The ARC Principle: Experimental Validation of Super-Linear Error Suppression Through Sequential Recursive Processing
1 min read ยท 206 wordsThe ARC Principle: Experimental Validation of Super-Linear Error Suppression Through Sequential Recursive Processing: a research paper from the ARC-Eden programme by Michael Darius Eastwood. The paper suite is registered at the Open Science Framework (DOI 10.17605/OSF.IO/6C5XB).
This paper presents experimental validation of the ARC Principle across multiple frontier AI models (Claude, DeepSeek, Gemini, Grok, Groq Qwen, GPT), confirming that error rates decrease according to a power law with recursive depth. The form of recursion determines the scaling regime: sequential re This companion post provides context. For the full text and figures, see the canonical paper page.
The paper is one of 23 in the ARC-Eden programme. Each paper is dated and evidence-anchored. The programme priority claims are traceable through the priority claims ledger.
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