60 citations · 119 across the 36 of their papers we have counts for
9 papers · 1 filter
Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq Approaches
Yomal De Mel, Kasun Wickramasinghe, Nisansa de Silva +1
Due to reasons of convenience and lack of tech literacy, transliteration (i.e., Romanizing native scripts instead of using localization tools) is eminently prevalent in the context…
Unsupervised Bilingual Lexicon Induction for Low Resource Languages
Charitha Rathnayake, P. R. S. Thilakarathna, Uthpala Nethmini +2
Bilingual lexicons play a crucial role in various Natural Language Processing tasks. However, many low-resource languages (LRLs) do not have such lexicons, and due to the same reas…
Large Language Models for Ingredient Substitution in Food Recipes using Supervised Fine-tuning and Direct Preference Optimization
Thevin Senath, Kumuthu Athukorala, Ransika Costa +2
In this paper, we address the challenge of recipe personalization through ingredient substitution. We make use of Large Language Models (LLMs) to build an ingredient substitution s…
SiTSE: Sinhala Text Simplification Dataset and Evaluation
Surangika Ranathunga, Rumesh Sirithunga, Himashi Rathnayake +4
Text Simplification is a task that has been minimally explored for low-resource languages. Consequently, there are only a few manually curated datasets. In this paper, we present a…
Transfer Learning on Transformers for Building Energy Consumption Forecasting -- A Comparative Study
Robert Spencer, Surangika Ranathunga, Mikael Boulic +2
This study investigates the application of Transfer Learning (TL) on Transformer architectures to enhance building energy consumption forecasting. Transformers are a relatively new…
Shoulders of Giants: A Look at the Degree and Utility of Openness in NLP Research
Surangika Ranathunga, Nisansa de Silva, Dilith Jayakody +1
We analysed a sample of NLP research papers archived in ACL Anthology as an attempt to quantify the degree of openness and the benefit of such an open culture in the NLP community.…
Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning
Teo Susnjak, Peter Hwang, Napoleon H. Reyes +3
This research pioneers the use of fine-tuned Large Language Models (LLMs) to automate Systematic Literature Reviews (SLRs), presenting a significant and novel contribution in integ…
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation
Tong Su, Xin Peng, Sarubi Thillainathan +3
Parameter-efficient fine-tuning (PEFT) methods are increasingly vital in adapting large-scale pre-trained language models for diverse tasks, offering a balance between adaptability…
Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora
Surangika Ranathunga, Nisansa de Silva, Menan Velayuthan +2
We conducted a detailed analysis on the quality of web-mined corpora for two low-resource languages (making three language pairs, English-Sinhala, English-Tamil and Sinhala-Tamil).…