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Related Questions
- How do large language models learn to capture nuances of figurative language across different linguistic and cultural contexts?
- What are the key factors that influence the ability of large language models to recognize and generate metaphors in languages with distinct grammatical and semantic structures?
- Can you explain the role of corpus size and diversity in enabling large language models to learn metaphorical language in languages with unique grammatical and semantic characteristics?
- How do large language models handle ambiguity and polysemy when learning to recognize and generate metaphors in languages with complex semantic structures?
- What are the implications of large language models' ability to recognize and generate metaphors for natural language processing and generation applications?
- Can you discuss the potential challenges and limitations of training large language models to recognize and generate metaphors in languages with limited training data?
- How do large language models integrate knowledge from multiple sources, such as linguistic theories and lexical resources, to improve their metaphor recognition and generation capabilities?
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