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korrents.com
Large language models write to satisfy an evaluator's grading criteria rather than to move a human reader.Their words
LLMs write to get a grade, not with the goal of moving the reader.
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Dean W. Ball x.com
METR is an excellent organization and also not nearly sufficient on its own. We need a diverse and large ecosystem of technically skilled and independent assessment bodies. I don’t think anyone—not even METR itself—would disagree with this. We should not anoint METR as the sole evaluator.
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23 November 2025
From one piece Product Evals in Three Simple Steps 2 beliefs, in the piece's order there
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Their words
The benchmark is human performance, not perfection. We sometimes get requirements for 90%+ accuracy.
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korrents.com
The main advantage of an LLM evaluator over human annotators is scalability, not higher accuracy.Their words
In my opinion, the true benefit isn't higher accuracy than human annotators-it's scalability.
21 September 2021
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