24 citations · 24 across the 1 of their papers we have counts for
3 papers
cs.CL2020★ 24 cited
Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?
Peter Hase, Mohit Bansal
Algorithmic approaches to interpreting machine learning models have proliferated in recent years. We carry out human subject tests that are the first of their kind to isolate the e…
cs.CV2019
Interpretable Image Recognition with Hierarchical Prototypes
Peter Hase, Chaofan Chen, Oscar Li +1
Vision models are interpretable when they classify objects on the basis of features that a person can directly understand. Recently, methods relying on visual feature prototypes ha…
cs.AI2018
Shall I Compare Thee to a Machine-Written Sonnet? An Approach to Algorithmic Sonnet Generation
John Benhardt, Peter Hase, Liuyi Zhu +1
We provide an approach for generating beautiful poetry. Our sonnet-generation algorithm includes several novel elements that improve over the state of the art, leading to metrical,…