[2603.22858] The Coordinate System Problem in Persistent Structural Memory for Neural Architectures

Computer Science > Machine Learning arXiv:2603.22858 (cs) [Submitted on 24 Mar 2026] Title:The Coordinate System Problem in Persistent Structural Memory for Neural Architectures Authors:Abhinaba Basu View a PDF of the paper titled The Coordinate System Problem in Persistent Structural Memory for Neural Architectures, by Abhinaba Basu View PDF HTML (experimental) Abstract:We introduce the Dual-View Pheromone Pathway Network (DPPN), an architecture that routes sparse attention through a persistent pheromone field over latent slot transitions, and use it to discover two independent requirements for persistent structural memory in neural networks. Through five progressively refined experiments using up to 10 seeds per condition across 5 model variants and 4 transfer targets, we identify a core principle: persistent memory requires a stable coordinate system, and any coordinate system learned jointly with the model is inherently unstable. We characterize three obstacles -- pheromone saturation, surface-structure entanglement, and coordinate incompatibility -- and show that neither contrastive updates, multi-source distillation, Hungarian alignment, nor semantic decomposition resolves the instability when embeddings are learned from scratch. Fixed random Fourier features provide extrinsic coordinates that are stable, structure-blind, and informative, but coordinate stability alone is insufficient: routing-bias pheromone does not transfer (10 seeds, p>0.05). DPPN outperforms tran...