State-of-the-art natural language processing (NLP) models are trained on massive training
corpora, and report a superlative performance on evaluation datasets. This survey delves …

We introduce Jais and Jais-chat, new state-of-the-art Arabic-centric foundation and
instruction-tuned open generative large language models (LLMs). The models are based on …

As the reach of large language models (LMs) expands globally, their ability to cater to
diverse cultural contexts becomes crucial. Despite advancements in multilingual …

Transfer learning with a unified Transformer framework (T5) that converts all language
problems into a text-to-text format was recently proposed as a simple and effective transfer …

The expanding financial markets of the Arab world require sophisticated Arabic NLP tools.
To address this need within the banking domain, the Arabic Financial NLP (AraFinNLP) …

We present WojoodNER-2023, the first Arabic Named Entity Recognition (NER) Shared
Task. The primary focus of WojoodNER-2023 is on Arabic NER, offering novel NER datasets …

Reliance on social networks has become an integral part of modern daily activities. Social
networks are crowded with vast numbers of comments, opinions, and beliefs about different …

Like most natural language understanding and generation tasks, state-of-the-art models for
summarization are transformer-based sequence-to-sequence architectures that are …

Pre-trained transformers are now the de facto models in Natural Language Processing given
their state-of-the-art results in many tasks and languages. However, most of the current …

Word embeddings, which represent words as numerical vectors in a high-dimensional
space, are contextualized by generating a unique vector representation for each sense of a …