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Related Questions
- What are the key factors to consider when selecting a pre-training corpus for LLMs in low-resource languages?
- How does the choice of architecture, such as transformer or recurrent neural network (RNN), impact the performance of LLMs in low-resource languages?
- What are the trade-offs between using a large pre-training corpus versus a smaller, more specialized corpus for LLMs in low-resource languages?
- Can you explain the concept of 'domain adaptation' in the context of LLMs and how it relates to low-resource languages?
- How does the choice of pre-training corpus and architecture affect the ability of LLMs to generalize to unseen data in low-resource languages?
- What are some strategies for adapting pre-trained LLMs to low-resource languages, and how do they impact performance?
- Can you discuss the role of multitask learning in improving the performance of LLMs in low-resource languages?
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