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Related Questions
- How do large language models identify and interpret figurative language, such as sarcasm and irony, in text data?
- What techniques are used to detect implicit sentiment in text, and how do they account for the nuances of human language?
- Can you explain the challenges of modeling sarcasm and irony in text, and how researchers address these challenges?
- How do models handle context-dependent sentiment, where the same phrase can have different meanings depending on the conversation or situation?
- What role do linguistic features, such as tone and syntax, play in detecting sarcasm and irony in text?
- Can you discuss the importance of training data quality in accurately detecting implicit sentiment and sarcasm in text?
- How do models differentiate between literal and figurative language, and what implications does this have for sentiment analysis?
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