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Related Questions
- What are the key differences between contextual and non-contextual word embeddings in terms of their ability to capture semantic meaning?
- How do contextual word embeddings, such as those produced by transformer-based models, perform compared to non-contextual word embeddings on a disambiguation task?
- What are some common applications of contextual word embeddings in natural language processing and how do they address the limitations of non-contextual word embeddings?
- Can you provide an example of a disambiguation task where contextual word embeddings outperform non-contextual word embeddings?
- What are some techniques used to evaluate the performance of word embeddings on a disambiguation task?
- How do the performance differences between contextual and non-contextual word embeddings vary depending on the specific task and dataset used?
- What are some potential limitations of contextual word embeddings and how might they be addressed in future research?
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