SELFDOUBT Uncertainty Quantification
SELFDOUBT is a new framework for uncertainty quantification in reasoning language models. It addresses the difficulty of deploying uncertainty estimation in practice, particularly for proprietary APIs.
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SELFDOUBT is a new framework for uncertainty quantification in reasoning language models. It addresses the difficulty of deploying uncertainty estimation in practice, particularly for proprietary APIs.
Researchers trained mRNA language models across 25 species for $165. This breakthrough has significant implications for bioinformatics and natural language processing.