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Related Questions
- How does WordPiece tokenization handle Out-of-Vocabulary (OOV) words, such as those with very low frequencies?
- Are there any specific issues when applying WordPiece tokenization to text with many unigrams, which can also be low-frequency words?
- Can WordPiece tokenization lead to incomplete or incorrect tokenization when dealing with low-frequency compound words or proper nouns?
- How does subword modeling, like the one used in WordPiece tokenization, handle issues related to low-frequency contexts?
- In rare word situations, do all WordPiece tokenizers face difficulties when dealing with completely new, unseen vocabulary entities?
- Do special treatment of low-frequency punctuation, or other boundary token cases exist in the latest WordPiece tokenizers algorithms?
- Does existing subword tokenizers work in favor of lower rank frequency vocabulary items to an excessive extent?
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