2 citations · 3 across the 10 of their papers we have counts for
6 papers · 1 filter
Unifying Privacy Accounting: Information Equivalence and Information Loss
Buxin Su, Qiaoshi Yang, Yiding Su +1
Differential privacy (DP) admits several notions, but the choice among them may affect both privacy analysis and utility. In this paper, we consider four mainstream curve-based pri…
Use and Effects of LLMs in Peer Review: A Randomized Experiment and Survey at ICML 2026
Sunnie S. Y. Kim, Wesley Hanwen Deng, Jennifer Wortman Vaughan +8
LLMs are rapidly reshaping peer review, making it important to understand how reviewers use them in practice and how different LLM-use policies affect review outcomes. We investiga…
A Sieve-Accelerated Quadrature Method for Exact Privacy Accounting in the 2020 U.S. Decennial Census
Buxin Su, Weijie Su, Chendi Wang
In 2020, the U.S. Census Bureau adopted differential privacy for the Decennial Census by injecting integer-valued Gaussian noise into published census tabulations. Exactly evaluati…
Statistical Proof as a Window into Human-AI Collaboration: Practical Insights and a Community Agenda
Xiaojing Sun, Huayu Tang, Buxin Su +4
Large language models (LLMs) are increasingly woven into expert cognitive work in daily research, yet we know little about how human expertise should adapt when an AI system can ex…
Rethinking Synthetic Rationale Supervision for Disease Prediction
Buxin Su, Bingxuan Li, Cheng Qian +3
Supervised fine-tuning with synthetic rationales is widely assumed to improve clinical prediction by teaching models not only what to predict but why. We test this assumption on fi…
Recommending Best Paper Awards for ML/AI Conferences via the Isotonic Mechanism
Garrett G. Wen, Buxin Su, Natalie Collina +2
Machine learning and artificial intelligence conferences such as NeurIPS and ICML now regularly receive tens of thousands of submissions, posing significant challenges to maintaini…