Papers with out-of-vocabulary rate

2 papers
Improving Multilingual Models with Language-Clustered Vocabularies (2020.emnlp-main)

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Challenge: State-of-the-art multilingual models depend on vocabularies that cover all languages . but the methods for generating those vocalaries are not ideal for massively multilingual applications.
Approach: They propose a procedure for multilingual vocabulary generation that combines separately trained vocabularies of several automatically derived language clusters.
Outcome: The proposed procedure shows improvements across languages on multilingual benchmark tasks . the proposed procedure reduces out-of-vocabulary rate by a factor of 8 .
Improving a Neural-based Tagger for Multiword Expressions Identification (L18-1)

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Challenge: MUMULS tagger for automatic detection of verbal multiword expressions is based on neural networks . character-level embeddings can improve the performance, reducing out-of-vocabulary rate . multiword Expressions are viewed by computational linguists as a "pain in the neck of NLP"
Approach: They propose to improve MUMULS, a tagger for automatic detection of verbal multiword expressions.
Outcome: The proposed tagger performed better on Czech language than the previous taggers.

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