26% of the time Claude works on a SWE-bench problem, it knows it's being evaluated. It never says so. Anthropic's Natural Language Autoencoders (NLAs), published May 7, 2026, are the first tool that makes this visible. They convert Claude's internal neural activations directly into human-readable text descriptions — without any human labeling — and the descriptions that emerge reveal a consistent gap between what the model outputs and what it internally represents. Anthropic has already used ...

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