Publications [Google Scholar]

2025

NeurIPS'25	The Emergence of Abstract Thought in Large Language Models Beyond Any Language Yuxin Chen, Yiran Zhao, Yang Zhang, An Zhang*, Kenji Kawaguchi, Shafiq Joty, Junnan Li, Tat-Seng Chua, Michael Qizhe Shieh, Wenxuan Zhang
NeurIPS'25	Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation Guoqing Hu, An Zhang*, Shuchang Liu, Wenyu Mao, Jiancan Wu, Xun Yang, Xiang Li, Lantao Hu, Han Li, Kun Gai, Xiang Wang
NeurIPS'25	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
NeurIPS'25	On Reasoning Strength Planning in Large Reasoning Models Leheng Sheng, An Zhang*, Zijian Wu, Weixiang Zhao, Changshuo Shen, Yi Zhang, Xiang Wang, Tat-Seng Chua
NeurIPS'25	RSafe: Incentivizing Proactive Reasoning to Build Robust and Adaptive LLM Safeguards Jingnan Zheng, Xiangtian Ji, Yijun Lu, Chenhang Cui, Weixiang Zhao, Gelei Deng, Zhenkai Liang, An Zhang*, Tat-Seng Chua
NeurIPS'25	Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning Yaorui Shi, Sihang Li, Chang Wu, Zhiyuan Liu, Junfeng Fang, Hengxing Cai, An Zhang, Xiang Wang
NeurIPS'25	AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Yu Shang, Peijie Liu, Yuwei Yan, Zijing Wu, Leheng Sheng, Yuanqing Yu, Chumeng Jiang, An Zhang, Fengli Xu, Yu Wang, Min Zhang, Yong Li
KDD'25	LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Yingzhi He, Xiaohao Liu, An Zhang*, Yunshan Ma, Tat-Seng Chua
SIGIR'25	AlphaFuse: Learn ID Embeddings for Sequential Recommendation in Null Space of Language Embeddings Guoqing Hu, An Zhang*, Shuo Liu, Xiang Wang, Tat-Seng Chua
ICLR'25	Language Representations Can be What Recommenders Need: Findings and Potentials Leheng Sheng, An Zhang*, Yi Zhang, Yuxin Chen, Xiang Wang, Tat-Seng Chua
ICLR'25	Preference Diffusion for Recommendation Shuo Liu, An Zhang*, Guoqing Hu, Hong Qian, Tat-Seng Chua
ICLR'25	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

2024

NeurIPS'24	On Softmax Direct Preference Optimization for Recommendation Yuxin Chen, Junfei Tan, An Zhang*, Zhengyi Yang, Leheng Sheng, Enzhi Zhang, Xiang Wang, Tat-Seng Chua
NeurIPS'24	Customizing Language Models with Instance-wise LoRA for Sequential Recommendation Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, Xiangnan He
NeurIPS'24	Towards Neuron Attributions in Multi-Modal Large Language Models Junfeng Fang, Zac Bi, Ruipeng Wang, Houcheng Jiang, Yuan Gao, Kun Wang, An Zhang, Jie Shi, Xiang Wang, Tat-Seng Chua
NeurIPS'24	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
ACL'24	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
WWW'24	General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout An Zhang, Wenchang Ma, Pengbo Wei, Leheng Sheng, Xiang Wang
SIGIR'24	On Generative Agents in Recommendation An Zhang, Yuxin Chen, Leheng Sheng, Xiang Wang, Tat-Seng Chua
SIGIR'24	Large Language Model Powered Agents for Information Retrieval (Tutorial) An Zhang, Yang Deng, Yankai Lin, Xu Chen, Ji-Rong Wen, Tat-Seng Chua
WWW'24	Large Language Model Powered Agents in the Web (Tutorial, Companion Volume) Yang Deng, An Zhang, Yankai Lin, Xu Chen, Ji-Rong Wen, Tat-Seng Chua

2023

TOIS'23	Robust Collaborative Filtering to Popularity Distribution Shift An Zhang, Wenchang Ma, Jingnan Zheng, Xiang Wang, Tat-Seng Chua
EMNLP'23	ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction Yaorui Shi, An Zhang*, Enzhi Zhang, Zhiyuan Liu, Xiang Wang
NeurIPS'23	Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss An Zhang, Leheng Sheng, Zhibo Cai, Xiang Wang, Tat-Seng Chua
NeurIPS'23	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
NeurIPS'23	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
ACM MM'23	Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation Wei Ji, Xiangyan Liu, An Zhang*, Yinwei Wei, Yongxin Ni, Xiang Wang
ACM MM'23	Redundancy-aware Transformer for Video Question Answering Yicong Li, Xun Yang, An Zhang, Chun Feng, Xiang Wang, Tat-Seng Chua
KDD'23	Discovering Dynamic Causal Space for DAG Structure Learning Fangfu Liu, Wenchang Ma, An Zhang*, Xiang Wang, Yueqi Duan, Tat-Seng Chua
WWW'23	Invariant Collaborative Filtering to Popularity Distribution Shift An Zhang, Jingnan Zheng, Xiang Wang, Yancheng Yuan, Tat-Seng Chua
ICLR'23	Boosting Causal Discovery via Adaptive Sample Reweighting An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua
WSDM'23	Cooperative Explanations of Graph Neural Networks Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua

2022

NeurIPS'22	Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering. An Zhang, Wenchang Ma, Xiang Wang, Tat-Seng Chua
ICML'22	Let Invariant Rationale Discovery inspire Graph Contrastive Learning. Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua.
ICLR'22	Discovering invariant rationales for graph neural networks. YingXin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua.
TPAMI'22	Reinforced Causal Explainer for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang*, Fuli Feng, Xiangnan He, Tat-Seng Chua
KDD'22	CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation. Yunshan Ma, Yingzhi He, An Zhang*, Xiang Wang, Tat-Seng Chua.

2021

NeurIPS'21

Towards Multi-Grained Explainability for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang, Xiangnan He, Tat-Seng Chua

2020

SIGIR'20

Disentangled Graph Collaborative Filtering Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, Tat-Seng Chua.