KyrgyzNLP: Challenges, Progress, and Future
Journal: arXiv (Cornell University)
Year: 2024

Large language models (LLMs) have excelled in numerous benchmarks, advancing AI applications in both linguistic and non-linguistic tasks. However, this has primarily benefited well-resourced languages, leaving less-resourced ones (LRLs) at a disadvantage. In this paper, we highlight the current state of the NLP field in the specific LRL: kyrgyz tili. Human evaluation, including annotated datasets created by native speakers, remains an irreplaceable component of reliable NLP performance, especial