Xudong Shen

Xudong Shen

Ph.D. student

National University of Singapore

About Me : )

Hello! I am Xudong Shen (沈旭东). Friends also call me Oliver. I am a 5th year Ph.D. student at National Univeristy of Singapore, advised by professor Mohan Kankanhalli. I am interested in both the technical approaches to address social issues in AI systems and the role of policy and regulation in making AI systems more beneficial to our society. With a particular focus on fairness, I have worked on gender discrimination in FinTech, general fair representation learning, and biases in large language models and text-to-image generative models. I can be reached at xudong.shen@u.nus.edu.

I had the privilege of interning at Sea AI Lab in Singapore from 2022 to 2023. Between 2015 and 2019, I was an undergraduate at Zhejiang University, China, majoring in Naval Architect and Ocean Engineering. During this period, I explored various topics including computational fluid dynamics, satellite imaging, and policy research. My cv is here.

I believe in Diversity, Equity & Inclusion. I am committed to uphold these values.

If you are interested, I’ve written something more about myself…

Working Papers

[w1] Xudong Shen, Tianhui Tan, Jussi Keppo, and Tuan Q. Phan, Improved Identification of Gender Discrimination Drivers in Online P2P Lending.
          — We show an improved identification of the taste-based and the belief-based gender discrimination drivers in P2P lending.
          — Oral presentation at the International Conference on Smart Finance, 2022, [slides].
          — Preparing journal submission.

[w2] Xudong Shen, Yongkang Wong, and Mohan Kankanhalli, Theoretical Guarantees of Subgroup-Fair Representation via Task Anticipation.

Preprints

[p1] Xudong Shen, Hannah Brown, Jiashu Tao, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez, “Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities”, arXiv:2306.12609, 2023, under review for Communications of the ACM. [arXiv]

[p2] Xudong Shen, Chao Du, Tianyu Pang, Min Lin, Yongkang Wong, and Mohan Kankanhalli, Finetuning Text-to-Image Diffusion Models for Fairness, arXiv:2311.07604, 2023, under review for ICLR 2024. [arXiv]

Publications

[2021a] Ziwei Xu, Xudong Shen, Yongkang Wong, and Mohan S Kankanhalli, “Unsupervised Motion Representation Learning with Capsule Autoencoders”, NeurIPS, 2021. [Paper] [arXiv] [GitHub] [Slide] [Video]

[2022a] Xudong Shen, Yongkang Wong, and Mohan S Kankanhalli, “Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks”, IEEE Trans. PAMI, 2022. [Paper] [arXiv] [GitHub]

[2022b] Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, …, Xudong Shen, …, “Benchmarking Generalization via In-Context Instructions on 1,600+ Language Tasks”, EMNLP, 2022. [Paper] [arXiv] [Data]

[2023a] Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, …, Xudong Shen, …, “NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation”, Northern European Journal of Language Technology (NEJLT), 2023. [arXiv] [GitHub]

[2023b] Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, …, Xudong Shen, …, “Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models”, JMLR, 2023. [Paper] [arXiv]

[2023c] Xudong Shen, Tianhui Tan, Tuan Q. Phan, Jussi Keppo, “Gender Animus Can Still Exist Under Favorable Disparate Impact: a Cautionary Tale from Online P2P Lending”, ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2023. [Paper] [arXiv] [Video]

[2023d] Ian McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, …, Xudong Shen, …, “Inverse Scaling: When Bigger Isn’t Better”, TMLR, 2023. [arXiv] [GitHub]