2024, 2024

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

Zhiyuan Liu, An Zhang, Hao Fei, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

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

Zhiyuan Liu, Yaorui Shi, An Zhang, Sihang Li, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Reinforced Causal Explainer for Graph Neural Networks.

Xiang Wang, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He, Tat-Seng Chua

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Towards Goal-oriented Intelligent Tutoring Systems in Online Education.

Yang Deng, Zifeng Ren, An Zhang, Wenqiang Lei, Tat-Seng Chua

CoRR, 2023

Large Language Model Can Interpret Latent Space of Sequential Recommender.

Zhengyi Yang, Jiancan Wu, Yanchen Luo, Jizhi Zhang, Yancheng Yuan, An Zhang, Xiang Wang, Xiangnan He

CoRR, 2023

On Generative Agents in Recommendation.

An Zhang, Leheng Sheng, Yuxin Chen, Hao Li, Yang Deng, Xiang Wang, Tat-Seng Chua

CoRR, 2023

Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting.

An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua

CoRR, 2023

Invariant Collaborative Filtering to Popularity Distribution Shift.

An Zhang, Jingnan Zheng, Xiang Wang, Yancheng Yuan, Tat-Seng Chua

Proceedings of the ACM Web Conference 2023, 2023

Cooperative Explanations of Graph Neural Networks.

Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss.

An Zhang, Leheng Sheng, Zhibo Cai, Xiang Wang, Tat-Seng Chua

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules.

Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation.

Wei Ji, Xiangyan Liu, An Zhang, Yinwei Wei, Yongxin Ni, Xiang Wang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Redundancy-aware Transformer for Video Question Answering.

Yicong Li, Xun Yang, An Zhang, Chun Feng, Xiang Wang, Tat-Seng Chua

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Discovering Dynamic Causal Space for DAG Structure Learning.

Fangfu Liu, Wenchang Ma, An Zhang, Xiang Wang, Yueqi Duan, Tat-Seng Chua

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Boosting Causal Discovery via Adaptive Sample Reweighting.

An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua

Proceedings of the Eleventh International Conference on Learning Representations, 2023

ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction.

Yaorui Shi, An Zhang, Enzhi Zhang, Zhiyuan Liu, Xiang Wang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Adversarial Causal Augmentation for Graph Covariate Shift.

Yongduo Sui, Xiang Wang, Jiancan Wu, An Zhang, Xiangnan He

CoRR, 2022

Differentiable Invariant Causal Discovery.

Yu Wang, An Zhang, Xiang Wang, Xiangnan He, Tat-Seng Chua

CoRR, 2022

Deconfounding to Explanation Evaluation in Graph Neural Networks.

Ying-Xin Wu, Xiang Wang, An Zhang, Xia Hu, Fuli Feng, Xiangnan He, Tat-Seng Chua

CoRR, 2022

Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering.

An Zhang, Wenchang Ma, Xiang Wang, Tat-Seng Chua

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation.

Yunshan Ma, Yingzhi He, An Zhang, Xiang Wang, Tat-Seng Chua

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Let Invariant Rationale Discovery Inspire Graph Contrastive Learning.

Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua

Proceedings of the International Conference on Machine Learning, 2022

Discovering Invariant Rationales for Graph Neural Networks.

Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

A-FMI: Learning Attributions from Deep Networks via Feature Map Importance.

An Zhang, Xiang Wang, Chengfang Fang, Jie Shi, Tat-Seng Chua, Zehua Chen

CoRR, 2021

Towards Multi-Grained Explainability for Graph Neural Networks.

Xiang Wang, Ying-Xin Wu, An Zhang, Xiangnan He, Tat-Seng Chua

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Disentangled Graph Collaborative Filtering.

Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, Tat-Seng Chua

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020