Reproduce “Uncertainty Quantification for Financial Foundation Models: A Survey” on OpenResearch
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About this paper
Zijie Zhao, Mingjun Sun, Shenbo Xu
The authors survey financial uncertainty in AI, organizing six sources across evidence, model inference, outcomes, and actions. They classify representations into five method families and map finance-specific studies screened for operational uncertainty measures and quantitative evaluation. The review covers 24 papers and 26 assignments; only two span multiple task domains, and none links evidence or reasoning reliability to constrained action.
Summary by alphaXiv.
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