AI Research
Rethinking Uncertainty Evaluation in Large Language Models
Moving beyond calibration to measure true probabilistic coherence in generative models.
Calibration is the primary criterion for evaluating LLM confidence, but it is insufficient: it admits trivially incoherent estimators, depends on the evaluation distribution, and does not test the extent to which the estimation can be interpreted as a consistent, underlying proba...
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ArXiv CS.AI
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ArXiv CS.AI
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Current methods for measuring LLM confidence rely on flawed calibration metrics that fail to capture the true probabilistic reasoning of models. By shifting the focus to structural coherence and faithfulness, this research exposes a critical reliability gap that standard alignment techniques currently cannot bridge.
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