Hebrew Language Model

Research on Hebrew language models focuses on developing and improving computational models capable of understanding and generating Hebrew text, addressing the challenges posed by its rich morphology and ambiguous writing system. Current efforts involve adapting and extending existing architectures like BERT and RoBERTa, exploring techniques like transliteration for cross-lingual applications (e.g., Arabic-Hebrew), and evaluating model performance on tasks such as sentiment analysis, question answering, and machine translation. These advancements are significant for the NLP community, providing valuable resources for Hebrew-specific applications and furthering our understanding of how language models handle morphologically complex languages.