AIBullisharXiv – CS AI · Apr 77/10
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Evolutionary Search for Automated Design of Uncertainty Quantification Methods
Researchers developed an LLM-powered evolutionary search method to automatically design uncertainty quantification systems for large language models, achieving up to 6.7% improvement in performance over manual designs. The study found that different AI models employ distinct evolutionary strategies, with some favoring complex linear estimators while others prefer simpler positional weighting approaches.
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