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Related Questions
- What are the key components of a large language model's architecture that enable it to generalize across similar tasks?
- How do large language models learn to recognize and leverage patterns in language that facilitate generalization across tasks?
- What role does transfer learning play in enabling large language models to generalize across similar tasks?
- How does the similarity between tasks influence the activation of neural connections in large language models?
- What is the relationship between task similarity and the formation of abstract representations in large language models?
- Can you explain how large language models use contextual information to disambiguate similar tasks and generalize accordingly?
- What are some common pitfalls or challenges that arise when trying to generalize large language models across similar tasks, and how can they be addressed?
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