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Found 10 papers, 5 papers with code
DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
The goal of the Qur’an QA 2022 shared task is to fill this gap by producing state-of-the-art question answering and reading comprehension research on Qur’an.
A Federated Learning Approach to Privacy Preserving Offensive Language Identification
Since most social media data originates from end users, we propose a privacy preserving decentralized architecture for identifying offensive language online by introducing Federated Learning (FL) in the context of offensive language identification.
NSINA: A News Corpus for Sinhala
NSINA is the largest news corpus for Sinhala, available up to date.
Can Model Fusing Help Transformers in Long Document Classification? An Empirical Study
Text classification is an area of research which has been studied over the years in Natural Language Processing (NLP).
Deep Learning Methods for Extracting Metaphorical Names of Flowers and Plants
The domain of Botany is rich with metaphorical terms.
SOLD: Sinhala Offensive Language Dataset
SOLD is a manually annotated dataset containing 10, 000 posts from Twitter annotated as offensive and not offensive at both sentence-level and token-level, improving the explainability of the ML models.
Overview of the HASOC Subtrack at FIRE 2022: Offensive Language Identification in Marathi
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 content automatically.
Transformer-based Detection of Multiword Expressions in Flower and Plant Names
In this paper, we explore state-of-the-art neural transformers in the task of detecting MWEs in flower and plant names.
BERT(s) to Detect Multiword Expressions
Multiword expressions (MWEs) present groups of words in which the meaning of the whole is not derived from the meaning of its parts.
DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
The goal of the Qur'an QA 2022 shared task is to fill this gap by producing state-of-the-art question answering and reading comprehension research on Qur'an.
