141 citations · 150 across the 4 of their papers we have counts for
4 papers
Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigation
Bashar Alhafni, Go Inoue, Christian Khairallah +1
Grammatical error correction (GEC) is a well-explored problem in English with many existing models and datasets. However, research on GEC in morphologically rich languages has been…
Camelira: An Arabic Multi-Dialect Morphological Disambiguator
Ossama Obeid, Go Inoue, Nizar Habash
We present Camelira, a web-based Arabic multi-dialect morphological disambiguation tool that covers four major variants of Arabic: Modern Standard Arabic, Egyptian, Gulf, and Levan…
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…
The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models
Go Inoue, Bashar Alhafni, Nurpeiis Baimukan +2
In this paper, we explore the effects of language variants, data sizes, and fine-tuning task types in Arabic pre-trained language models. To do so, we build three pre-trained langu…