What is the main challenge addressed by the transformer architecture in NLP?
- Handling sequential data effectively
- Capturing long-range dependencies
- Image classification
- Speech recognition
The main challenge addressed by the transformer architecture is capturing long-range dependencies in sequential data. Transformers use self-attention mechanisms to understand the relationship between distant words in a sentence, making them effective for various NLP tasks like machine translation and text summarization.
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