Six modern tabular foundation models are near-redundant, limiting ensemble gains to +0.18% accuracy at high cost while some methods degrade calibration.
Selective classification for deep neural networks
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A Transformer model predicts personalized post-intervention trajectories and direction of change for heart rate and variability from wearable sensor data, showing feasibility as a proof of concept.
citing papers explorer
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Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap
Six modern tabular foundation models are near-redundant, limiting ensemble gains to +0.18% accuracy at high cost while some methods degrade calibration.
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Personalized and Context-Aware Transformer Models for Predicting Post-Intervention Physiological Responses from Wearable Sensor Data
A Transformer model predicts personalized post-intervention trajectories and direction of change for heart rate and variability from wearable sensor data, showing feasibility as a proof of concept.