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Related Questions
- How does semantic similarity contribute to LLMs' ability to distinguish between homophone words in a self-supervised learning setting?
- In what ways do LLMs use semantic similarity to identify and differentiate between homophone pairs?
- Can you explain how LLMs learn to recognize homophones through self-supervised learning and what role semantic similarity plays in this process?
- How do LLMs leverage semantic similarity to overcome the challenges of homophone recognition in natural language processing?
- In self-supervised learning, what is the relationship between semantic similarity and LLMs' accuracy in identifying homophones?
- What are the key factors that influence LLMs' ability to use semantic similarity to recognize homophones?
- Can you provide an example of how LLMs apply semantic similarity to identify homophones and improve their overall performance in NLP tasks?
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