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ZENODO
Software . 2026
Data sources: ZENODO
ZENODO
Software . 2026
Data sources: Datacite
ZENODO
Software . 2026
Data sources: Datacite
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Routed Attention: Learning When to Think Hard

Authors: Bonsignore, Mike;

Routed Attention: Learning When to Think Hard

Abstract

Routed attention learns to dynamically select between O(N) causal convolution and O(N²) softmax attention on a per-position basis. A lightweight router network examines each position and routes it to the appropriate computational pathway. Using curriculum learning (first train with no attention penalty, then gradually increase it), routed attention achieves 100% accuracy with only 0.3% attention usage at distance 126 (99.7% compute savings), and 100% accuracy with 25% attention usage at distance 510 (75% compute savings).

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Keywords

attention mechanisms, mixture of experts, curriculum learning, sequence modeling, deep learning, efficient transformers, neural networks

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average