mlsanityData to 14 Oct 2026

ECG-Soup: Harnessing Multi-Layer Synergy for ECG Foundation Models

arXiv 2509.00102 ↗First posted 27 Aug 2025cs.LG cs.AIcited by 1

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Abstract (arXiv)

Transformer-based foundation models for Electrocardiograms (ECGs) have recently achieved impressive performance in many downstream applications.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 35 of its 59 references that are in the map. First posted on arXiv 27 Aug 2025.

Builds on

35 of 59 references.

References · 35

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  9. 2020CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patientscited by 171
  10. 2019Automatic diagnosis of the 12-lead ECG using a deep neural networkcited by 164
  11. 2020Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XLcited by 158
  12. 2022Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practicecited by 136
23 more
  1. 2020Self-supervised ECG Representation Learning for Emotion Recognitioncited by 99
  2. 2024Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogramcited by 84
  3. 2021Self-supervised representation learning from 12-lead ECG datacited by 80
  4. 2023Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggerscited by 72
  5. 2024Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancementcited by 67
  6. 2023Frozen Language Model Helps ECG Zero-Shot Learningcited by 62
  7. 2022Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learningcited by 57
  8. 2022Towards Understanding Mixture of Experts in Deep Learningcited by 52
  9. 2022Self-Supervised Time Series Representation Learning via Cross Reconstruction Transformercited by 47
  10. 2021Vision Transformers with Patch Diversificationcited by 45
  11. 20213KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentationscited by 36
  12. 2023Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionalscited by 32
  13. 2023Analyzing Vision Transformers for Image Classification in Class Embedding Spacecited by 26
  14. 2022Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolutioncited by 22
  15. 2024Learning General Representation of 12-Lead Electrocardiogram with a Joint-Embedding Predictive Architecturecited by 19
  16. 2024Self-Supervised Pre-Training with Joint-Embedding Predictive Architecture Boosts ECG Classification Performancecited by 14
  17. 2021Real-Time Patient-Specific ECG Classification by 1D Self-Operational Neural Networkscited by 13
  18. 2023Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approachcited by 13
  19. 2022Analysis of Augmentations for Contrastive ECG Representation Learningcited by 12
  20. 2022Global ECG Classification by Self-Operational Neural Networks with Feature Injectioncited by 9
  21. 2023Masked Transformer for Electrocardiogram Classificationcited by 7
  22. 2024A Multi-Resolution Mutual Learning Network for Multi-Label ECG Classificationcited by 4
  23. 2024Hierarchical Transformer for Electrocardiogram Diagnosiscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.