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 5
Targeted Retrieval, Compact Representations: How CoT Reasoning Improves Long-Context Counting
Large language models (LLMs) have been rapidly improving in long-context tasks, powered by Chain-of-Thought (CoT) reasoning.A Rank Graduation metric for Algorithmic fairness
Fairness assessment in algorithmic decisions that affect individuals, such as credit scoring, often relies on parity measures calculated at the aggregate group level.Efficient Active Auditing of Multi-Group Fairness with Bias Probes
Over the past decade, Machine Learning (ML) has been trained under dual objectives: minimizing prediction error via Empirical Risk Minimization (ERM) while controlling unfairness bias.SimplexUQ: An Evaluation Framework and Benchmark for Conformal Uncertainty on Simplex-Valued Predictions
Conformal prediction guarantees marginal coverage, but a single calibration threshold can still spread that coverage unevenly, over-covering easy regions and under-covering hard ones.Agent Evaluation Reliability: More Tasks Won't (Always) Fix An Agent Leaderboard
Agent evaluations are increasingly used to compare LLMs and inform deployment decisions, yet ranks can reflect not only the model but also the effects of the evaluation conditions such as the…Learning to Price Electricity for Optimal Demand Response
There is considerable interest in using time-varying electricity prices to shape consumer demand response, and better align energy demand with renewable production.Kinematic signatures of impairment: Detecting alcohol intoxication in e-scooter riders using sensor data and machine learning
Alcohol intoxication is a leading contributor to fatal and severe-injured e-scooterist crashes.An Input-Frugal Deep Learning Framework for Weather-Driven National Crop-Yield Forecasting: A Case Study of Brazilian Soybean
Reliable, timely crop-yield forecasts are essential for market stability and risk management, yet many approaches rely on costly or hard-to-scale inputs.Price Stability in the European Union: A Systemic Approach Using Random Matrix Theory
Price stability remains a pillar in monetary policy practices and carries a special importance within monetary unions.Reliability Engineering for AI Systems: Challenges, Methods, and Directions
AI reliability concerns whether an AI system performs its intended function dependably over a stated period and under stated operating conditions, with stated evidence.AI-based matching improves refugee employment in a double-blind randomized trial
Refugee integration is a central policy challenge for host countries, and where governments initially place refugees shapes their integration trajectories.What Paired Evaluations Reveal under Visual Perturbations
Robustness evaluation must examine diverse visual perturbations, while benchmarks cover only some real-world conditions and physical testing is costly.Group dynamics of engagement with AI topics on Bluesky
Social media increasingly shapes everyday life, serving as both a central venue for discussion of major events and a space where online collective behavior can spill over into real-world activity…AmbiModBench: Benchmarking Gene Perturbation Prediction Beyond Shared Responses
Predicting cellular responses to genetic perturbations helps prioritize experiments in single-cell genomics, where exhaustive measurement is infeasible.Design-Ignoring versus Design-Respecting World Models for Epidemiology
World models for epidemiology learn from records shaped by study designs, including assignment, sampling, measurement, and related processes.Missingness-Aware Conformal Prediction Under Cross-Hospital Distribution Shift
Clinical measurements are recorded for some patients but not others, at rates that differ across hospitals, and marginal conformal coverage does not ensure coverage within groups defined by…Accounting for Bias Enables Sustainable LLM Evaluation
LLM-as-a-judge has become the de facto standard for scalable, subjective evaluation, yet current leaderboards compensate for systematic measurement bias by running ever more comparisons, an approach…DIAL: Position-Debiased LLM Judges with Adaptive Human Preference Calibration
Large language models (LLMs) as a judge enable scalable evaluation, but their judgments can be sensitive to response order and, even after removing such position effects, can still diverge…Statistical Foundations for a Google Play User-Review Sentiment Index: Signal Fusion, Shrinkage, Distributional Validation, and Dynamic Smoothing
We develop a statistically explicit sentiment index for Google Play user reviews and establish the mathematical results supporting its construction.Uncertainty and Explainability in Deep Rough Volatility: A Neural Information-Theoretic Posterior Approach
Deep learning has substantially accelerated the calibration of complex stochastic-volatility models, but neural point calibration alone does not capture the uncertainty remaining after an…