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Related Questions
- Can you explain the concept of pre-trained models and how they facilitate transfer learning in language models?
- How does the pre-trained model's knowledge about visual concepts and objects enable language models to generalize across different image recognition tasks?
- What are some common techniques used in domain adaptation to adapt a pre-trained model to a new domain or task?
- How does the use of meta-learning in transfer learning enable language models to learn from a few examples and adapt to new tasks?
- Can you discuss the role of feature extraction in transfer learning and how it enables language models to extract relevant features from images?
- What are some challenges in applying transfer learning and domain adaptation to language models, and how can they be addressed?
- Can you provide examples of successful applications of transfer learning and domain adaptation in image recognition tasks, such as object detection and segmentation?
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