SNB researchers develop ‘more precise’ LLM-based risk predictor
New model allows for “more nuanced understanding” of types of uncertainty, researchers say
Researchers from the Swiss National Bank (SNB) have developed new tools that could “revolutionise the analysis and quantification of uncertainty”.
In a paper published on October 23, economists Francesco Audrino, Jessica Gentner and Simon Stalder show that their model outperforms previous benchmark tools that measure uncertainty, such as “bag-of-words” (BoW) models.
The team used “state-of-the-art” large language models (LLMs) such as GPT-4 and LLaMa-2-7B-Beta to analyse and classify a set of
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