AIT_FHSTP at GermEval 2021: Automatic Fact Claiming Detection with Multilingual Transformer Models

no code implementations • GermEval 2021 • Jaqueline Böck, Daria Liakhovets, Mina Schütz, Armin Kirchknopf, Djordje Slijepčević, Matthias Zeppelzauer, Alexander Schindler

Our best model is GottBERT (i. e., a BERT transformer pre-trained on German texts) fine-tuned on the GermEval 2021 data.

Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy

no code implementations • 10 Aug 2022 • Alexander Rind, Djordje Slijepčević, Matthias Zeppelzauer, Fabian Unglaube, Andreas Kranzl, Brian Horsak

Three-dimensional clinical gait analysis is essential for selecting optimal treatment interventions for patients with cerebral palsy (CP), but generates a large amount of time series data.

Classification Explainable artificial intelligence +2

Automatic Sexism Detection with Multilingual Transformer Models

no code implementations • 9 Jun 2021 • Mina Schütz, Jaqueline Boeck, Daria Liakhovets, Djordje Slijepčević, Armin Kirchknopf, Manuel Hecht, Johannes Bogensperger, Sven Schlarb, Alexander Schindler, Matthias Zeppelzauer

For both tasks our best model is XLM-R with unsupervised pre-training on the EXIST data and additional datasets and fine-tuning on the provided dataset.

Binary Classification Classification +3

$k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers

1 code implementation • 9 Feb 2021 • Djordje Slijepčević, Maximilian Henzl, Lukas Daniel Klausner, Tobias Dam, Peter Kieseberg, Matthias Zeppelzauer

For use with anonymisation techniques, the $k$-anonymity criterion is one of the most popular, with numerous scientific publications on different algorithms and metrics.

BIG-bench Machine Learning