activity
20162026
most citedMorphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects

7 citations · 15 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2026

YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models

Mahmoud Reda, Salam Khalifa, Reham Marzouk +1

Arabic morphology remains challenging for large language models, since fluent generation does not guarantee accurate morphosyntactic control. Existing Arabic evaluations mainly tar…

cs.CL2025

Proper Noun Diacritization for Arabic Wikipedia: A Benchmark Dataset

Rawan Bondok, Mayar Nassar, Salam Khalifa +2

Proper nouns in Arabic Wikipedia are frequently undiacritized, creating ambiguity in pronunciation and interpretation, especially for transliterated named entities of foreign origi…

cs.CL2024★ 2 cited

Computational Morphology and Lexicography Modeling of Modern Standard Arabic Nominals

Christian Khairallah, Reham Marzouk, Salam Khalifa +2

Modern Standard Arabic (MSA) nominals present many morphological and lexical modeling challenges that have not been consistently addressed previously. This paper attempts to define…

cs.CL2023

Exploring Linguistic Probes for Morphological Generalization

Jordan Kodner, Salam Khalifa, Sarah Payne

Modern work on the cross-linguistic computational modeling of morphological inflection has typically employed language-independent data splitting algorithms. In this paper, we supp…

cs.CL2023

Morphological Inflection: A Reality Check

Jordan Kodner, Sarah Payne, Salam Khalifa +1

Morphological inflection is a popular task in sub-word NLP with both practical and cognitive applications. For years now, state-of-the-art systems have reported high, but also high…

cs.CL2021★ 7 cited

Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects

Go Inoue, Salam Khalifa, Nizar Habash

We present state-of-the-art results on morphosyntactic tagging across different varieties of Arabic using fine-tuned pre-trained transformer language models. Our models consistentl…

cs.CL2018★ 6 cited

MADARi: A Web Interface for Joint Arabic Morphological Annotation and Spelling Correction

Ossama Obeid, Salam Khalifa, Nizar Habash +3

In this paper, we introduce MADARi, a joint morphological annotation and spelling correction system for texts in Standard and Dialectal Arabic. The MADARi framework provides intuit…

cs.CL2016

A Large Scale Corpus of Gulf Arabic

Salam Khalifa, Nizar Habash, Dana Abdulrahim +1

Most Arabic natural language processing tools and resources are developed to serve Modern Standard Arabic (MSA), which is the official written language in the Arab World. Some Dial…