23 citations · 25 across the 4 of their papers we have counts for
4 papers
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models
Tuwe Löfström, Fatima Rabia Yapicioglu, Alessandra Stramiglio +2
This paper introduces Fast Calibrated Explanations, a method designed for generating rapid, uncertainty-aware explanations for machine learning models. By incorporating perturbatio…
When Explanations Compete: Policy-Aware Selection Under Uncertainty
Helena Löfström, Tuwe Löfström, Johan Hallberg Szabadvary
Uncertainty-aware explanation methods often produce several alternatives for the same prediction. Selecting among them requires a policy for balancing prediction confidence, uncert…
On the Definition of Appropriate Trust and the Tools that Come with it
Helena Löfström
Evaluating the efficiency of human-AI interactions is challenging, including subjective and objective quality aspects. With the focus on the human experience of the explanations, e…
A Meta Survey of Quality Evaluation Criteria in Explanation Methods
Helena Löfström, Karl Hammar, Ulf Johansson
Explanation methods and their evaluation have become a significant issue in explainable artificial intelligence (XAI) due to the recent surge of opaque AI models in decision suppor…