Connections Between Superposition and Adversarial Robustness

Ascertain the causal relationships between superposition in neural representations and adversarial robustness, determining whether and how superposed feature encoding influences vulnerability or resilience to adversarial perturbations.

Background

The review highlights a duality between interpretability and adversarial robustness, and superposition may modulate how models respond to perturbations by entangling features in overlapping directions.

Establishing this connection would provide theoretical and empirical guidance for designing models that balance representational efficiency with robustness and interpretability.