Larval connectome rate operator shows gross behavior fixed by degree and weight statistics while input routing and dominant driving modes are fixed by exact wiring placement.
Optimal Degrees of Synaptic Connectivity
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×-shaped variable-width transformers outperform parameter-matched uniform baselines on language modeling loss with 22% fewer FLOPs and 15% smaller KV cache.
Four axioms (Causality, Minimality, Separability, Stability) are formalized for latent thought representations; audits of open LLMs on 23 tasks show none satisfy all four and representations add little beyond input embeddings.
KLR Hopfield networks reach P/N storage of ~16 for random patterns and ~20 for structured data, with limits set by dynamical instability against noise rather than geometric separability per Cover's theorem.
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Variable-Width Transformers
×-shaped variable-width transformers outperform parameter-matched uniform baselines on language modeling loss with 22% fewer FLOPs and 15% smaller KV cache.