78 citations · 156 across the 29 of their papers we have counts for
12 papers · 1 filter
Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages
Thomas Mandl, Sandip Modha, Gautam Kishore Shahi +8
The widespread of offensive content online such as hate speech poses a growing societal problem. AI tools are necessary for supporting the moderation process at online platforms. F…
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…
Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi
Saurabh Gaikwad, Tharindu Ranasinghe, Marcos Zampieri +1
The widespread presence of offensive language on social media motivated the development of systems capable of recognizing such content automatically. Apart from a few notable excep…
WLV-RIT at GermEval 2021: Multitask Learning with Transformers to Detect Toxic, Engaging, and Fact-Claiming Comments
Skye Morgan, Tharindu Ranasinghe, Marcos Zampieri
This paper addresses the identification of toxic, engaging, and fact-claiming comments on social media. We used the dataset made available by the organizers of the GermEval-2021 sh…
An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers
Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov
Most studies on word-level Quality Estimation (QE) of machine translation focus on language-specific models. The obvious disadvantages of these approaches are the need for labelled…