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Related Questions
- Can non-contextual word embeddings capture nuances of word meanings in tasks like sentiment analysis?
- How do non-contextual word embeddings perform in tasks that require subtle semantic differences, such as detecting irony or sarcasm?
- Do non-contextual word embeddings struggle with tasks that involve subtle differences in word meanings, such as distinguishing between synonyms?
- In what scenarios do non-contextual word embeddings tend to perform poorly in tasks that require subtle semantic differences?
- Can non-contextual word embeddings be fine-tuned to improve their performance in tasks that require subtle semantic differences?
- How do the results of non-contextual word embeddings compare to contextual word embeddings in tasks that require subtle semantic differences?
- What are some common pitfalls or limitations of using non-contextual word embeddings in tasks that require subtle semantic differences?
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