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Preprint Aug 2026

Infrared Universality of Collective Dynamics across Transformer and State-Space Architectures

Whether distinct neural architectures develop common collective dynamics remains an open question. Recent analysis of Transformer language models revealed a nearly flat, weakly infrared-enhanced time-scale density of states (TDOS) associated with near-marginal long-memory dynamics. Here we test whether a closely relate...

B. Chae · 0 citations
#artificial intelligence Preprint Sep 2026

Beyond Episodic AI: Cognitive Field Networks for Biologically Inspired Persistent Cognition

The CFN provides a controlled computational platform for studying persistent, history-dependent cognitive dynamics without a separately prescribed memory system and finds that learning organizes persistent, content-dependent recurrent dynamics whose timescale increases systematically with the trained recurrent horizon.

B. Chae · 0 citations

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