Papers by Cheyn Shmuel Shmidman

1 papers
Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses? (2023.eacl-main)

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Challenge: Semitic morphologically-rich languages are characterized by extreme word ambiguity . many of the words are homographs with multiple possible analyses .
Approach: They evaluate existing models for Hebrew homographs using word-piece embeddings . they find they are more effective when the number of word-part splits is limited .
Outcome: The proposed models outperform non-contextualized embeddings on Hebrew homograph challenge sets.

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