Releases a 457-sentence Komi-Yazva--Russian parallel corpus and shows that retrieval-based few-shot prompting improves LLM translation over zero-shot in this low-resource setting, with performance varying by model and metric.
Findings of the Association for Computational Linguistics: ACL 2023 , month = jul, year =
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A Komi-Yazva--Russian Parallel Corpus and Evaluation Protocol for Zero- and Few-Shot LLM Translation
Releases a 457-sentence Komi-Yazva--Russian parallel corpus and shows that retrieval-based few-shot prompting improves LLM translation over zero-shot in this low-resource setting, with performance varying by model and metric.