arXiv AI
Jul 22
When Does Machine Learning Beat Value Sorting? A Three-Dataset Diagnostic of Exposure-Weighted Shipment Prioritization
arXiv:2607. 18573v1 Announce Type: new Abstract: Delay-risk models are usually judged by predictive accuracy.
When Does Machine Learning Beat Value Sorting? A Three-Dataset Diagnostic of Exposure-Weighted Shipment Prioritization
Delay-risk models are usually judged by predictive accuracy. What matters in practice is narrower: with capacity to review only a few shipments, which ones should a manager check first?
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arXiv Machine Learning
Sep 15
Accuracy Is Not Service: A Decision-Aware Benchmark for Intermittent-Demand Forecasting
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arXiv AI
Aug 28
Diagnosing Conformal Prediction Failures Under Distribution Shift: A COVID-19 Case Study
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arXiv Machine Learning
1d ago
The Hidden Costs of 99% Accuracy: A Trustworthiness Audit of the Telco Customer Churn Benchmark
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arXiv Machine Learning
Aug 31
RiskBlend: A Multi-Signal Framework for Test Input Prioritization in Machine Learning Regression Testing
arXiv:2608.27704v1 Announce Type: new Abstract: When machine learning classifiers are retrained, inputs correctly classified by the previous model version may be misclassified by the updated version,...
arXiv AI
Jul 22
Censoring-Aware In-Context Learning for Generalized Supplier Lead Time Estimation in Supply Chain Planning
arXiv:2607. 18530v1 Announce Type: cross Abstract: Supplier lead time forecasting is a central input to material requirements planning, inventory optimization, and supply chain risk management.
arXiv Machine Learning
Jul 17
The Challenger: When Do New Data Sources Justify Switching Machine Learning Models?
arXiv:2512. 18390v2 Announce Type: replace Abstract: Organizations often have an incumbent predictive model in production when new data sources become available.
arXiv AI
Jul 24
SalesLoop: Reinforcement Learning from Performance Feedback for Sales Lead Ranking
arXiv:2607. 20655v1 Announce Type: cross Abstract: Lead ranking in Customer Relationship Management (CRM) systems faces a persistent challenge: models achieving high offline accuracy often underperform in production.
arXiv Machine Learning
Jun 2
Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation
arXiv:2602. 06136v2 Announce Type: replace Abstract: Test-time adaptation (TTA) offers a compelling remedy for machine learning (ML) models that degrade under domain shifts, improving generalisation on-the-fly with only unlabelled samples.
arXiv Machine Learning
Aug 12
DACRI: Decision-Aware Causal Intervention Ranking for Critical Supply Chains
arXiv:2608. 11154v1 Announce Type: new Abstract: Detecting or attributing a supply-chain disruption is not the same as selecting the intervention that maximizes recoverable net value.
arXiv AI
Jun 3
The Reliability Gap in Benchmark Auditing: Distribution Shift and Scale as Failure Modes of Contamination Detection
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arXiv Machine Learning
2d ago
Beyond Model Ranking: Regime Diagnosis for Distributional-Statistical Misspecification in Industrial Time-Series Forecasting
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