1 citations · 2 across the 7 of their papers we have counts for
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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…
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,…
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…
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…
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…