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Related Questions
- What is the concept of out-of-vocabulary (OOV) handling in neural machine translation, and how does it relate to unseen entities in entity-based attention models?
- Can you explain the role of subword modeling in addressing the problem of unseen entities during inference in language models?
- How do you handle unknown entities in a pre-trained transformer-based language model during downstream tasks?
- What are some common techniques used to mitigate the impact of unseen entities in sequence-to-sequence models, such as machine translation or text summarization?
- Can you discuss the effect of unknown entities on the performance of entity-based attention models in tasks such as named entity recognition and coreference resolution?
- How do you evaluate the robustness of a model to unseen entities in a test dataset, and what metrics are commonly used for this purpose?
- What is the relationship between entity embedding and the performance of entity-based attention models on unseen entities, and how can entity embeddings be improved for better performance?
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