2025
FSTs vs ICL: Generalisation in LLMs for an under-resourced language
EMNLP 2025
LLMs have been widely adopted to tackle many traditional NLP tasks. Their effectiveness remains uncertain in scenarios where pre-trained models have limited prior knowledge of a language. In this work, we examine LLMs’ generalization in under-resourced settings through the task of orthographic norma