Probability & Statistics · Mathematics & Statistics
Applications
The newest papers in Applications that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
143 papers, from 4 September 2026 to 5 November 2026: 143 arXiv preprints.
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Newest papers, page 6
LLM Judge Validation Under Sparse Overlap: From Inference to Design
Validating an LLM-as-a-judge requires estimating its agreement with humans, yet annotation budgets rarely allow every item to be multiply labeled.GeoDose-CP: Graph-Local Conformal Inference for Continuous-Treatment Earth Observation
Reliable intervention-oriented uncertainty quantification from Earth observation (EO) remains challenging when continuous treatment shifts, spatial dependence, limited support, and satellite-outcome…Do Audio Language Models Hear and Read Distinctive Features Alike?
Audio language models pass speech and text through a single decoder.An End-to-End Pipeline for Causal ML with Continuous Treatments: An Application to Financial Decision Making
This paper presents an end-to-end causal machine learning (ML) pipeline designed for real-world applications with continuous treatments.Suitable Measures for the Potential Operational Utility of AI NWP Rainfall Forecasts Over Africa
Artificial intelligence (AI)-based weather prediction is approaching the skill of physical numerical weather prediction (NWP) systems at a fraction of the computational cost.Scientific capabilities and deployment sustainability of small-scale LLMs in biological wastewater treatment
Large language models (LLMs) are emerging as scientific assistants, yet their computational demands and limited domain specialization constrain sustainable deployment in environmental engineering.Beyond Scalar Sensitivity: Activation-Aware Mixed-Precision LLM Quantization with Cross-Layer Refinement
Mixed-precision weight quantization is commonly formulated as a Multiple-Choice Knapsack Problem (MCKP), yet existing solvers rely on scalar sensitivity proxies that collapse each weight matrix's…Additive Nonparametric Regression with Spatial and Network Objects
This article is motivated by an imaging application from the Adolescent Brain Cognitive Development (ABCD) study, aiming to predict task-based brain activation maps from t-fMRI using cortical…OSCAR: Order-aware Scoring and Calibration for AI Rankings
Judge-specific sensitivity is useful for aggregating pairwise LLM evaluations, but its interpretation depends on which systematic presentation effects the ranking model includes.Augmented Hypothesis Testing with Persona-Based LLM Simulations
A/B testing requires large sample sizes, long timelines, and significant costs.PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models
In high-dimensional tabular learning, feature screening provides a lightweight, model-agnostic way to remove irrelevant features before model fitting.Human-Level Accuracy, Non-Human Strategies: Revealing Model-Human Divergence in Video Physical Reasoning
Video foundation models now reach human-level accuracy on physical-reasoning benchmarks, yet such tasks require predicting unobserved physical outcomes.Auditing Bayesian Graph Alignment: Diagnostic Comparisons and Reference Failure
Bayesian graph alignment estimates correspondence probabilities, but convergence of an alignment-score trace need not imply accurate correspondence marginals.Adapting Pairs Trading to Gambling Markets A Case Study of the U.S. Presidential Election
Pairs trading exploits mean reversion in the relationship between related assets.Compression Hurts, Pooling Helps: Information Loss in Rayleigh-Scale Estimation from B-Mode Ultrasound
Clinical B-mode images are widely available as potential data sources for quantitative ultrasound (QUS) analysis for tissue characterization.Prediction-Powered Smoothing and Validation for Disaggregated AI Evaluation
Evaluating an AI system requires disaggregated assessment, as performance varies across domains such as benchmark task types or conversation types in deployed agents.Continuous Delayed-Memory Stochastic Gradient Descent and Continuous-Time Reinforcement Learning from History of Astrophysical Time Series Studies
Quasars are luminous objects in the universe that exhibit stochastic brightness variations encoding information about the supermassive black holes powering them, and modeling these variations from…Triply-Scalable Equivariant Gaussian Process Modeling
Gaussian processes (GPs) provide principled probabilistic predictions while encoding prior knowledge, including equivariances.Causal Path Analysis from Perturbational and Population-Scale Single-Cell Data with Multiscale Confounding and Measurement Error
Single-cell perturbation experiments provide causal information on gene regulation, whereas population-scale single-cell studies characterize gene expression and phenotypes in human populations.Accelerating Diffusion Sampling via Speculative Draft Trees
Speculative sampling accelerates diffusion model generation by drafting inexpensive candidate states and correcting them under a coupling that preserves the target distribution exactly, reducing the…