A Dataset for Research on Modelling Depression Severity in Online Forum Data

no code implementations • RANLP 2021 • Isuri Anuradha Nanomi Arachchige, Vihangi Himaya Jayasuriya, Ruvan Weerasinghe

People communicate more with online forums to find answers for their psychological disease.

CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

1 code implementation • 4 Apr 2024 • Nirmalie Wiratunga, Ramitha Abeyratne, Lasal Jayawardena, Kyle Martin, Stewart Massie, Ikechukwu Nkisi-Orji, Ruvan Weerasinghe, Anne Liret, Bruno Fleisch

Retrieval-Augmented Generation (RAG) enhances Large Language Model (LLM) output by providing prior knowledge as context to input.

Language Modelling Large Language Model +2

Aspect Oriented Suggestion Extraction from Online Reviews

no code implementations • 20th IEEE International Conference on Machine Learning and Applications (ICMLA) 2021 • Tharushi Jayasekara, Ruvan Weerasinghe, Viraj Welgama

Extracting these suggestions with respect to the aspects that reviewers are not satisfied with, could be used as a potential solution to improve products.

Aspect Extraction Language Modelling +1

Determining the Ethno-nationality of Writers Using Written English Text

no code implementations • 29 Sep 2021 • Deenuka Niroshini Perera, Ruvan Weerasinghe, Randhil Pushpananda

The current literature mainly focuses on determining the native language of English writers and a minimal number of researches have been conducted in determining the country-of-origin of English writers.

Sinhala-Tamil Machine Translation: Towards better Translation Quality

no code implementations • ALTA 2014 • Pushpan, R a, il, Ruvan Weerasinghe, Mahesan Niranjan

Machine Translation Translation

Collaboratively Building Language Resources while Localising the Web

no code implementations • WS 2012 • Asanka Wasala, Reinhard Sch{\"a}ler, Ruvan Weerasinghe, Chris Exton

Machine Translation