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Related Questions
- How does multi-task learning allow a model to learn multiple tasks simultaneously and improve its overall performance?
- What are some common tasks that are often combined in multi-task learning, and how can they help a model respond to context-dependent language?
- Can you explain the concept of transfer learning and how it can be used to adapt a pre-trained model to a new task or domain?
- How can pre-training a model on a large corpus of text and then fine-tuning it on a smaller dataset improve its ability to respond to context-dependent language?
- What are some challenges that models may face when trying to respond to context-dependent language, and how can multi-task learning and transfer learning help address these challenges?
- Can you provide some examples of how multi-task learning and transfer learning have been used in natural language processing to improve model performance on context-dependent language tasks?
- How can the use of multi-task learning and transfer learning be combined to create a more robust and adaptable model that can respond to a wide range of context-dependent language tasks?
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