perceiver-latent-array-decouples-compute-from-input-length
IN premise — summaries/2026/08/24/wiki-Transformer_deep_learning_architecture-chunk-6-chunk-2.md
Created 2026-08-24T17:11:26+00:00
Perceiver and Perceiver IO use a small set of learned latent arrays to cross-attend to arbitrary-length inputs and then iteratively refine, decoupling computational cost from input sequence length.
Summary
Instead of letting every element in the input interact with every other element, which gets explosively expensive as inputs grow, the system compresses attention to a small fixed set of learned queries that "read" the input of any size and then iteratively refine the result. The practical upshot is that processing cost stays roughly constant no matter how long the input is, so the system can handle very long sequences like high-resolution images or extended audio without a proportional jump in compute.