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Related Questions
- What are the primary techniques used to identify context in sentiment analysis for large language models?
- How do large language models handle idiomatic expressions and figurative language in sentiment analysis?
- What role does contextualized word embeddings play in enabling large language models to understand context in sentiment analysis?
- Can you explain the concept of contextualized learning and its impact on large language models' ability to understand context?
- How do large language models handle out-of-vocabulary words and their impact on sentiment analysis?
- What is the relationship between attention mechanisms and large language models' ability to understand context in sentiment analysis?
- What are some common challenges faced by large language models in understanding context in sentiment analysis and how can they be addressed?
- Can you discuss the importance of pre-training large language models on large datasets for sentiment analysis tasks?
- How do large language models incorporate common sense knowledge to better understand context in sentiment analysis?
- What is the impact of multimodal learning on large language models' ability to understand context in sentiment analysis?
- Can you explain how large language models use discourse structure to understand context in sentiment analysis?
- What are some future directions for research in large language models and their ability to understand context in sentiment analysis?
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