Unverified50% confidenceFactExact time
PrO-GPs treat predictive uncertainty directly as the primary inferential target, rather than first establishing a posterior over the parameter or function space.
1
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50%
Confidence
Long-term
Relevance
10/5/2026
First Seen
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Related Claims
UnverifiedThe prediction-centric perspective makes PrO-GPs more robust in the face of model misspecification.75% similarUnverifiedAdding schema validation at the tool-calling stage constrains the uncertainty of model outputs to a controllable range.65% similarUnverifiedConformal prediction is an uncertainty quantification framework that outputs prediction sets or prediction intervals with rigorous statistical coverage guarantees.63% similarVerifiedThe core mechanism of large model inference is probability-based Next Token Prediction, generating complete output word by word.63% similarUnverifiedThe paper proposes a novel optimization-based algorithm (codenamed METHODNAME) that learns optimal uncertainty profiles directly from LLM outputs, rather than estimating uncertainty through repeated sampling.63% similar
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