AppliedAIPrep logoAppliedAI/Prep
← LLM & GenAI Fundamentals / 32
mediumGoogleOpenAICohere

What is cross-attention, and how does it differ from self-attention?

Cross-attention is how a model attends from one sequence into another, the mechanism behind encoder-decoder models and multimodal conditioning. The signal is knowing exactly where the queries vs keys/values come from.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Cross-attention is how a model attends from one sequence into another, the mechanism behind encoder-decoder models and multimodal conditioning. The signal is knowing exactly where the queries vs keys/values come from.

Unlock the other 750 answers · ₹2,000 / $25Your progress and mastery stay saved · 6 months · one payment · no auto-renew
UP NEXT ON YOUR JOURNEY
Next in this trackWhat do the feed-forward (MLP) layers in a transformer do, and why are they most of the parameters?Next in this trackWhy is an LLM's context window limited, and how do models extend it?Next in this trackHow do efficient attention variants (sparse, sliding-window, linear) make long context feasible?
DISCUSSION · 0

No comments yet — be the first to share your approach.