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Related Questions
- Can you explain how entity-based attention allows the model to focus on specific entities in a sentence?
- How does entity-based attention capture the nuances of relationships between entities, such as hierarchical or causal relationships?
- What are some common applications of entity-based attention in natural language processing tasks, such as question answering or text classification?
- How does entity-based attention differ from traditional attention mechanisms, such as additive attention or scalar multiplication?
- Can you provide examples of how entity-based attention can be used to improve the performance of downstream tasks, such as named entity recognition or relation extraction?
- What are some challenges or limitations of entity-based attention, and how can they be addressed in practice?
- How can entity-based attention be combined with other techniques, such as graph-based methods or memory-augmented neural networks, to capture even more nuanced relationships between entities?
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