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Related Questions
- What happens to the language understanding and generation capabilities of a pre-trained model when it encounters a new task or domain?
- In what ways does the general knowledge and language understanding pre-trained models acquire during the pre-training phase facilitate task adaptation?
- How does the transfer learning mechanism in pre-trained large language models enable them to leverage knowledge from one domain to another?
- What role does contextual understanding play in the adaptation of pre-trained models to new tasks and domains?
- Can pre-trained models learn to ignore irrelevant information and focus on the most relevant aspects when adapting to new tasks?
- How do the different pre-training tasks and objectives, such as masked language modeling and next sentence prediction, contribute to the adaptability of the model?
- What are some potential strategies for fine-tuning and adapting pre-trained models for specific tasks and domains in a way that maximizes their performance and minimizes the risk of overfitting?
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