The upper-tail accumulation scale derived from the gap-counting function N_n sets the critical inverse temperature for softmax attention concentration, unifying prior conflicting laws as special cases of different N_n.
Attention is all you need
2 Pith papers cite this work. Polarity classification is still indexing.
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Ister is a linear-complexity transformer using Dot-attention and inverted seasonal-trend decomposition for multivariate time series forecasting that reports state-of-the-art benchmark performance.
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A Unified Framework for Critical Scaling of Inverse Temperature in Self-Attention
The upper-tail accumulation scale derived from the gap-counting function N_n sets the critical inverse temperature for softmax attention concentration, unifying prior conflicting laws as special cases of different N_n.
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Ister: Linear Transformer for Efficient Multivariate Time Series Forecasting
Ister is a linear-complexity transformer using Dot-attention and inverted seasonal-trend decomposition for multivariate time series forecasting that reports state-of-the-art benchmark performance.