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 advance automatic summarization and generation techniques, with a focus on aspect-aware methods that capture fine-grained information and sentiment within concise textual representations.
Extended Abstracts
Kushan Hewapathirana, Nisansa de Silva, and C. D. Athuraliya, "Adapter-based Fine-tuning for PRIMERA", in 1st Applied Data Science \& Artificial Intelligence Symposium, April. 2025.
