What is attention mechanism in NLP?

Updated May 17, 2026

Short answer

Attention allows models to focus on relevant parts of input sequences.

Deep explanation

Attention computes weighted representations of input tokens based on their relevance to the current prediction step, improving long-range dependency handling.

Real-world example

Machine translation systems use attention to align words.

Common mistakes

Confusing attention with memory storage.

Follow-up questions

What is self-attention?
Why is attention better than RNNs?

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