Zhang, An

29 publications

ICLR 2026 AlphaAlign: Incentivizing Safety Alignment with Extremely Simplified Reinforcement Learning Yi Zhang, An Zhang, XiuYu Zhang, Leheng Sheng, Yuxin Chen, Zhenkai Liang, Xiang Wang

ICLR 2026 AlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint Leheng Sheng, Changshuo Shen, Weixiang Zhao, Junfeng Fang, Xiaohao Liu, Zhenkai Liang, Xiang Wang, An Zhang, Tat-Seng Chua

ICLR 2026 Denoising Neural Reranker for Recommender Systems Wenyu Mao, Shuchang Liu, HailanYang, Xiaobei Wang, Xiaoyu Yang, Xu Gao, Xiang Li, Lantao Hu, Han Li, Kun Gai, An Zhang, Xiang Wang

ICLR 2026 Look Back to Reason Forward: Revisitable Memory for Long-Context LLM Agents Yaorui Shi, Yuxin Chen, Siyuan Wang, Sihang Li, Hengxing Cai, Qi Gu, Xiang Wang, An Zhang

ICLR 2026 Quantile Advantage Estimation: Stabilizing RLVR for LLM Reasoning Junkang Wu, Kexin Huang, Jiancan Wu, An Zhang, Xiang Wang, Xiangnan He

NeurIPS 2025 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

NeurIPS 2025 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

ICLR 2025 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

ICLR 2025 Language Representations Can Be What Recommenders Need: Findings and Potentials Leheng Sheng, An Zhang, Yi Zhang, Yuxin Chen, Xiang Wang, Tat-Seng Chua

NeurIPS 2025 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

ICLR 2025 Preference Diffusion for Recommendation Shuo Liu, An Zhang, Guoqing Hu, Hong Qian, Tat-Seng Chua

NeurIPS 2025 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 2025 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 2025 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 2025 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 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

NeurIPS 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

ECCV 2024 Disentangling Masked Autoencoders for Unsupervised Domain Generalization An Zhang, Han Wang, Xiang Wang, Tat-Seng Chua

NeurIPS 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

NeurIPS 2024 Towards Neuron Attributions in Multi-Modal Large Language Models Junfeng Fang, Zongze Bi, Ruipeng Wang, Houcheng Jiang, Yuan Gao, Kun Wang, An Zhang, Jie Shi, Xiang Wang, Tat-Seng Chua

ICLR 2023 Boosting Causal Discovery via Adaptive Sample Reweighting An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua

NeurIPS 2023 Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss An Zhang, Leheng Sheng, Zhibo Cai, Xiang Wang, Tat-Seng Chua

NeurIPS 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

NeurIPS 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

ICLR 2022 Discovering Invariant Rationales for Graph Neural Networks Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua

NeurIPS 2022 Incorporating Bias-Aware Margins into Contrastive Loss for Collaborative Filtering An Zhang, Wenchang Ma, Xiang Wang, Tat-Seng Chua

ICML 2022 Let Invariant Rationale Discovery Inspire Graph Contrastive Learning Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua

NeurIPS 2022 SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments Mohan Zhang, Xiaozhou Wang, Benjamin Decardi-Nelson, Bo Song, An Zhang, Jinfeng Liu, Sile Tao, Jiayi Cheng, Xiaohong Liu, Dengdeng Yu, Matthew Poon, Animesh Garg

NeurIPS 2021 Towards Multi-Grained Explainability for Graph Neural Networks Xiang Wang, Yingxin Wu, An Zhang, Xiangnan He, Tat-Seng Chua