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- When Does Sparse Routing Help? The Geometry of Expert Separation in Mixture of Experts
- Principled Human-AI Collaboration in Agentic Workflows
- Abstention Spends Its Budget on Local Label Variance More Than on Novelty: Auditing Conformal Calibration and Selective Prediction under Molecular Scaffold Shift
- A Debiased Machine Learning Single-Imputation Framework for Item Nonresponse in Surveys
- Correctness and Predictive Uncertainty in Bayesian TSK Fuzzy Regression: A Reproducible Evaluation on Tabular and Building-Meter Data
- Measurement Error and Nonlinear Confounding: Structural Equation Modeling Versus Double Machine Learning
- Infinite Quantiles Inference under Local Differential Privacy
- Sentiment sensing: comparative analysis of multilingual sentiment dynamics
- Accuracy Is Not Risk: Why Medical AI Should Not Report Only Its Most Likely Label
- Likelihood-Free Schrödinger--Föllmer Sampling for Bayesian Inference with Fixed-Proposal Reuse
- Model-Based Co-Clustering for Censored Data
- Geodesics and intrinsic statistics of isolated connections in Hermitian positive-definite matrices
- A model-based adaptive sampling framework for infectious disease surveillance
- Selective inference for pruned interaction trees with known unequal variances in randomized trials
- A Kernel-Based Test for Multi-Way Conditional Independence
- Self-Normalized Inference from Riemannian Stochastic Gradient Paths
- Second-Order Least Squares Method for Statistical Inference in Linear Models with Asymmetric Errors
- HALO: Hierarchical Evidence Selection and Reinforcement Learning for Allocating Budgeted Label Optimization from Longitudinal Clinical Records
- Riemannian Newton Methods with Statistical Inference
- Bootstrap Inference for Riemannian Optimization Problems
- A Bayesian Magnitude-Composition Model for Tree-Size Distributions and Stand-Tables
- Differential Privacy for Generalized Entropy Indices of Income Inequality
- Finite-Sample Calibration and Power Benchmarks in Two-Sample Random-Integration Tests
- Power-optimal allocation in multi-arm cluster randomized trials
- Tight Stochastic Sequential Covers for General VC Classes with Unknown i.i.d. Features