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王子泰
王子泰 助理研究员
电子邮箱: wangzitai@ict.ac.cn
通讯地址: 北京市海淀区科学院南路6号
研究方向: 机器学习与数据挖掘
个人简介

王子泰,中国科学院计算技术研究所博士后/特别研究助理,研究方向为机器学习与数据挖掘,包括但不限于复杂指标优化、长尾学习、开放域学习、大模型高效学习,已在 CCF-A 类期刊/会议发表论文 20 余篇,其中TPAMI/IJCV/ICML/NeurIPS 10 余篇,并有 7 篇入选 Oral/Spotlight 论文,获 CVPR 国际竞赛冠军;入选中国图象图形学学会博士学位论文激励计划(CSIG优博)、ACM北京分会优秀博士学位论文奖、中国科学院院长优秀奖等;博士后创新人才支持计划(博新计划)、国家自然科学基金青年项目C类、北京市自然科学基金-海淀原始创新联合基金培育项目、中国科学院特别研究助理资助项目、中国博士后科学基金面上项目资助;担任 TPAMI、ICML、NeurIPS 等 CCF-A 类期刊/会议审稿人,被评为 NeurIPS Top 审稿人。

英文主页:https://wang22ti.github.io/

谷歌学术主页:https://scholar.google.com/citations?user=45qZ_LcAAAAJ


协助指导学生情况:

• 华  聪(博士生,导师:黄庆明):ICML 2025, ICML 2024(中国科协青年科技人才培育工程博士生专项计划)

• 李斯骢(博士生,导师:黄庆明): ICML 2025

• 孙宇辰(硕士,导师:许倩倩): AAAI 2025, ACM MM 2023 (Oral), 计算机学报(中国图象图形学学会优硕、北京图象图形学学会优硕,毕业去向:京东)

• 何俊伟(硕士,导师:黄庆明):ACM MM 2024, AAAI 2024(国家奖学金,毕业去向:字节跳动)

• 孟本源(硕士生,导师:黄庆明):CVPR 2026, NeurIPS 2024 (Spotlight), NeurIPS 2024

• 许志康(硕士生,导师:许倩倩):CVPR 2026

• 冯迪夫(硕士生,导师:黄庆明):AAAI 2026

• 王广辉(硕士生,导师:杨智勇):ICML 2025 (Oral)

经历

2024.07—至今     中国科学院计算技术研究所  博士后

2019.09—2024.06  中国科学院信息工程研究所  博士生

2015.09—2019.06  北京交通大学计算机与信息技术学院  本科生

学术服务
研究内容

机器学习与数据挖掘,包括但不限于复杂指标优化、长尾学习、开放域学习、大模型高效学习

邀请报告与论著

[CVPR 26] Zhikang Xu, Qianqian Xu, Zitai Wang, Cong Hua, Sicong Li, Zhiyong Yang, and Qingming Huang. Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026. (Accepted)

[CVPR 26] Benyuan Meng, Qianqian Xu, Zitai Wang, Xiaochun Cao, Longtao Huang, and Qingming Huang. Making Training-Free Diffusion Segmentors Scale with the Generative Power. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026. (Accepted)

[AAAI 26] Difu feng, Qianqian Xu, Zitai Wang, Cong Hua, Zhiyong Yang, and Qingming Huang. Quantifying the Potential to Escape Filter Bubbles: A Behavior-Aware Measure via Contrastive Simulation. AAAI Conference on Artificial Intelligence (AAAI), 2026. (Accepted)

[TPAMI 25] Zitai Wang, Qianqian Xu, Zhiyong Yang, Zhikang Xu, Linchao Zhang, Xiaochun Cao, and Qingming Huang. A Unified Perspective for Loss-Oriented Imbalanced Learning via Localization. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 48(1): 639-656, Jan. 2026.

[TPAMI 25] Zhiyong Yang, Qianqian Xu, Sicong Li, Zitai Wang, Xiaochun Cao, and Qingming Huang. DirMixE: Harnessing Test Agnostic Long-tail Recognition with Hierarchical Label Variations. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025. (Accepted, DOI: 10.1109/TPAMI.2025.3647124)

[ICML 25] Guanghui Wang, Zhiyong Yang, Zitai Wang, Shi Wang, Qianqian Xu, and Qingming Huang. ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via α-β-Divergence. International Conference on Machine Learning (ICML), 65167-65212, 2025. (Oral, 1.0%) 

[ICML 25] Cong Hua, Qianqian Xu, Zhiyong Yang, Zitai Wang, Shilong Bao, and Qingming Huang. OpenworldAUC: Towards Unified Evaluation and Optimization for Open-world Prompt Tuning. International Conference on Machine Learning (ICML), 24975-25020, 2025.

[ICML 25] Sicong Li, Qianqian Xu, Zhiyong Yang, Zitai Wang, Linchao Zhang, Xiaochun Cao, and Qingming Huang. Focal-SAM: Focal Sharpness-Aware Minimization for Long-Tailed Classification. International Conference on Machine Learning (ICML), 36624-36651, 2025.

[AAAI 25] Yuchen Sun, Qianqian Xu, Zitai Wang, Zhiyong Yang, and Junwei He. EDGE: Unknown-aware Multi-label Learning by Energy Distribution Gap Expansion. AAAI Conference on Artificial Intelligence (AAAI), 12613-12621, 2025.

[IJCV 24] Zitai Wang, Qianqian Xu, Zhiyong Yang, Peisong Wen, Yuan He, Xiaochun Cao, and Qingming Huang. Top-K Pairwise Ranking: Bridging the Gap Among Ranking-Based Measures for Multi-Label Classification. International Journal of Computer Vision (IJCV), 133(1): 211-253, Jan. 2025.

[ICML 24] Zhiyong Yang, Qianqian Xu, Zitai Wang, Sicong Li, Boyu Han, Shilong Bao, Xiaochun Cao, and Qingming Huang. Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition. International Conference on Machine Learning (ICML), 56624-56664, 2024.

[NeurIPS 24] Benyuan Meng, Qianqian Xu, Zitai Wang, Xiaochun Cao, and Qingming Huang. Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features. Annual Conference on Neural Information Processing Systems (NeurIPS), 55141-55177, 2024. (Spotlight, 2.1%)

[NeurIPS 24] Benyuan Meng, Qianqian Xu, Zitai Wang, Zhiyong Yang, Xiaochun Cao, and Qingming Huang. Suppress Content Shift: Better Diffusion Features via Off-the-Shelf Generation Techniques. Annual Conference on Neural Information Processing Systems (NeurIPS), 18910-18939, 2024.

[AAAI 24] Junwei He, Qianqian Xu, Yangbangyan Jiang, Zitai Wang, and Qingming Huang. ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection. AAAI Conference on Artificial Intelligence (AAAI), 8481-8489, 2024.

[ACM MM 24] Junwei He, Qianqian Xu, Yangbangyan Jiang, Zitai Wang, Yuchen Sun, and Qingming Huang. HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph Out-of-Distribution Detection. ACM Conference on Multimedia (ACM MM), 1544-1553, 2024.

[NeurIPS 23] Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, and Qingming Huang. A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning. Annual Conference on Neural Information Processing Systems (NeurIPS), 48417-48430, 2023. (Spotlight, 3.1%)

[ACM MM 23] Yuchen Sun, Qianqian Xu, Zitai Wang, and Qingming Huang. When Measures are Unreliable: Imperceptible Adversarial Perturbations toward Top-k Multi-Label Learning. ACM Conference on Multimedia (ACM MM), 1515-1526, 2023. (Oral, 5.4%)

[TPAMI 22] Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, and Qingming Huang. Optimizing Partial Area Under the Top-k Curve: Theory and Practice. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI, IF: 18.6), 45(4): 5053-5069, Apr. 2023. 

[NeurIPS 22] Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, and Qingming Huang. OpenAUC: Towards AUC-Oriented Open-Set Recognition. Annual Conference on Neural Information Processing Systems (NeurIPS), 25033-25045, 2022. (Spotlight, 5.4%)

[ACM MM 22] Zitai Wang, Qianqian Xu, Ke Ma, Xiaochun Cao, and Qingming Huang. Confederated Learning: Going Beyond Centralization. ACM Conference on Multimedia (ACM MM), 2939-2947, 2022. (Oral, 5.6%)

[ACM MM 21] Zitai Wang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, and Qingming Huang. Implicit feedbacks are not always favorable: Iterative Relabeled One-Class Collaborative Filtering against Noisy Interactions. ACM Conference on Multimedia (ACM MM), 3070-3078, 2021. 

[ACM MM 19] Zitai Wang, Qianqian Xu, Ke Ma, Yangbangyan Jiang, Xiaochun Cao, and Qingming Huang. Adversarial Preference Learning with Pairwise Comparisons. ACM Conference on Multimedia (ACM MM), 656-664, 2019. (Oral, 9.4%)