<ul><li>A new paper introduces a visualisation tool for determining the alignment of embedded data in deep learning models.</li><li>The method evaluates the distribution around planes defined by the network's privileged basis vectors, providing a holistic metric for interpreting activations.</li><li>Multiple variations of the technique are presented, with a hyperparameter to probe different angular scales and examples showing representations tend to align with privileged basis.</li><li>The paper establishes a causal link between activation functions, functional form symmetry breaking, and alignment with neuron basis, offering insights into representation alignment in neural networks.</li></ul>

The Spotlight Resonance Method: Resolving the Alignment of Embedded Activations

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