Search Results for author:
Found 2 papers, 0 papers with code
Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew
We investigate the hypothesis that incorporating explicit morphological knowledge in the pre-training phase can improve the performance of PLMs for MRLs.
Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All
We perform a contrastive analysis of this model against all previous Hebrew PLMs (mBERT, heBERT, AlephBERT) and assess the effects of larger vocabularies on task performance.
Ranked #1 on
Named Entity Recognition (NER)
on NEMO-Corpus
Cannot find the paper you are looking for? You can
Submit a new open access paper.
