Persistent Memory Through Triple-Loop Consolidation Under Stochastic Unit Turnover

arXiv:2603.27188 · cs.NE, q-bio.NC · Submitted 2026-03-28 · Read on arXiv

cs.NE, q-bio.NC

Submitted: 2026-03-28

Updated: 2026-09-24

Comments: 27 pages, 7 figures, 6 tables. v2 (revised after peer review): title changed; "non-gradient" replaced with "backpropagation-free" (an EMA update is gradient-equivalent, so the earlier classification was wrong); new Foster-Lyapunov drift bound (Prop. 5); bootstrap 95% CIs added; "phase diagram" corrected to "regime map"; run count corrected to 1,007

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Ablation — 22× in this paper · explained in 1 episode
• Deep Memory — 13× in this paper
• Uniform Activation — 10× in this paper
• Fidelity — 6× in this paper · explained in 2 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Failure Modes — 4× in this paper · explained in 3 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• Associative Memory — 3× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 3× in this paper · explained in 5 episodes
• Graceful Degradation — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• In International Conference on Learning Representations — 2× in this paper
• Liquid State Machine — 2× in this paper
• Mixture-of-Experts (MoE) — 2× in this paper · explained in 7 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Credit assignment — 1× in this paper · explained in 3 episodes
• Fisher Information — 1× in this paper · explained in 3 episodes
• International Conference on Machine Learning — 1× in this paper
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Titans: Learning to Memorize at Test Time
• Neural Turing Machines
• Progressive Neural Networks

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