12 citations · 46 across the 17 of their papers we have counts for
25 papers · 1 filter
Predicting the Type and Target of Offensive Social Media Posts in Marathi
Marcos Zampieri, Tharindu Ranasinghe, Mrinal Chaudhari +4
The presence of offensive language on social media is very common motivating platforms to invest in strategies to make communities safer. This includes developing robust machine le…
Overview of the HASOC Subtrack at FIRE 2022: Offensive Language Identification in Marathi
Tharindu Ranasinghe, Kai North, Damith Premasiri +1
The widespread of offensive content online has become a reason for great concern in recent years, motivating researchers to develop robust systems capable of identifying such conte…
Transformer-based Detection of Multiword Expressions in Flower and Plant Names
Damith Premasiri, Amal Haddad Haddad, Tharindu Ranasinghe +1
Multiword expression (MWE) is a sequence of words which collectively present a meaning which is not derived from its individual words. The task of processing MWEs is crucial in man…
DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
Damith Premasiri, Tharindu Ranasinghe, Wajdi Zaghouani +1
The task of machine reading comprehension (MRC) is a useful benchmark to evaluate the natural language understanding of machines. It has gained popularity in the natural language p…
Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation
Diptesh Kanojia, Marina Fomicheva, Tharindu Ranasinghe +3
Current Machine Translation (MT) systems achieve very good results on a growing variety of language pairs and datasets. However, they are known to produce fluent translation output…
FBERT: A Neural Transformer for Identifying Offensive Content
Diptanu Sarkar, Marcos Zampieri, Tharindu Ranasinghe +1
Transformer-based models such as BERT, XLNET, and XLM-R have achieved state-of-the-art performance across various NLP tasks including the identification of offensive language and h…