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Related Questions
- What are the key differences between fine-tuning and adapting pre-trained LLMs for visual tasks?
- How does data augmentation in the context of transfer learning help LLMs generalize to viewpoint and lighting variations?
- What is the role of self-supervised learning in transfer learning for visual tasks, and how does it contribute to generalization?
- Can you explain the concept of domain adaptation in transfer learning, and how it applies to LLMs for visual tasks?
- What are some common techniques used to handle class imbalance in transfer learning for visual tasks?
- How does transfer learning help LLMs generalize to new classes or objects that were not seen during training?
- What are some strategies for selecting the right pre-trained model and fine-tuning parameters for a specific visual task?
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