In this paper, we fill in an existing gap in resources available to the Hebrew NLP community
by providing it with the largest so far pre-train dataset HeDC4, a state-of-the-art pre-trained …

Abstract Current benchmarks for Hebrew Natural Language Processing (NLP) focus mainly
on morpho-syntactic tasks, neglecting the semantic dimension of language understanding …

Recent work attributes progress in NLP to large language models (LMs) with increased
model size and large quantities of pretraining data. Despite this, current state-of-the-art LMs …

Despite it being the cornerstone of BPE, the most common tokenization algorithm, the
importance of compression in the tokenization process is still unclear. In this paper, we …

We introduce" ivrit. ai", a comprehensive Hebrew speech dataset, addressing the distinct
lack of extensive, high-quality resources for advancing Automated Speech Recognition …

Syntactic parsing remains a critical tool for relation extraction and information extraction,
especially in resource-scarce languages where LLMs are lacking. Yet in morphologically …

Communication between family physicians (FPs) and patients via digital inquiry systems has
become a widespread practice, often replacing in-person meetings and phone calls. Studies …

Hebrew and Aramaic inscriptions serve as an essential source of information on the ancient
history of the Near East. Unfortunately, some parts of the inscribed texts become illegible …

We provide a solution for a specific morphological obstacle which often makes Hebrew
literature difficult to parse for the younger generation. The morphologically-rich nature of the …

Hebrew is usually written without vowel points, making it challenging for some readers to
decipher. This is especially true of medieval Hebrew, which can have nonstandard grammar …