2 citations · 2 across the 13 of their papers we have counts for
14 papers
A Character-Level Neural Approach to Sinhala Sandhi Splitting
Yasas Ekanayaka, Deshan Sumanathilaka
Sinhala Sandhi splitting recovers the constituent words or morphemes hidden inside a phonologically merged surface form. The task is important for Sinhala NLP because Sandhi obscur…
SwanNLP at SemEval-2026 Task 5: An LLM-based Framework for Plausibility Scoring in Narrative Word Sense Disambiguation
Deshan Sumanathilaka, Nicholas Micallef, Julian Hough +1
Recent advances in language models have substantially improved Natural Language Understanding (NLU). Although widely used benchmarks suggest that Large Language Models (LLMs) can e…
An Exploration-Analysis-Disambiguation Reasoning Framework for Word Sense Disambiguation with Low-Parameter LLMs
Deshan Sumanathilaka, Nicholas Micallef, Julian Hough
Word Sense Disambiguation (WSD) remains a key challenge in Natural Language Processing (NLP), especially when dealing with rare or domain-specific senses that are often misinterpre…
Bridging Lexical Ambiguity and Vision: A Mini Review on Visual Word Sense Disambiguation
Shashini Nilukshi, Deshan Sumanathilaka
This paper offers a mini review of Visual Word Sense Disambiguation (VWSD), which is a multimodal extension of traditional Word Sense Disambiguation (WSD). VWSD helps tackle lexica…
Can Small Language Models Handle Context-Summarized Multi-Turn Customer-Service QA? A Synthetic Data-Driven Comparative Evaluation
Lakshan Cooray, Deshan Sumanathilaka, Pattigadapa Venkatesh Raju
Customer-service question answering (QA) systems increasingly rely on conversational language understanding. While Large Language Models (LLMs) achieve strong performance, their hi…
A Low-Resource Speech-Driven NLP Pipeline for Sinhala Dyslexia Assistance
Peshala Perera, Deshan Sumanathilaka
Dyslexia in adults remains an under-researched and under-served area, particularly in non-English-speaking contexts, despite its significant impact on personal and professional liv…
Prompt Balance Matters: Understanding How Imbalanced Few-Shot Learning Affects Multilingual Sense Disambiguation in LLMs
Deshan Sumanathilaka, Nicholas Micallef, Julian Hough
Recent advances in Large Language Models (LLMs) have significantly reshaped the landscape of Natural Language Processing (NLP). Among the various prompting techniques, few-shot pro…
Swa-bhasha Resource Hub: Romanized Sinhala to Sinhala Transliteration Systems and Data Resources
Deshan Sumanathilaka, Sameera Perera, Sachithya Dharmasiri +6
The Swa-bhasha Resource Hub provides a comprehensive collection of data resources and algorithms developed for Romanized Sinhala to Sinhala transliteration between 2020 and 2025. T…
A Systematic Decade Review of Trip Route Planning with Travel Time Estimation based on User Preferences and Behavior
Nikil Jayasuriya, Deshan Sumanathilaka
This paper systematically explores the advancements in adaptive trip route planning and travel time estimation (TTE) through Artificial Intelligence (AI). With the increasing compl…
IndoNLP 2025: Shared Task on Real-Time Reverse Transliteration for Romanized Indo-Aryan languages
Deshan Sumanathilaka, Isuri Anuradha, Ruvan Weerasinghe +2
The paper overviews the shared task on Real-Time Reverse Transliteration for Romanized Indo-Aryan languages. It focuses on the reverse transliteration of low-resourced languages in…
Can LLMs assist with Ambiguity? A Quantitative Evaluation of various Large Language Models on Word Sense Disambiguation
T. G. D. K. Sumanathilaka, Nicholas Micallef, Julian Hough
Ambiguous words are often found in modern digital communications. Lexical ambiguity challenges traditional Word Sense Disambiguation (WSD) methods, due to limited data. Consequentl…
Swa Bhasha: Message-Based Singlish to Sinhala Transliteration
Maneesha U. Athukorala, Deshan K. Sumanathilaka
Machine Transliteration provides the ability to transliterate a basic language into different languages in a computational way. Transliteration is an important technical process th…
EmoScan: Automatic Screening of Depression Symptoms in Romanized Sinhala Tweets
Jayathi Hewapathirana, Deshan Sumanathilaka
This work explores the utilization of Romanized Sinhala social media data to identify individuals at risk of depression. A machine learning-based framework is presented for the aut…
A Survey on Lexical Ambiguity Detection and Word Sense Disambiguation
Miuru Abeysiriwardana, Deshan Sumanathilaka
This paper explores techniques that focus on understanding and resolving ambiguity in language within the field of natural language processing (NLP), highlighting the complexity of…