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SPIN Processed News Frame: The Fog
Class Imbalance and Batch Effects in LLM-Based Screening for Systematic Reviews
A new arXiv preprint examines how large language models behave in imbalanced binary classification tasks—specifically, screening studies for systematic reviews—and finds that batch processing (vs. individual item processing) induces significant, prevalence-dependent behavioral shifts in model decisions, while prevalence metadata shows no measurable performance benefit.
Spin 35% Claim Present in Source AI Risk Moderate
arXiv Computation and Language
Aug 18, 2026
SPIN Processed News Frame: The Hype
SemiScope: Disentangling Classifier Tuning and Joint Optimization in Semi-Supervised Security Classification
Researchers develop SemiScope to improve semi-supervised security classification.
Spin 50% Claim Present in Source AI Risk Moderate
arXiv Machine Learning
Published Jul 2, 2026 · Analyzed Jul 5, 2026