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Found 2 papers, 1 papers with code
Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints
Learning to defer (L2D) aims to improve human-AI collaboration systems by learning how to defer decisions to humans when they are more likely to be correct than an ML classifier.
FiFAR: A Fraud Detection Dataset for Learning to Defer
Financial fraud detection is a high-stakes setting where algorithms and human experts often work in tandem; however, there are no publicly available datasets for L2D concerning this important application of human-AI teaming.
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