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Related Questions
- What are the key differences between source and target domains in entity categorization, and how do domain adaptation techniques address these differences?
- How can adversarial training be used to improve the robustness of entity categorization models in the target domain?
- What are some common techniques used in domain adaptation for entity categorization, such as multi-task learning, self-training, and pivot-based adaptation?
- How can the choice of training data and the preprocessing of text data impact the performance of entity categorization models in the target domain?
- What is the role of domain-invariant features in domain adaptation for entity categorization, and how can they be extracted?
- How can domain adaptation techniques be used to handle the problem of class imbalance in entity categorization, where some categories have much fewer instances than others?
- What are some recent advances in domain adaptation techniques for entity categorization, such as meta-learning and few-shot learning?
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