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Related Questions
- How does the capacity of a large language model to store and process vast amounts of world knowledge impact its ability to generalize to new tasks and domains?
- Can you describe the role of knowledge graph representations in enabling large language models to transfer knowledge across different domains?
- How does the size and quality of the training dataset affect the ability of a large language model to generalize and adapt to new, unseen tasks and domains?
- What are some common challenges that large language models face when generalizing to new domains, and how can these challenges be addressed?
- Can you explain the relationship between language model fine-tuning and its ability to adapt to new tasks and domains?
- How do large language models leverage their prior knowledge to make sense of new, unseen data and generalize to new domains?
- Can you discuss the importance of knowledge fusion in enabling large language models to integrate information from multiple sources and generalize to new domains?
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