14 citations · 24 across the 13 of their papers we have counts for
13 papers
UK-PRBENCH: A Paragraph-Level Precedent Retrieval Benchmark for United Kingdom Case Law
Damith Premasiri, Tharindu Ranasinghe
Prior case retrieval (PCR) aims to identify precedent cases relevant to a given query case. Existing PCR benchmarks and methods predominantly operate at the document level, treatin…
APEX-VW: A Document-Level English-Spanish Post-Editing Dataset in the Healthcare Domain
Marie Escribe, Tharindu Ranasinghe, Amal Haddad Haddad +2
Post-Editing (PE) of Machine Translation (MT) output often involves repeating the same lexical and terminological corrections across many segments, especially in specialised and hi…
LLM-based Embedders for Prior Case Retrieval
Damith Premasiri, Tharindu Ranasinghe, Ruslan Mitkov
In common law systems, legal professionals such as lawyers and judges rely on precedents to build their arguments. As the volume of cases has grown massively over time, effectively…
Overview of the First Workshop on Language Models for Low-Resource Languages (LoResLM 2025)
Hansi Hettiarachchi, Tharindu Ranasinghe, Paul Rayson +5
The first Workshop on Language Models for Low-Resource Languages (LoResLM 2025) was held in conjunction with the 31st International Conference on Computational Linguistics (COLING…
A Federated Learning Approach to Privacy Preserving Offensive Language Identification
Marcos Zampieri, Damith Premasiri, Tharindu Ranasinghe
The spread of various forms of offensive speech online is an important concern in social media. While platforms have been investing heavily in ways of coping with this problem, the…
NSINA: A News Corpus for Sinhala
Hansi Hettiarachchi, Damith Premasiri, Lasitha Uyangodage +1
The introduction of large language models (LLMs) has advanced natural language processing (NLP), but their effectiveness is largely dependent on pre-training resources. This is esp…
Can Model Fusing Help Transformers in Long Document Classification? An Empirical Study
Damith Premasiri, Tharindu Ranasinghe, Ruslan Mitkov
Text classification is an area of research which has been studied over the years in Natural Language Processing (NLP). Adapting NLP to multiple domains has introduced many new chal…
Deep Learning Methods for Extracting Metaphorical Names of Flowers and Plants
Amal Haddad Haddad, Damith Premasiri, Tharindu Ranasinghe +1
The domain of Botany is rich with metaphorical terms. Those terms play an important role in the description and identification of flowers and plants. However, the identification of…
SOLD: Sinhala Offensive Language Dataset
Tharindu Ranasinghe, Isuri Anuradha, Damith Premasiri +4
The widespread of offensive content online, such as hate speech and cyber-bullying, is a global phenomenon. This has sparked interest in the artificial intelligence (AI) and natura…
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…
BERT(s) to Detect Multiword Expressions
Damith Premasiri, Tharindu Ranasinghe
Multiword expressions (MWEs) present groups of words in which the meaning of the whole is not derived from the meaning of its parts. The task of processing MWEs is crucial in many…
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…