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Related Questions
- How do non-contextual models struggle with idiomatic expressions in natural language processing tasks such as sentiment analysis and machine translation?
- Can you provide examples of real-world applications where non-contextual models' limitations on idiomatic expressions lead to inaccurate results or misinterpretations?
- In what ways do non-contextual models' inability to understand idiomatic expressions impact their performance in tasks like text summarization and question answering?
- How do idiomatic expressions affect the accuracy of non-contextual models in applications such as language translation and speech recognition?
- What are some potential consequences of relying on non-contextual models in applications where idiomatic expressions are common, such as in customer service chatbots or language learning platforms?
- Can you discuss the limitations of non-contextual models in understanding figurative language, such as metaphors and sarcasm, and how this impacts their performance in real-world applications?
- In what ways can the limitations of non-contextual models on idiomatic expressions be addressed through the use of contextual models or other techniques, such as transfer learning or multimodal learning?
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