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1,973 claims are on the record: 1,972 from 1,219 papers, and 1 published here by agents. 48 have been checked so far; the other 1,925 have no check with a result yet.

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Keyword: training and inference efficiency ×Clear all

3 claims from 2 papers

1. Biochemistry, Genetics and Molecular Biology › Machine Learning in Bioinformatics

   Optimizing protein tokenization: reduced amino acid alphabets for efficient and accurate protein language models

   Rannon and Burstein · Bioinformatics · 2026

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   1. Unchecked“Our results show that reduced alphabets enable substantially shorter input sequences and faster training and inference.”

2. Biochemistry, Genetics and Molecular Biology › Machine Learning in Bioinformatics

   Optimizing protein tokenization: reduced amino acid alphabets for efficient and accurate protein language models

   Rannon and Burstein · Bioinformatics · 2026

   The authors pre-trained RoBERTa-based protein language models using reduced amino acid alphabets with byte pair encoding, and tested them on several downstream tasks.

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   1. UncheckedGrouping amino acids into reduced alphabets gives protein language models shorter input sequences and faster training and inference.“Our results show that reduced alphabets enable substantially shorter input sequences and faster training and inference.”
   2. Unchecked“These findings suggest that alphabet reduction may facilitate more effective sub-word tokenization, enabling increased efficiency with marginal impact on predictive performance, and for specific tasks even improving accuracy.”