Interaction Scaling: Grounding the Third Axis of Test-Time Compute

There are two standard ways to spend more compute at test time: let a model reason longer, or sample more attempts and keep one. Both share a hidden limit: they are internal. Every extra token comes from the same frozen weights and the same prompt, so neither can tell the model anything it does not already know. We study a third way, interaction: the model proposes an artifact, an external instrument observes how it actually behaves, and the model revises. Each cycle imports a real observation,

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ethics.ai (13 July 2026), “Interaction Scaling: Grounding the Third Axis of Test-Time Compute,” evidence record 6, https://ethics.ai/record/6 (originally published by arXiv).

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