88 citations · 114 across the 24 of their papers we have counts for
27 papers
Statistical attribute alignment for black-box generative AI via output post-processing
Kevin Jiang, Morgane Austern, Edgar Dobriban +1
Generative AI systems are increasingly used, but aligning their outputs with user requirements poses a continuing challenge. Here, we aim to ensure that the distribution of an attr…
The Zero Pattern of a Design Matrix Drives Multiple Descent in Over-parameterized Regression
Kevin Han Huang, Haoyu Ye, Somak Laha +1
Over-parameterized linear regression has been widely studied over the last decade. However, most existing works assume that the covariates are independent and that their covariance…
Graph Attention Network for Node Regression on Random Geometric Graphs with Erdős--Rényi contamination
Somak Laha, Suqi Liu, Morgane Austern
Graph attention networks (GATs) are widely used and often appear robust to noise in node covariates and edges, yet rigorous statistical guarantees demonstrating a provable advantag…
Computable Bounds for Strong Approximations with Applications
Haoyu Ye, Morgane Austern
The Komlós$\unicode{x2013}$Major$\unicode{x2013}$Tusnády (KMT) inequality for partial sums is one of the most celebrated results in probability theory. Yet its practical applicatio…
Inference on Optimal Policy Values and Other Irregular Functionals via Softmax Smoothing
Justin Whitehouse, Qizhao Chen, Morgane Austern +1
Constructing confidence intervals for the value of an (unknown) optimal treatment policy is a fundamental problem in causal inference. Insight into the optimal policy value can gui…
Poisson-Process Topic Model for Integrating Knowledge from Pre-trained Language Models
Morgane Austern, Yuanchuan Guo, Zheng Tracy Ke +1
Topic modeling is traditionally applied to word counts without accounting for the context in which words appear. Recent advancements in large language models (LLMs) offer contextua…