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Related Questions
- What are some common problems in obtaining and labeling sufficient training data for low-resource languages?
- How do lack of standardized language resources, such as dictionaries and linguistic corpora, impact LLM training?
- Can you explain the difficulties of finding and selecting suitable annotation tools and workflows for LLM training in low-resource languages?
- What are some strategies to overcome the dearth of in-domain, high-quality training data in low-resource languages?
- How do biases in linguistic data and model training practices affect LLM performance and reliability in low-resource languages?
- Are there any creative solutions, such as exploiting transfer learning, multi-lingual training, or few-shot learning, that can overcome the challenges in training LLMs for low-resource languages?
- What are the implications for model evaluation, validation, and testing when working with low-resource languages, considering the limited available data?
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