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Related Questions
- What are the key differences between multi-task learning and transfer learning, and how do they impact contextual understanding in language models?
- Can you provide examples of how multi-task learning can improve contextual understanding in language models, such as in sentiment analysis or question-answering tasks?
- How does transfer learning enable language models to generalize across different domains and tasks, and what are the implications for contextual understanding?
- What are some challenges and limitations of using multi-task learning and transfer learning for improving contextual understanding in language models?
- How can the use of multi-task learning and transfer learning be combined with other techniques, such as attention mechanisms or graph-based methods, to further improve contextual understanding?
- Can you discuss the role of pre-training and fine-tuning in multi-task learning and transfer learning, and how they contribute to improved contextual understanding?
- What are some potential applications of multi-task learning and transfer learning in real-world language models, such as conversational AI or text summarization?
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