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Conformal Prediction with Paraphrase-Aware Scoring for LLM Uncertainty Quantification
Uncertainty quantification (UQ) for large language models (LLMs) aims to provide reliable measures of predictive confidence, yet current methods are often unstable under meaning-preserving perturbations. Semantically equivalent paraphrases can induce substantial variability in predictive confidence,
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