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Related Questions
- Can BERT capture long-range dependencies in text through self-attention mechanisms?
- How do transformer-based models like BERT handle non-local dependencies in text compared to recurrent neural networks?
- What are the limitations of using BERT for tasks that require modeling non-local dependencies in text?
- Can we improve BERT's ability to capture non-local dependencies in text using techniques like hierarchical attention or graph neural networks?
- How do the self-attention mechanisms in transformer-based models like BERT compare to traditional recurrent neural network architectures in handling non-local dependencies?
- What role does the size of the context window play in BERT's ability to capture non-local dependencies in text?
- Can we use BERT to model complex non-local dependencies in text, such as those found in literary or poetic language?
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