基本情况

何向南，教授、博导，中国科学技术大学大数据学院副院长

教育背景

博士, 新加坡国立大学, 计算机学院, 导师: Min-Yen Kan 2011 年 7 月 - 2015 年 12 月

本科, 华东师范大学, 软件学院 2007 年 9 月 - 2011 年 6 月 

研究方向

推荐系统、信息检索、数据挖掘、机器学习、因果推理、多媒体

主要学术成绩

Google 学术页面：

https://scholar.google.com.sg/citations?user=X45Go24AAAAJ引用 7900 余次，h-index=39

发表 CCF A 类论文 90 余篇，其中通讯或一作 30 余篇:

- A 类会议：ACM SIGIR 24 篇，WWW 11 篇，KDD 6 篇等

- A 类期刊：IEEE Trans. on Know. Eng. (TKDE) 12 篇，ACM Trans on Info. Sys. (TOIS) 7 篇等

专利申请 20 余项


论文发表

  1. Zhang T, Fang J, Jiang H, et al. Explainable and Efficient Editing for Large Language Models[C]//THE WEB CONFERENCE 2025.
  2. Xu Y, Wang W, Zhang Y, et al. Personalized Image Generation with Large Multimodal Models[J]. arXiv preprint arXiv:2410.14170, 2024.
  3. Wu J, Xie Y, Yang Z, et al. Towards robust alignment of language models: Distributionally robustifying direct preference optimization[J]. arXiv preprint arXiv:2407.07880, 2024.
  4. Ding C, Wu J, Yuan Y, et al. Unified Parameter-Efficient Unlearning for LLMs[J]. arXiv preprint arXiv:2412.00383, 2024.
  5. Li H, Zheng C, Ding S, et al. Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference[J]. arXiv preprint arXiv:2404.19620, 2024.
  6. Li S, Liu Z, Luo Y, et al. Towards 3d molecule-text interpretation in language models[J]. arXiv preprint arXiv:2401.13923, 2024.
  7. Kong X, Wu J, Zhang A, et al. Customizing language models with instance-wise lora for sequential recommendation[J]. arXiv preprint arXiv:2408.10159, 2024.
  8. Liao J, Chen X, Fu Q, et al. Text-to-image generation for abstract concepts[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2024, 38(4): 3360-3368.
  9. Zhu X, Wang S, Lu J, et al. Boosting few-shot learning via attentive feature regularization[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2024, 38(7): 7793-7801.
  10. Yu J, Li H, Hao Y, et al. CgT-GAN: clip-guided text GAN for image captioning[C]//Proceedings of the 31st ACM International Conference on Multimedia. 2023: 2252-2263.
  11. Lu J, Wang S, Zhang X, et al. Semantic-based selection, synthesis, and supervision for few-shot learning[C]//Proceedings of the 31st ACM International Conference on Multimedia. 2023: 3569-3578.
  12. Zhang J, Bao K, Zhang Y, et al. Is chatgpt fair for recommendation? evaluating fairness in large language model recommendation[C]//Proceedings of the 17th ACM Conference on Recommender Systems. 2023: 993-999.
  13. Li H, Wu K, Zheng C, et al. Removing hidden confounding in recommendation: a unified multi-task learning approach[J]. Advances in Neural Information Processing Systems, 2023, 36: 54614-54626.
  14. Yang Z, Wu J, Wang Z, et al. Generate what you prefer: Reshaping sequential recommendation via guided diffusion[J]. Advances in Neural Information Processing Systems, 2023, 36: 24247-24261.
  15. Sui Y, Wu Q, Wu J, et al. Unleashing the power of graph data augmentation on covariate distribution shift[J]. Advances in Neural Information Processing Systems, 2023, 36: 18109-18131.
  16. Fang J, Liu W, Gao Y, et al. Evaluating post-hoc explanations for graph neural networks via robustness analysis[J]. Advances in neural information processing systems, 2023, 36: 72446-72463.
  17. Wu J, Chen J, Wu J, et al. Understanding contrastive learning via distributionally robust optimization[J]. Advances in Neural Information Processing Systems, 2023, 36: 23297-23320.
  18. Jin J, Li H, Feng F, et al. Fairly recommending with social attributes: a flexible and controllable optimization approach[J]. Advances in Neural Information Processing Systems, 2023, 36: 21454-21465.