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Related Questions
- How does entity-based attention address the issue of out-of-vocabulary words in large language models?
- Can you provide an example of how entity-based attention is used to handle out-of-vocabulary words in a specific LLM architecture?
- What are the benefits of using entity-based attention in handling out-of-vocabulary words compared to traditional approaches?
- How does entity-based attention improve the performance of LLMs on tasks that involve out-of-vocabulary words?
- Can you explain the concept of entity-based attention and its application in LLMs?
- What are some common challenges in handling out-of-vocabulary words in LLMs, and how does entity-based attention address them?
- How does entity-based attention affect the training process of LLMs, and what are the implications for model development?
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