mlsanityData to 7 Oct 2026

Spanish Biomedical and Clinical Language Embeddings

arXiv 2102.12843 ↗First posted 25 Feb 2021cs.CL cs.AIcited by 1

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Abstract (arXiv)

We computed both Word and Sub-word Embeddings using FastText. For Sub-word embeddings we selected Byte Pair Encoding (BPE) algorithm to represent the sub-words. We evaluated the Biomedical Word Embeddings obtaining better results than previous versions showing the implication that with more data, we obtain better representations.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 9 references that are in the map. First posted on arXiv 25 Feb 2021.

Builds on

4 of 9 references.

References · 4

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  4. 2017BPEmb: Tokenization-free Pre-trained Subword Embeddings in 275 Languagescited by 52

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Cited by year

Citing papers per year: 2021: 1.

1 paper.

  1. 2021MarIA: Spanish Language Modelscited by 36