seniorDeep Learning
What is Multi-Head Attention and why is it powerful?
Updated May 16, 2026
Short answer
Multi-Head Attention allows Transformers to learn multiple contextual relationships simultaneously by using several parallel attention mechanisms.
Deep explanation
Single attention mechanisms capture only one type of relationship at a time. Multi-Head Attention improves representational power by projecting inputs into multiple independent attention subspaces.
Process:
- Input embeddings are projected into:
- Queries (Q)
- Keys (K)
- Values (V)
- Multiple attention heads operate independently.
- Each head learns different contextual patterns.
- Outputs are concatenated and projected again.…
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