Papers by Victor Mijangos

1 papers
FSTs vs ICL: Generalisation in LLMs for an under-resourced language (2025.findings-emnlp)

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Challenge: LLMs have been widely adopted to tackle many traditional NLP tasks, but their effectiveness remains uncertain in scenarios where pre-trained models have limited prior knowledge of a language.
Approach: They propose a rule-based method using a finite-state transducer and an in-context learning method that provides the model with string transduction examples.
Outcome: The proposed method outperforms FSTs in zero-shot settings while ICL surpasses FLMs.

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