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Related Questions
- How do LLMs handle homophones in natural language processing?
- What techniques do LLMs use to disambiguate words with multiple meanings?
- Can LLMs learn to recognize homophones through supervised or unsupervised learning?
- How do contextual clues influence LLMs' ability to distinguish between homophones?
- What role do linguistic resources, such as dictionaries and thesauri, play in LLMs' homophone disambiguation?
- Are there specific algorithms or models that excel in handling homophones with different meanings?
- Can LLMs be fine-tuned to improve their performance on homophone disambiguation tasks?
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