Related papers: Build Fast and Accurate Lemmatization for Arabic
This study focuses on the design of multiple Arabic diacritical marks and to developing a model that generates the stacking of multiples Arabic diacritics in order to integrate it into a system of Arabic composition. The problem concerns…
Large Language Models (LLMs) have shown exceptional capabilities in Natural Language Processing (NLP) across diverse domains. However, their application in specialized tasks such as Legal Judgment Prediction (LJP) for low-resource languages…
Efficient hospital management systems (HMS) are critical worldwide to address challenges such as overcrowding, limited resources, and poor availability of urgent health care. Existing methods often lack the ability to provide accurate,…
Arabic poses a particular challenge for natural language processing (NLP) and information retrieval (IR) due to its complex morphology, optional diacritics and the coexistence of Modern Standard Arabic (MSA) and various dialects. Despite…
Arabic morphology encapsulates many valuable features such as word root. Arabic roots are being utilized for many tasks; the process of extracting a word root is referred to as stemming. Stemming is an essential part of most Natural…
The ultimate aim of handwriting recognition is to make computers able to read and/or authenticate human written texts, with a performance comparable to or even better than that of humans. Reading means that the computer is given a piece of…
We present QIMMA, a quality-assured Arabic LLM leaderboard that places systematic benchmark validation at its core. Rather than aggregating existing resources as-is, QIMMA applies a multi-model assessment pipeline combining automated LLM…
The process of language learning involves the mastery of countless tasks: making the constituent sounds of the language being learned, learning the grammatical patterns, and acquiring the requisite vocabulary for reception and production.…
This paper presents a dataset for closest opposite questions in Arabic language. The dataset is the first of its kind for the Arabic language. It is beneficial for the assessment of systems on the aspect of antonymy detection. The structure…
We study the performance of Arabic text classification combining various techniques: (a) tfidf vs. dependency syntax, for feature selection and weighting; (b) class association rules vs. support vector machines, for classification. The…
Like most natural language understanding and generation tasks, state-of-the-art models for summarization are transformer-based sequence-to-sequence architectures that are pretrained on large corpora. While most existing models focused on…
The focus of language model evaluation has transitioned towards reasoning and knowledge-intensive tasks, driven by advancements in pretraining large models. While state-of-the-art models are partially trained on large Arabic texts,…
Back-of-the-book indexes are crucial for book readability. Their manual creation is laborious and error prone. In this paper, we consider automating back-of-the-book index extraction for Arabic books to help simplify both the creation and…
This article describes the constitution process of the first morpho-syntactically annotated Tunisian Arabish Corpus (TArC). Arabish, also known as Arabizi, is a spontaneous coding of Arabic dialects in Latin characters and arithmographs…
Handwriting recognition is a challenging and critical problem in the fields of pattern recognition and machine learning, with applications spanning a wide range of domains. In this paper, we focus on the specific issue of recognizing…
Classical Arabic represents a significant era that encompasses the golden age of Arab culture, philosophy, and scientific literature. With a broad consensus on the importance of translating these literatures to enrich knowledge…
Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While these models have been compared with…
The goal of the paper is to predict answers to questions given a passage of Qur'an. The answers are always found in the passage, so the task of the model is to predict where an answer starts and where it ends. As the initial data set is…
In this paper, we propose a method to automatically identify future events in Lebanon's economy from Arabic texts. Challenges are threefold: first, we need to build a corpus of Arabic texts that covers Lebanon's economy; second, we need to…
The rapid growth of the internet has increased the number of online texts. This led to the rapid growth of the number of online texts in the Arabic language. The enormous amount of text must be organized into classes to make the analysis…