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20232026
most citedA Decision Theoretic Framework for Measuring AI Reliance

2 citations · 3 across the 17 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.HC2024

Unexploited Information Value in Human-AI Collaboration

Ziyang Guo, Yifan Wu, Jason Hartline +1

Humans and AIs are often paired on decision tasks with the expectation of achieving complementary performance -- where the combination of human and AI outperforms either one alone.…

cs.AI2024

ElicitationGPT: Text Elicitation Mechanisms via Language Models

Yifan Wu, Jason Hartline

Scoring rules evaluate probabilistic forecasts of an unknown state against the realized state and are a fundamental building block in the incentivized elicitation of information. T…

cs.GT2024

Subgame Optimal and Prior-Independent Online Algorithms

Jason Hartline, Aleck Johnsen, Anant Shah

This paper takes a game theoretic approach to the design and analysis of online algorithms and illustrates the approach on the finite-horizon ski-rental problem. This approach allo…

cs.GT2024

Fundamental Limits of Throughput and Availability: Applications to prophet inequalities & transaction fee mechanism design

Aadityan Ganesh, Jason Hartline, Atanu R Sinha +1

This paper studies the fundamental limits of availability and throughput for independent and heterogeneous demands of a limited resource. Availability is the probability that the d…

cs.AI2024★ 2 cited

A Decision Theoretic Framework for Measuring AI Reliance

Ziyang Guo, Yifan Wu, Jason Hartline +1

Humans frequently make decisions with the aid of artificially intelligent (AI) systems. A common pattern is for the AI to recommend an action to the human who retains control over…