Enhancing Causal Interpretability in Black-Box Models: Latest Research Insights

Explore cutting-edge methods to improve causal interpretability in black-box models. This article reviews algorithms and designs that leverage causal inference techniques, aiming to optimize performance using advanced approaches like GPT-4 fine-tuning in diverse applications such as medical diagnosis and financial risk control.