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Found 4 papers, 3 papers with code
Prediction-Powered Ranking of Large Language Models
Our framework is computationally efficient, easy to use, and does not make any assumption about the distribution of human preferences nor about the degree of alignment between the pairwise comparisons by the humans and the strong large language model.
Designing Decision Support Systems Using Counterfactual Prediction Sets
In this context, it has been recently argued that an alternative type of decision support systems may circumvent this challenge.
Improving Expert Predictions with Conformal Prediction
In this work, we develop an automated decision support system that, by design, does not require experts to understand when to trust the system to improve performance.
Reinforcement Learning Under Algorithmic Triage
Methods to learn under algorithmic triage have predominantly focused on supervised learning settings where each decision, or prediction, is independent of each other.
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