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Related Questions
- How does self-attention mechanism allow for parallel processing of contextual information compared to RNNs?
- Can you explain the concept of 'attention' in self-attention and how it differs from the sequential processing of RNNs?
- What are the implications of self-attention's ability to weigh the importance of different contextual elements for natural language processing tasks?
- How does the parallelization of self-attention affect the computational efficiency of models compared to RNNs?
- Can you provide an example of a scenario where self-attention outperforms RNNs in handling contextual information?
- What are some potential limitations of self-attention in handling long-range dependencies in contextual information?
- How do self-attention mechanisms compare to other contextual representation learning techniques, such as graph attention networks?
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