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Related Questions
- How do language models detect and interpret literal versus non-literal expressions in a given context?
- What techniques can be used to identify figurative language and idiomatic expressions, and how can they be disambiguated from literal meanings?
- Can you discuss the importance of understanding implied meaning, tone, and speaker's intent in capturing contextual information?
- How can machine learning algorithms be fine-tuned to handle metaphors, metonymy, and other complex figurative language mechanisms?
- What approaches can be taken to create training data that effectively capture nuances of figurative language, without relying on annotation and validation?
- In text classification tasks, how do you address overfitting and underfitting of models when training on tasks involving figurative language and idioms?
- Can you propose ways to evaluate the efficacy of methods for handling figurative language and idiomatic expressions, and how this affects broader contextual understanding in language modeling?
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