CryptoWorld News reports that Anthropic has released a research blog introducing training strategies to eliminate "agent misalignment" in Claude 4.5 and subsequent models. The research shows that relying solely on "correct behavior demonstrations" has limited effectiveness; what truly works is teaching the model "why it should do so," and reshaping values through synthetic documents. The team found that targeted learning from tens of thousands of records refusing to do bad things reduced the misalignment rate from 22% to just 15%.

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