FoNE encodes numbers as single tokens via Fourier features and outperforms subword and digit-wise embeddings on addition, subtraction, and multiplication with far less data.
Representing numbers in nlp: a survey and a vision
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LLM embeddings from clinical records, fused with tabular data via gradient-boosted trees, predict post-traumatic epilepsy at AUC-ROC 0.892 and AUPRC 0.798.
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FoNE: Precise Single-Token Number Embeddings via Fourier Features
FoNE encodes numbers as single tokens via Fourier features and outperforms subword and digit-wise embeddings on addition, subtraction, and multiplication with far less data.
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Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings
LLM embeddings from clinical records, fused with tabular data via gradient-boosted trees, predict post-traumatic epilepsy at AUC-ROC 0.892 and AUPRC 0.798.