Hebrew NLP

Hebrew Natural Language Processing (NLP) focuses on developing computational methods to understand and process the Hebrew language, addressing its unique morphological complexity. Current research emphasizes creating and improving large language models (LLMs), such as BERT and RoBERTa variants, along with developing robust parsing techniques tailored to Hebrew's rich morphology, often employing sequence-to-sequence architectures or innovative pipeline approaches. These advancements, fueled by the release of new, larger datasets and pre-trained models, are significantly improving performance on tasks like part-of-speech tagging, dependency parsing, and question answering, benefiting both the broader NLP community and applications requiring Hebrew language processing.