most citedExtending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives

6 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20223 cited

CAIPI in Practice: Towards Explainable Interactive Medical Image Classification

Emanuel Slany, Yannik Ott, Stephan Scheele +2

Would you trust physicians if they cannot explain their decisions to you? Medical diagnostics using machine learning gained enormously in importance within the last decade. However…

cs.LG20223 cited

Explainable Online Lane Change Predictions on a Digital Twin with a Layer Normalized LSTM and Layer-wise Relevance Propagation

Christoph Wehner, Francis Powlesland, Bashar Altakrouri +1

Artificial Intelligence and Digital Twins play an integral role in driving innovation in the domain of intelligent driving. Long short-term memory (LSTM) is a leading driver in the…

cs.LG20225 cited

An Interactive Explanatory AI System for Industrial Quality Control

Dennis Müller, Michael März, Stephan Scheele +1

Machine learning based image classification algorithms, such as deep neural network approaches, will be increasingly employed in critical settings such as quality control in indust…

cs.CL20216 cited

Extending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives

Jonas-Dario Troles, Ute Schmid

Human gender bias is reflected in language and text production. Because state-of-the-art machine translation (MT) systems are trained on large corpora of text, mostly generated by…

cs.LG2021

Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach

Johannes Rabold, Michael Siebers, Ute Schmid

In recent research, human-understandable explanations of machine learning models have received a lot of attention. Often explanations are given in form of model simplifications or…