HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Thu, 30 Oct 2025 22:13:07 GMT access-control-allow-origin: * strict-transport-security: max-age=31556952 etag: W/"6903e2f3-4239" expires: Sun, 28 Dec 2025 15:01:00 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: 259D:292AC1:7B7E0A:8A74BD:695143D3 accept-ranges: bytes age: 0 date: Sun, 28 Dec 2025 14:51:00 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210073-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1766933460.992017,VS0,VE228 vary: Accept-Encoding x-fastly-request-id: 936a7c134e6db83704a89fa8cf053f15dbaa934f content-length: 3019

Rui Xin I am a PhD student at University of Washington, where I am fortunate to be advised by Pang Wei Koh and Sewoong Oh. I am interested in reinforcement learning, privacy-preserving machine learning, and memorization. Previously, I graduated with a BS in Mathematics and Computer Science from Duke University, where I was very lucky to be advised by Cynthia Rudin and Margo Seltzer. Email  /  Google Scholar  /  GitHub Research Spurious Rewards: Rethinking Training Signals in RLVR Rulin Shao*, Shuyue Stella Li*, Rui Xin*, Scott Geng*, Yiping Wang, Sewoong Oh, Simon Shaolei Du, Nathan Lambert, Sewon Min, Ranjay Krishna, Yulia Tsvetkov, Hannaneh Hajishirzi, Pang Wei Koh, and Luke Zettlemoyer arXiv preprint, 2025 paper / code A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-Level Privacy Leakage Rui Xin*, Niloofar Mireshghallah*, Shuyue Stella Li, Michael Duan, Hyunwoo Kim, Yejin Choi, Yulia Tsvetkov, Sewoong Oh, and Pang Wei Koh NeurIPS Safe Generative AI Workshop, 2024 paper / code The Curious Case of Factuality Finetuning: Models' Internal Beliefs Can Improve Factuality Benjamin Newman, Abhilasha Ravichander, Jaehun Jung, Rui Xin, Hamish Ivison, Yegor Kuznetsov, Pang Wei Koh, and Yejin Choi arXiv preprint, 2025 paper DataComp-LM: In Search of the Next Generation of Training Sets for Language Models Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, ..., Rui Xin, ..., Ludwig Schmidt, and Vaishaal Shankar NeurIPS Datasets and Benchmarks, 2024 paper Language Models Scale Reliably with Over-Training and on Downstream Tasks Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, ..., Rui Xin, ..., and Ludwig Schmidt ICLR, 2025 paper Optimal Sparse Survival Trees Rui Zhang, Rui Xin, Margo Seltzer, and Cynthia Rudin AISTATS, 2024 paper Optimal Sparse Regression Trees Rui Zhang*, Rui Xin*, Margo Seltzer, and Cynthia Rudin AAAI, 2023 paper / code Exploring the Whole Rashomon Set of Sparse Decision Trees Rui Xin*, Chudi Zhong*, Zhi Chen*, Takuya Takagi, Margo Seltzer, Cynthia Rudin NeurIPS, 2022 (Oral) paper / code TimberTrek: Exploring and Curating Trustworthy Decision Trees with Interactive Visualization Zijie J. Wang, Chudi Zhong, Rui Xin, Takuya Takagi, Zhi Chen, Duen Horng Chau, Cynthia Rudin IEEE Visualization Conference (VIS), 2022 paper / code InviCloak: An End-to-End Approach to Privacy and Performance in Web Content Shihan Lin, Rui Xin, Aayush Goel, and Xiaowei Yang ACM CCS, 2022 paper / code Multitask learning for citation purpose classification Alex Oesterling*, Angikar Ghosal*, Haoyang Yu*, Rui Xin*, Yasa Baig*, Lesia Semenova, and Cynthia Rudin Second Workshop on Scholarly Document Processing, NAACL, 2021 paper Design and source code from Jon Barron's website and Leonid Keselman's fork