Talks
Tutorials
- AAAI 2025: Evaluating Large Language Models: Challenges and Methods, Feb., 2025.
- AAAI 2025: Unified Semi-Supervised Learning with Foundation Models, Feb., 2025.
- AAAI 2024: Out-of-Distribution Generalization in Time Series, Feb., 2024. [Website&Slides]
- KDD 2023: Trustworthy machine learning: robustness, generalization and interpretability, Aug., 2023. [Website&Slides]
- WSDM 2023: On the robustness of ChatGPT and NLP Foundation models: an adversarial and OOD perspective, Feb., 2023. [PDF] [More]
- IJCAI 2022: A Tutorial on Domain Generalization, July, 2022. [website]
Invited talks
- Understanding and improving foundation models, at From Theory to Practice: Workshop on Large Language and Foundation Models (WLLFM’24), IEEE BigData Conference 2024. Washington DC. Dec. 2024. [website]
- Understanding the catastrophic inheritance of large foundation models, at 2024 International Workshop on Risk and Governance of Generative Artificial Intelligence, Hong Kong, Nov. 2024. [website]
- Dynamic evaluation of large language models, at The First International Conference on Cognitive Psychological Assessment and Enhancement, Jul. 2024. [website]
- LLM evaluation and interdisciplinary research, at Sun Yat-Sen University. Jun. 2024.
- Understanding LLMs: evaluation, enhancement, and interdisciplinary research, at KAUST AI symposium. Feb. 2024.
- Understanding LLMs: evaluation, enhancement, and interdisciplinary research, at UIUC. Nov. 2023.
- Theory, evaluation, and enhancement of large language models, at HHME 2023, Harbin, China. August 2023.
- Towards generalization in dynamic distributions, at Domain Generalization workshop in University of Warwick, UK. July 2023. [Youtube]
- Towards robustness research in the era of large models, at Southern University of Science Technology (Sustech), Shenzhen. June 2023.
- Safe, efficient, and generalizable transfer learning, at NCIIP 2023. Changchun. May 2023.
- Robust machine learning for responsible AI, at Hefei University of Technology. Mar. 2023. [video at Bilibili]
- Building robust machine learning models, at MLNLP community. Sep. 2022. [Video & PDF]
- Transfer learning: low-resource, generalization, and safety, at AI Time. Apr. 2022. [PDF] [Video] [Zhihu]
- Recent advance in transfer learning, at Jiqizhixin. Jun. 2021. [PDF] [Video]
- Transfer learning: challenges and methods, at Shandong University, Jinan, China. Oct. 2018.
- Transfer learning methods, at Shenzhen University & Harbin Institute of Technology. Jun. 2018. [PDF] [Video]
- Domain adaptation in transfer learning, at Extreme Vision, online. Dec. 14, 2017. [PDF] [Video]
Invited Course
- Transfer learning and large languaeg models, at City University of Hong Kong. 2023.
- Transfer learning, at Institute of Computing Technology, CAS. 2023.
- Transfer learning, at Tsinghua University. Dec. 2019. (THU’s advanced machine learning course for EE graduates) [Class photo]
- Transfer learning, at Leiphone, online. Nov. 4, 2017.
- On machine learning, at AI Salon at Shanghai Jiao Tong University, Shanghai, China. Sep. 16, 2017. [PDF] [Photo]
- Feature engineering in machine learning, at Zhihu Live, online. Mar. 19, 2017. [PDF] [Visit Live]
- Machine learning starter, at Zhihu Live, online. Dec. 22. [PDF] [Visit Live]