New method to measure LLM uncertainty through causal robustness
In brief
- New method quantifies LLM uncertainty via internal stability analysis.
- Causal robustness margin measures sensitivity to internal interventions.
- Uncertain responses show lower margins than correct ones.
Researchers introduce a novel approach to assess uncertainty in large language models (LLMs) by analyzing the stability of their internal mechanisms. This method, based on the causal robustness margin, helps distinguish uncertain from correct responses. Tests across multiple models and datasets confirm its effectiveness compared to traditional methods.
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