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Accurate and Efficient Statistical Testing for Word Semantic Breadth ACL 2026 The Generalised Kernel Covariance Measure CLeaR 2026 FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees ICML 2025 Hypothesis Testing for Generalized Thurstone Models ICML 2025 Max-Rank: Efficient Multiple Testing for Conformal Prediction AISTATS 2025 Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data ICML 2025 Covariate Shift Corrected Conditional Randomization Test NeurIPS 2024 Non-splitting Neyman-Pearson Classifiers JMLR 2024 Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams ICML 2024 Segmenting Watermarked Texts From Language Models NeurIPS 2024 Sequential Kernel Goodness-of-fit Testing ICML 2024 Conditional independence testing under misspecified inductive biases NeurIPS 2023 Frequentist Uncertainty Quantification in Semi-Structured Neural Networks AISTATS 2023 K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing NeurIPS 2023 Nearest-Neighbor Sampling Based Conditional Independence Testing AAAI 2023 Selective inference for k-means clustering JMLR 2023 Anytime-Valid Inference For Multinomial Count Data NeurIPS 2022 A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks ICLR 2022 A Witness Two-Sample Test AISTATS 2022 Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size AISTATS 2022 Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies AISTATS 2022 An Online Sequential Test for Qualitative Treatment Effects JMLR 2021 Statistical inference for individual fairness ICLR 2021 A New Framework for Online Testing of Heterogeneous Treatment Effect AAAI 2020 Neyman-Pearson classification: parametrics and sample size requirement JMLR 2020