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Related Questions
- How do context window sizes impact LLMs' ability to disambiguate homophones in English and other languages with complex linguistic features?
- Can varying context window sizes improve or hinder LLMs' performance in handling homophone ambiguity in languages with high morphological complexity?
- What are the implications of using larger context windows on LLMs' ability to capture subtle semantic nuances in homophone disambiguation tasks?
- How do LLMs with different architecture and training data handle homophone ambiguity with varying context window sizes?
- Can context window sizes be used as a hyperparameter to adapt LLMs to different linguistic domains and homophone disambiguation tasks?
- What are the trade-offs between using larger context windows and increased computational resources in LLMs for homophone disambiguation?
- Can the performance of LLMs in handling homophone ambiguity be improved by combining varying context window sizes with other techniques, such as subword modeling or multi-task learning?
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