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I'm interested to hear what these techniques are. Decreasing the generality will help, but I fail to see how that scopes the output. At best that mitigates the errors to an extent.

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Requiring the answers to automatically verifiable, or having answers be inputs to a reliable query system?

I’d rather use the reliable query system!

conformal prediction

Predicting a set of answers to some confidence interval would still result in hallucinated answers.

low probability answers get shot to a human and reviewed for model improvement.

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