method
active
method:scaled-dot-product-attentionScaled Dot-Product Attention
Attention mechanism used to contextualize response representations with stimulus representations; chosen for interpretability and temporal preservation.
Neighborhood — ranked by edge-count
Thinkers (1)
thinker
- Ashish VaswaniintroducesLead author of 'Attention is all you need', introducing the transformer architecture
Methods (2)
method
- Time series of response representations contextualized by applying dot-product attention to the corresponding stimulus representations.
- Extension of ARR where attention is directed specifically to linguistic spans (complement syntax or mental state verbs) within the stimulus.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Justifies the methodological choice of attention over concatenation, mean pooling, residual connections, or joint embedding.
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- Interpretive process for transforming many-valued contexts into formal contexts via scale attributes.
- Assertion that low-tech process-based restoration approaches can be applied at watershed scales large enough to match the extent of degradation.
- Approach using extra compute at test time to double-check answers and improve reliability.
- Mechanisms by which smaller competent subunits bind into a higher-level Self with larger goals; key example via gap junction connections.
- The property that living structures contain centers at a beautiful range of sizes at well-marked levels with definite jumps, where each level helps the next; jumps should not be too great (ideally 2:1 to 4:1, less than 10:1)