41 citations · 118 across the 31 of their papers we have counts for
32 papers
Palm: A Culturally Inclusive and Linguistically Diverse Dataset for Arabic LLMs
Fakhraddin Alwajih, Abdellah El Mekki, Samar Mohamed Magdy +41
As large language models (LLMs) become increasingly integrated into daily life, ensuring their cultural sensitivity and inclusivity is paramount. We introduce our dataset, a year-l…
Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarks
Gagan Bhatia, El Moatez Billah Nagoudi, Abdellah El Mekki +2
We introduce {\bf Swan}, a family of embedding models centred around the Arabic language, addressing both small-scale and large-scale use cases. Swan includes two variants: Swan-Sm…
Casablanca: Data and Models for Multidialectal Arabic Speech Recognition
Bashar Talafha, Karima Kadaoui, Samar Mohamed Magdy +24
In spite of the recent progress in speech processing, the majority of world languages and dialects remain uncovered. This situation only furthers an already wide technological divi…
Qalam : A Multimodal LLM for Arabic Optical Character and Handwriting Recognition
Gagan Bhatia, El Moatez Billah Nagoudi, Fakhraddin Alwajih +1
Arabic Optical Character Recognition (OCR) and Handwriting Recognition (HWR) pose unique challenges due to the cursive and context-sensitive nature of the Arabic script. This study…
Peacock: A Family of Arabic Multimodal Large Language Models and Benchmarks
Fakhraddin Alwajih, El Moatez Billah Nagoudi, Gagan Bhatia +2
Multimodal large language models (MLLMs) have proven effective in a wide range of tasks requiring complex reasoning and linguistic comprehension. However, due to a lack of high-qua…
FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models
Gagan Bhatia, El Moatez Billah Nagoudi, Hasan Cavusoglu +1
We introduce FinTral, a suite of state-of-the-art multimodal large language models (LLMs) built upon the Mistral-7b model and tailored for financial analysis. FinTral integrates te…
Beyond English: Evaluating LLMs for Arabic Grammatical Error Correction
Sang Yun Kwon, Gagan Bhatia, El Moatez Billah Nagoudi +1
Large language models (LLMs) finetuned to follow human instruction have recently exhibited significant capabilities in various English NLP tasks. However, their performance in gram…
Violet: A Vision-Language Model for Arabic Image Captioning with Gemini Decoder
Abdelrahman Mohamed, Fakhraddin Alwajih, El Moatez Billah Nagoudi +2
Although image captioning has a vast array of applications, it has not reached its full potential in languages other than English. Arabic, for instance, although the native languag…
ProMap: Effective Bilingual Lexicon Induction via Language Model Prompting
Abdellah El Mekki, Muhammad Abdul-Mageed, ElMoatez Billah Nagoudi +2
Bilingual Lexicon Induction (BLI), where words are translated between two languages, is an important NLP task. While noticeable progress on BLI in rich resource languages using sta…
Octopus: A Multitask Model and Toolkit for Arabic Natural Language Generation
AbdelRahim Elmadany, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
Understanding Arabic text and generating human-like responses is a challenging endeavor. While many researchers have proposed models and solutions for individual problems, there is…
NADI 2023: The Fourth Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, AbdelRahim Elmadany, Chiyu Zhang +3
We describe the findings of the fourth Nuanced Arabic Dialect Identification Shared Task (NADI 2023). The objective of NADI is to help advance state-of-the-art Arabic NLP by creati…
ChatGPT for Arabic Grammatical Error Correction
Sang Yun Kwon, Gagan Bhatia, El Moatez Billah Nagoud +1
Recently, large language models (LLMs) fine-tuned to follow human instruction have exhibited significant capabilities in various English NLP tasks. However, their performance in gr…
TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties
Karima Kadaoui, Samar M. Magdy, Abdul Waheed +4
Despite the purported multilingual proficiency of instruction-finetuned large language models (LLMs) such as ChatGPT and Bard, the linguistic inclusivity of these models remains in…
Dolphin: A Challenging and Diverse Benchmark for Arabic NLG
El Moatez Billah Nagoudi, AbdelRahim Elmadany, Ahmed El-Shangiti +1
We present Dolphin, a novel benchmark that addresses the need for a natural language generation (NLG) evaluation framework dedicated to the wide collection of Arabic languages and…
GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP
Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi +1
ChatGPT's emergence heralds a transformative phase in NLP, particularly demonstrated through its excellent performance on many English benchmarks. However, the model's efficacy acr…
Zero-Shot Slot and Intent Detection in Low-Resource Languages
Sang Yun Kwon, Gagan Bhatia, El Moatez Billah Nagoudi +2
Intent detection and slot filling are critical tasks in spoken and natural language understanding for task-oriented dialog systems. In this work we describe our participation in th…
ORCA: A Challenging Benchmark for Arabic Language Understanding
AbdelRahim Elmadany, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
Due to their crucial role in all NLP, several benchmarks have been proposed to evaluate pretrained language models. In spite of these efforts, no public benchmark of diverse nature…
JASMINE: Arabic GPT Models for Few-Shot Learning
El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany +2
Scholarship on generative pretraining (GPT) remains acutely Anglocentric, leaving serious gaps in our understanding of the whole class of autoregressive models. For example, we hav…
A Benchmark Study of Contrastive Learning for Arabic Social Meaning
Md Tawkat Islam Khondaker, El Moatez Billah Nagoudi, AbdelRahim Elmadany +2
Contrastive learning (CL) brought significant progress to various NLP tasks. Despite this progress, CL has not been applied to Arabic NLP to date. Nor is it clear how much benefits…
TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation
El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
We present TURJUMAN, a neural toolkit for translating from 20 languages into Modern Standard Arabic (MSA). TURJUMAN exploits the recently-introduced text-to-text Transformer AraT5…
Decay No More: A Persistent Twitter Dataset for Learning Social Meaning
Chiyu Zhang, Muhammad Abdul-Mageed, El Moatez Billah Nagoudi
With the proliferation of social media, many studies resort to social media to construct datasets for developing social meaning understanding systems. For the popular case of Twitt…
AraT5: Text-to-Text Transformers for Arabic Language Generation
El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
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…
Investigating Code-Mixed Modern Standard Arabic-Egyptian to English Machine Translation
El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
Recent progress in neural machine translation (NMT) has made it possible to translate successfully between monolingual language pairs where large parallel data exist, with pre-trai…
Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing
Ganesh Jawahar, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed +1
We describe models focused at the understudied problem of translating between monolingual and code-mixed language pairs. More specifically, we offer a wide range of models that con…