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Related Questions
- What are the key techniques used by large language models to learn new words and concepts from limited data in rapidly changing domains?
- How do LLMs handle out-of-vocabulary words and maintain their performance in dynamic environments?
- What is the role of transfer learning in enabling LLMs to adapt to new vocabulary and domains?
- Can you explain the concept of domain adaptation in LLMs and its importance in real-world applications?
- How do LLMs handle the problem of vocabulary drift, where the distribution of words and their meanings changes over time?
- What are some strategies for fine-tuning LLMs to adapt to new vocabulary and domains, such as few-shot learning and meta-learning?
- How do LLMs balance the trade-off between learning new vocabulary and maintaining their existing knowledge and performance?
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