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New 'Schema' Harness Boosts ARC-AGI-3 Scores to 99% with Claude Opus 4.8

A new AI harness named "Schema" has been developed, which significantly improves performance on the ARC-AGI-3 benchmark. When used with Anthropic's Claude Opus 4.8 and Meta's Fable 5, Schema achieves a 99% score on the benchmark. A separate test using OpenAI's GPT-5.6 Sol model yielded a 95.35% score. Schema's improvements stem from its novel approach to processing observations, testing predictions, and executing plans, rather than altering the underlying model weights. AI

IMPACT This development could lead to more effective AI agents capable of complex reasoning and problem-solving.

RANK_REASON The item describes a new harness that achieves a high score on a benchmark, which is a research milestone. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New 'Schema' Harness Boosts ARC-AGI-3 Scores to 99% with Claude Opus 4.8

COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/we_are_mammals ·

    New Fable5/Opus4.8 harness called "Schema" claims 99% on ARC-3 [R]

    <!-- SC_OFF --><div class="md"><blockquote> <p>Schema, the harness we introduce today, reaches 99% on the ARC‑AGI‑3 Public set using Claude Opus 4.8 and Fable 5, and 95.35% using GPT‑5.6 Sol. It does not change the underlying model weights. Instead, it changes the process around …