544 citations · 617 across the 22 of their papers we have counts for
7 papers · 1 filter
Out of Spuriousity: Improving Robustness to Spurious Correlations without Group Annotations
Phuong Quynh Le, Jörg Schlötterer, Christin Seifert
Machine learning models are known to learn spurious correlations, i.e., features having strong relations with class labels but no causal relation. Relying on those correlations lea…
Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding
Ahmad Idrissi-Yaghir, Amin Dada, Henning Schäfer +17
Recent advances in natural language processing (NLP) can be largely attributed to the advent of pre-trained language models such as BERT and RoBERTa. While these models demonstrate…
Corpus Considerations for Annotator Modeling and Scaling
Olufunke O. Sarumi, Béla Neuendorf, Joan Plepi +3
Recent trends in natural language processing research and annotation tasks affirm a paradigm shift from the traditional reliance on a single ground truth to a focus on individual p…
CEval: A Benchmark for Evaluating Counterfactual Text Generation
Van Bach Nguyen, Jörg Schlötterer, Christin Seifert
Counterfactual text generation aims to minimally change a text, such that it is classified differently. Judging advancements in method development for counterfactual text generatio…
A Second Look on BASS -- Boosting Abstractive Summarization with Unified Semantic Graphs -- A Replication Study
Osman Alperen Koraş, Jörg Schlötterer, Christin Seifert
We present a detailed replication study of the BASS framework, an abstractive summarization system based on the notion of Unified Semantic Graphs. Our investigation includes challe…
Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges
Shreyasi Pathak, Jörg Schlötterer, Jeroen Veltman +3
Deep learning models have achieved high performance in medical applications, however, their adoption in clinical practice is hindered due to their black-box nature. Self-explainabl…
PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans
Lisa Anita De Santi, Jörg Schlötterer, Michael Scheschenja +4
Information from neuroimaging examinations is increasingly used to support diagnoses of dementia, e.g., Alzheimer's disease. While current clinical practice is mainly based on visu…