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乐博app在线登录:邬渊

职称:助理教授,博士生导师

毕业院校:加拿大卡尔顿大学

email:yuanwu@jlu.edu.cn

个人主页:

研究方向:迁移学习,机器学习泛化理论,大语言模型

乐博app在线登录:个人简介

邬渊,乐博app在线登录助理教授,博士生导师。研究方向为迁移学习,机器学习泛化理论。所涉及的应用有图像分类,图像语义分割,文本分类等。在AAAI,ECCV,ICASSP,AISTATS,TIST,IJCAI,ACL等国际会议\期刊发表多篇文章。


近几年计划的研究方向:(1) 大语言模型的评估 (The evaluation on large language models);(2) 可信大语言模型(Trustworthy large language models);(3)心理学与大语言模型的交叉研究(Applying psychology to improve large language models);(4)大模型驱动的数据增强方法(Data augmentation driven by large language models and diffusion models)。


欢迎对以上方向感兴趣的本科生、硕士生、博士生咨询!(本组2025年博士名额已满。)

乐博app在线登录:工作经历

2022.11-至今 乐博app在线登录 助理教授

乐博app在线登录:教育经历

2018.09-2022.06   加拿大卡尔顿大学 计算机科学 博士 (导师:Dr. Ahemd El-Roby, Dr. Diana Inkpen.)

2015.09-2018.07   兰州大学 软件工程 硕士 (导师:李廉)

2008.09-2012.06   北京化工大学 计算机科学与技术 学士

乐博app在线登录:论文选

详见个人Google scholar:https://scholar.google.com/citations?user=KVeRu2QAAAAJ&hl=zh-CN

部分论文信息如下:

[1] Wu, Y., & Guo, Y. (2020, April). Dual adversarial co-learning for multi-domain text classification. In Proceedings of the AAAI conference on artificial intelligence (Vol. 34, No. 04, pp. 6438-6445). (第一作者,AAAI, CCF-A, 清华A类)

[2] Wu, Y., Inkpen, D., & El-Roby, A. (2020). Dual mixup regularized learning for adversarial domain adaptation. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIX 16 (pp. 540-555). Springer International Publishing. (第一作者,ECCV, CCF-B, 清华A类)

[3] Wu, Y., Inkpen, D., & El-Roby, A. (2021, June). Mixup regularized adversarial networks for multi-domain text classification. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 7733-7737). IEEE. (第一作者,ICASSP, CCF-B, 清华B类)

[4] Wu, Y., Inkpen, D., & El-Roby, A. (2021). Towards category and domain alignment: Category-invariant feature enhancement for adversarial domain adaptation. In Proceedings of the IEEE/CVF International Conference on Computer Vision workshops (pp. 132-141). (第一作者, ICCV workshop)

[5] Wu, Y., Inkpen, D., & El-Roby, A. (2021, April). Conditional Adversarial Networks for Multi-Domain Text Classification. In Proceedings of the Second Workshop on Domain Adaptation for NLP (pp. 16-27). (第一作者, EACL workshop)

[6] Wu, Y., Inkpen, D., & El-Roby, A. (2022, May). Co-regularized adversarial learning for multi-domain text classification. In International Conference on Artificial Intelligence and Statistics (pp. 6690-6701). PMLR. (第一作者,AISTATS, CCF-C, 清华B类)

[7] Wu, Y., Inkpen, D., & El-Roby, A. (2022, May). Maximum Batch Frobenius Norm for Multi-Domain Text Classification. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3763-3767). IEEE. (第一作者,ICASSP, CCF-B, 清华B类)

[8] Chang, Y., Wang, X., Wang, J., Wu, Y., Yang, L., Zhu, K., ... & Xie, X. (2023). A survey on evaluation of large language models. ACM Transactions on Intelligent Systems and Technology. (通讯作者)

[9] Hu, J., & Wu, Y. (2024, April). Regularized Conditional Alignment for Multi-Domain Text Classification. In ICASSP 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 5645-5649). IEEE. (通讯作者,ICASSP, CCF-B, 清华B类)

[10] Wang, X., & Wu, Y. (2024). NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli. This paper will appear at IJCAI 2024. (通讯作者,IJCAI, CCF-A, 清华B类)

[11] Zhou, Y., Guo, C., Wang, X., Chang, Y., & Wu, Y. (2024). A Survey on Data Augmentation in Large Model Era. arXiv preprint arXiv:2401.15422.(通讯作者)

[12] Xia, T., Yu, B., Wu, Y., Chang, Y., & Zhou, C. (2024). Language Models can Evaluate Themselves via Probability Discrepancy. This paper will appear at ACL Findings 2024. (通讯作者,ACL, CCF-A, 清华A类)

[13] Wu, Y. (2024). Margin Discrepancy-based Adversarial Training for Multi-Domain Text Classification. This paper will appear at NLPCC 2024. (独立作者, NLPCC, CCF-C)


乐博app在线登录:社会兼职

会议审稿人: AAAI, EMNLP, AISTATS, IJCAI, ACL, ICASSP.

期刊审稿人: Information Science, IEEE Transactions on Cybernetics, npj Digital Medicine, Financial Innovation, IEEE Transactions on Instrumentation and Measurement.

乐博app在线登录:获奖情况

EACL 2021, the Second Workshop on Domain Adaptation for NLP, Best paper award.

AISTATS 2022, Outstanding reviewer award.

乐博app在线登录:指导学生

夏婷玉,博士,2021- ,与常毅老师共同指导,1 WWW (CCF-A), 1 EMNLP (CCF-B),1 ACL (CCF-A) 目前在阿里巴巴达摩院实习(实习方向:大模型评测)。

李晋南,博士,2022- ,与常毅老师共同指导。

常雨鹏,博士,2023- ,1 TIST。

周悦,博士,2024- 。

李金哲,直博,2025- ,与常毅老师共同指导。

王旭,硕士,2022-,1 TIST, 1 IJCAI (CCF-A),目前在美团实习(实习方向:大模型评测)。

李耿旭,硕士,2022- 。

李亚寒,硕士,2023- 。

郭晨璐,硕士,2023- 。

李致远,硕士,2024- 。

杨海旗,硕士,2024- 。

乐博app在线登录:毕业学生

王蕊,硕士,2021-2024,1 Siggraph Asia Poster (EI)。

胡竣涛,硕士,2021-2024, 1 ICASSP (CCF-B),去向:字节跳动。

王翊,本科,2020-2024,实习经历:小马智行(提示工程师);去向:香港科技大学(广州分校)。


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