PI: Nisansa de Silva
We propose to advance natural language processing for low-resource settings by leveraging data augmentation, transfer learning, and model adaptation techniques to overcome the scarcity of annotated data and linguistic resources.
PI: Nisansa de Silva
We propose to build and analyze Sinhala language resources, datasets, and models to strengthen NLP research for this low-resource language, while connecting it to English and Tamil through bilingual lexicons, embeddings, and cross-lingual methods.
PI: Nisansa de Silva
We propose to advance automatic summarization and generation techniques, with a focus on aspect-aware methods that capture fine-grained information and sentiment within concise textual representations.
Theses: MSc Minor Component Research
Pubudu Cooray, "Headline Generation for Sinhala Newspaper Articles using Pre-trained Language Models", University of Moratuwa, 2025
Dushan Kumarasinghe, "Automatic Generation of Research Paper Abstracts using Deep-Hybrid Models", University of Moratuwa, 2025
Kushan Hewapathirana, "Towards Multi-document Summarisation in Low-resource Settings", University of Moratuwa, 2025
Akila Peiris, "Dungeons \& Dragons Fantasy Adventure Generation", University of Moratuwa, 2024
Conference Papers
Dushan Kumarasinghe and Nisansa de Silva, "Abstract Generation with Hybrid Model Supported by Relevance Matrix", in International Conference on Computational Collective Intelligence, 2024, pp. 211--223. doi: 10.1007/978-3-031-70816-9_17
