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20192024
most citedmEdIT: Multilingual Text Editing via Instruction Tuning

3 citations · 4 across the 6 of their papers we have counts for

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cs.CL2025

ARWI: Arabic Write and Improve

Kirill Chirkunov, Bashar Alhafni, Chatrine Qwaider +2

Although Arabic is spoken by over 400 million people, advanced Arabic writing assistance tools remain limited. To address this gap, we present ARWI, a new writing assistant that he…

cs.CL2024

Strategies for Arabic Readability Modeling

Juan Piñeros Liberato, Bashar Alhafni, Muhamed Al Khalil +1

Automatic readability assessment is relevant to building NLP applications for education, content analysis, and accessibility. However, Arabic readability assessment is a challengin…

cs.CL2024

The SAMER Arabic Text Simplification Corpus

Bashar Alhafni, Reem Hazim, Juan Piñeros Liberato +2

We present the SAMER Corpus, the first manually annotated Arabic parallel corpus for text simplification targeting school-aged learners. Our corpus comprises texts of 159K words se…

cs.CL2024

Personalized Text Generation with Fine-Grained Linguistic Control

Bashar Alhafni, Vivek Kulkarni, Dhruv Kumar +1

As the text generation capabilities of large language models become increasingly prominent, recent studies have focused on controlling particular aspects of the generated text to m…

cs.CL20243 cited

mEdIT: Multilingual Text Editing via Instruction Tuning

Vipul Raheja, Dimitris Alikaniotis, Vivek Kulkarni +2

We introduce mEdIT, a multi-lingual extension to CoEdIT -- the recent state-of-the-art text editing models for writing assistance. mEdIT models are trained by fine-tuning multi-lin…

cs.CL2022

Zero-shot Cross-Linguistic Learning of Event Semantics

Malihe Alikhani, Thomas Kober, Bashar Alhafni +6

Typologically diverse languages offer systems of lexical and grammatical aspect that allow speakers to focus on facets of event structure in ways that comport with the specific com…