pith:UOOVP6KN
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Perceiver IO adds a flexible querying mechanism to the Perceiver so one architecture processes arbitrary structured inputs and produces outputs of any size or type while scaling linearly.
arxiv:2107.14795 v3 · 2021-07-30 · cs.LG · cs.CL · cs.CV · cs.SD · eess.AS
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Claims
The same architecture achieves strong results on tasks spanning natural language and visual understanding, multi-task and multi-modal reasoning, and StarCraft II. As highlights, Perceiver IO outperforms a Transformer-based BERT baseline on the GLUE language benchmark despite removing input tokenization and achieves state-of-the-art performance on Sintel optical flow estimation with no explicit mechanisms for multiscale correspondence.
That the added flexible querying mechanism can produce outputs of arbitrary sizes and semantics across domains without introducing hidden task-specific assumptions or requiring per-task architectural changes that undermine the generality claim.
Perceiver IO is a general architecture that processes arbitrary structured inputs and outputs with linear scaling and achieves strong results on GLUE, Sintel optical flow, multi-task reasoning, and StarCraft II without task-specific components.
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| First computed | 2026-05-17T23:38:50.367308Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Canonical record JSON
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