7 papers
Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings
Jenny Y. Huang, Yunyi Shen, Dennis Wei +1
We propose a method for evaluating the robustness of widely used LLM ranking systems -- variants of a Bradley--Terry model -- to dropping a worst-case very small fraction of prefer…
Explicit modeling of density dependence in spatial capture-recapture models
Qing Zhao, Yunyi Shen
Density dependence occurs at the individual level and thus is greatly influenced by spatial local heterogeneity in habitat conditions. However, density dependence is often evaluate…
Approximations to worst-case data dropping: unmasking failure modes
Jenny Y. Huang, David R. Burt, Yunyi Shen +2
A data analyst might worry about generalization if dropping a very small fraction of data points from a study could change its substantive conclusions. Checking this non-robustness…
Oh SnapMMD! Forecasting Stochastic Dynamics Beyond the Schrödinger Bridge's End
Renato Berlinghieri, Yunyi Shen, Jialong Jiang +1
Scientists often want to make predictions beyond the observed time horizon of "snapshot" data following latent stochastic dynamics. For example, in time course single-cell mRNA pro…
Multi-marginal Schrödinger Bridges with Iterative Reference Refinement
Yunyi Shen, Renato Berlinghieri, Tamara Broderick
Practitioners often aim to infer an unobserved population trajectory using sample snapshots at multiple time points. E.g., given single-cell sequencing data, scientists would like…
Consistent Validation for Predictive Methods in Spatial Settings
David R. Burt, Yunyi Shen, Tamara Broderick
Spatial prediction tasks are key to weather forecasting, studying air pollution impacts, and other scientific endeavors. Determining how much to trust predictions made by statistic…