Implications of modularity across organizational levels

Characterize the implications of unit-level, orthogonal, and linear modularity for robustness, generalization, and learning dynamics across all three levels.

Background

The paper establishes a hierarchy in which functional modularity may emerge at the unit, orthogonal-subspace, or general-linear-subspace level. It explicitly states that the consequences of these different levels for network robustness, generalization, and learning dynamics have not yet been characterized.

References

Characterizing further implications for robustness, generalization, and learning dynamics across all three levels remains an open question.

— Neural networks are more modular than single neurons suggest  (2610.12842 - Saha et al., 9 Oct 2026) in Section 4, Discussion