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TopicsWeak-to-Strong Generalization AI Research Automation Anthropic

In the reported weak-to-strong supervision experiment, Claude-based agents recovered more of the performance gap than human researchers.

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Two human researchers, over about a week, recovered roughly 23% of that gap; the agents recovered 97% over 800 cumulative hours and used roughly $18,000 in compute.

When AI builds itself original reportinterest recorded · Anthropicextraction 0.80

April 2026 automated weak-to-strong supervision research demonstration; humans chose the problem and scoring rubric, and the result did not transfer cleanly to production-scale models.

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Created by extractor · Nov 13, 2026. Every judgment on this page is accompanied by a reasoning trace.