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papersTODAY 04:00 UTC

Study compares eight tokenization strategies for ECG transformer models

A new arXiv paper examines how different tokenization choices affect ECG transformer models, since the tokenizer decides both the physiological signal content the model sees and the sequence length attention operates over. The authors benchmark eight tokenization strategies across four architectures — Transformer, Informer, Reformer, and FEDformer — on the nine-label CPSC ECG dataset. The work is cross-listed in cs.AI and cs.LG.

FEDformerInformerReformerECGTransformertokenization

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