
Erratum : AI tool attribution was corrected in v12. SNN-Genesis v10.1 extends v10's discovery of stochastic resonance in LLM reasoning with two new experiments that explain WHY and HOW the effect works. Phase 58 (Cliff Anatomy): Dissects the σ=0.15→0.20 phase transition by measuring hidden-state diagnostics. Cosine similarity ≈ 0.50 is identified as the critical threshold — reasoning succeeds when the perturbed hidden-state direction is sufficiently preserved (cos ≥ 0.50) and collapses when noise overwhelms the original direction (cos < 0.46, SNR < 0.5). The transition is gradual, not discontinuous, with a therapeutic window of cos ∈ [0.50, 0.70]. Phase 59 (Smart Defibrillation): Tests conditional noise injection — firing σ=0.15 only after errors (like a cardiac AED). Result: defibrillation HURTS (4% vs 18% baseline, N=50). This establishes the Prophylactic Principle: stochastic resonance is preventive (vaccine), not curative (antibiotic). The noise must be present before reasoning enters a failure basin, not after. From v10 (retained): Orthogonal noise decomposition proving direction×magnitude interaction, classic bell curve (9% → 32% → 0%), large-N replication (N=100, p=8.4×10⁻⁵). 61 pages. All experiments conducted on RTX 5080 with Mistral-7B-Instruct-v0.3 (4-bit quantized). Code: https://github.com/hafufu-stack/snn-genesis
Spiking Neural Networks, Tower of Hanoi, Stochastic Resonance, Large Language Models, Liquid Neural Networks, Alignment Tax, AI Safety, Closed-form Continuous-time, Honest Null Result, Chat Template Effect, Deep-Thinking Ratio
Spiking Neural Networks, Tower of Hanoi, Stochastic Resonance, Large Language Models, Liquid Neural Networks, Alignment Tax, AI Safety, Closed-form Continuous-time, Honest Null Result, Chat Template Effect, Deep-Thinking Ratio
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