Shanshan Ye Postdoc Researcher Department of Machine Learning Mohamed Bin Zayed University of Artificial Intelligence Address: Residential Building (Biofuel Block) - Masdar City - SE45 05 - Abu Dhabi - United Arab Emirates Email: shanshan.ye_at_mbzuai.ac.ae [Google Scholar] [OpenReview]

Biography

I am currently a postdoc researcher with the Machine Learning Department at the Mohamed Bin Zayed Unviersity of AI. I got my PhD degree in AI from University of Technology Sydney (UTS), supervised by Prof Jie Lu and Prof Guangquan Zhang. I obtained my master degree from the The University of New South Wales and bechalor degree from The University of Sydney. I am interested in robust recommender systems, foundation models and information retrieval, and trustworhty AI.

Awards

• Faculty of Engineering and Information Technology Research Scholarship - University of Technology Sydney, 2022-2026

Selected Publications

• PARS: Partial-Label-Learning-inspired Recommender Systems [paper] (oral)
  Shanshan Ye, Kezhi Lu, Guangquan Zhang, Jie Lu
  Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2026.
  

• Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning [paper]
  Ali Taheri, Alireza Taban, Qizhou Wang, Shanshan Ye, Abdolreza Mirzaei, Tongliang Liu, Bo Han
  Transactions on Machine Learning Research (TMLR), 2026.
  

• Explainable LLM Unlearning through Reasoning [paper]
  Junfeng Liao, Qizhou Wang, Shanshan Ye, Xin Yu, Ling Chen, Zhen Fang
  The Fourteenth International Conference on Learning Representations (ICLR), 2026.
  

• Towards understanding valuable preference data for large language model alignment [paper]
  Zizhuo Zhang, Qizhou Wang, Shanshan Ye, Jianing Zhu, Jiangchao Yao, Bo Han, Masashi Sugiyama
  The Fourteenth International Conference on Learning Representations (ICLR), 2026.
  

• Towards Safe Machine Unlearning: A Paradigm that Mitigates Performance Degradation [paper]
  Shanshan Ye, Jie Lu, Guangquan Zhang
  ACM Web Conference (WWW), 2025.
  

• FLUID-MMRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation [paper]
  Maolin Wang, Yutian Xiao, Binhao Wang, Sheng Zhang, Shanshan Ye, Wanyu Wang, Hongzhi Yin, Ruocheng Guo, Zenglin Xu
  The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025.
  

• Training-free LLM Merging for Multi-task Learning [paper]
  Zichuan Fu, Xian Wu, Yejing Wang, Wanyu Wang, Shanshan Ye, Hongzhi Yin, Yi Chang, Yefeng Zheng, Xiangyu Zhao
  The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.
  

• MiraGe: Multimodal Discriminative Representation Learning for Generalizable AI-Generated Image Detection [paper]
  Kuo Shi, Jie Lu, Shanshan Ye, Guangquan Zhang, Zhen Fang
  The ACM Multimedia Conference (ACM MM), 2025.
  

• DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation [paper]
  Maolin Wang, Tianshuo Wei, Sheng Zhang, Ruocheng Guo, Wanyu Wang, Shanshan Ye, Lixin Zou, Xuetao Wei, Xiangyu Zhao
  The 34th International Joint Conference on Artificial Intelligence (IJCAI), 2025.
  

• Out-of-distribution detection with virtual outlier smoothing [paper]
  Jun Nie, Yadan Luo, Shanshan Ye, Yonggang Zhang, Xinmei Tian, and Zhen Fang
  International Journal of Computer Vision (IJCV), vol. 133, pp. 724-741, 2024.
  

• Robust Recommender Systems with Rating Flip Noise [paper]
  Shanshan Ye and Jie Lu
  ACM Trans. Intelligent Systems and Technology (ACM TIST), vol. 16, no. 11, pp. 1-19, 2024.
  

• Sequence unlearning for sequential recommender systems [paper]
  Shanshan Ye and Jie Lu
  Australasian Joint Conference on Artificial Intelligence (AJCAI), 2023.
  

Academic Services

• Conference Reviewer: CVPR; ICML; NeurIPS; AAAI; IJCAI; ACM MM; ACM Web Conference; IJCNN; AJCAI

• Journal Reviewer: IEEE Transactions on Pattern Analysis and Machine Intelligence; ACM Transactions on Intelligent Systems and Technology; Knowledge-Based Systems; Neural Networks

Last update: Feb 2025