Retrieval from out-of-domain foundation models enables personalization of a lightweight transformer for stress detection, yielding +3.92% accuracy and +4.76% F1 gains on WESAD without user labels.
Address for correspondence: Elias Stenhede Sykehusveien 25, 1478 Nordbyhagen, Norway elias.stenhede@ahus.no
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
Biomarker pretraining on MIMIC-IV-ECG followed by fine-tuning on Brazilian Chagas ECG datasets produced a 5th-place score of 0.269 in the 2025 PhysioNet Challenge.
citing papers explorer
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Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection
Retrieval from out-of-domain foundation models enables personalization of a lightweight transformer for stress detection, yielding +3.92% accuracy and +4.76% F1 gains on WESAD without user labels.
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Biomarker-Based Pretraining for Chagas Disease Screening in Electrocardiograms
Biomarker pretraining on MIMIC-IV-ECG followed by fine-tuning on Brazilian Chagas ECG datasets produced a 5th-place score of 0.269 in the 2025 PhysioNet Challenge.