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Related Questions
- How do current large language models handle figurative language, such as idioms and colloquial expressions, in text understanding and generation tasks?
- What are the common challenges that LLMs face when processing idiomatic expressions, and how do they impact the overall performance of these models?
- Can you explain the difference between literal and figurative language processing in LLMs, and how idioms and colloquial expressions fit into this distinction?
- What are some strategies that researchers are exploring to improve LLMs' ability to understand and generate idiomatic language, such as using context, semantics, or pragmatics?
- How do idiomatic expressions affect the interpretability and transparency of LLMs, and what are the implications for their deployment in real-world applications?
- Can you discuss the trade-offs between the complexity of idiomatic language processing and the computational resources required to support it in LLMs?
- What are some examples of idiomatic expressions that are particularly challenging for LLMs to process, and how do they reflect the limitations of current language understanding capabilities?
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