KoPE adds Kuramoto-based oscillatory phase states and synchronization to Vision Transformers, improving training, parameter, and data efficiency on structured vision tasks.
Analysis Experiments For analysis of attention concentration, we calculate the average Gini metric over all tokens for all heads of the attention of CLS token in the last layer
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Kuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency
KoPE adds Kuramoto-based oscillatory phase states and synchronization to Vision Transformers, improving training, parameter, and data efficiency on structured vision tasks.