most citedGrammatical Error Correction for Low-Resource Languages: The Case of Zarma

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cs.CL2025

Subasa - Adapting Language Models for Low-resourced Offensive Language Detection in Sinhala

Shanilka Haturusinghe, Tharindu Cyril Weerasooriya, Marcos Zampieri +2

Accurate detection of offensive language is essential for a number of applications related to social media safety. There is a sharp contrast in performance in this task between low…

cs.CL2025

Datasets for Depression Modeling in Social Media: An Overview

Ana-Maria Bucur, Andreea-Codrina Moldovan, Krutika Parvatikar +3

Depression is the most common mental health disorder, and its prevalence increased during the COVID-19 pandemic. As one of the most extensively researched psychological conditions,…

cs.CL2024★ 1 cited

Grammatical Error Correction for Low-Resource Languages: The Case of Zarma

Mamadou K. Keita, Adwoa Bremang, Huy Le +3

Grammatical error correction (GEC) aims to improve text quality and readability. Previous work on the task focused primarily on high-resource languages, while low-resource language…

cs.CL2024

On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook

Ana-Maria Bucur, Andreea-Codrina Moldovan, Krutika Parvatikar +3

Computational approaches to predicting mental health conditions in social media have been substantially explored in the past years. Multiple reviews have been published on this top…

cs.CL2024

ARTICLE: Annotator Reliability Through In-Context Learning

Sujan Dutta, Deepak Pandita, Tharindu Cyril Weerasooriya +3

Ensuring annotator quality in training and evaluation data is a key piece of machine learning in NLP. Tasks such as sentiment analysis and offensive speech detection are intrinsica…