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Discusses the current trend in enterprise AI agent solutions favoring deterministic, auditable behavior over creative, dynamic LLM reasoning, questioning whether any creative agentic solutions exist.
This paper introduces the Gauge-Fixed Ordinal Network (GON), a temporal convolutional model that assigns consistent predictability scores across different dynamical systems by fixing the gauge freedom of ordinal scoring. The method transfers better than training from scratch on held-out systems, with zero-shot scores retaining ordinal structure at the stochastic boundary.