1 citations · 2 across the 4 of their papers we have counts for
8 papers
Defx at SemEval-2020 Task 6: Joint Extraction of Concepts and Relations for Definition Extraction
Marc Hübner, Christoph Alt, Robert Schwarzenberg +1
Definition Extraction systems are a valuable knowledge source for both humans and algorithms. In this paper we describe our submissions to the DeftEval shared task (SemEval-2020 Ta…
Pattern-Guided Integrated Gradients
Robert Schwarzenberg, Steffen Castle
Integrated Gradients (IG) and PatternAttribution (PA) are two established explainability methods for neural networks. Both methods are theoretically well-founded. However, they wer…
Evaluating German Transformer Language Models with Syntactic Agreement Tests
Karolina Zaczynska, Nils Feldhus, Robert Schwarzenberg +2
Pre-trained transformer language models (TLMs) have recently refashioned natural language processing (NLP): Most state-of-the-art NLP models now operate on top of TLMs to benefit f…
Abstractive Text Summarization based on Language Model Conditioning and Locality Modeling
Dmitrii Aksenov, Julián Moreno-Schneider, Peter Bourgonje +3
We explore to what extent knowledge about the pre-trained language model that is used is beneficial for the task of abstractive summarization. To this end, we experiment with condi…
Layerwise Relevance Visualization in Convolutional Text Graph Classifiers
Robert Schwarzenberg, Marc Hübner, David Harbecke +2
Representations in the hidden layers of Deep Neural Networks (DNN) are often hard to interpret since it is difficult to project them into an interpretable domain. Graph Convolution…
Neural Vector Conceptualization for Word Vector Space Interpretation
Robert Schwarzenberg, Lisa Raithel, David Harbecke
Distributed word vector spaces are considered hard to interpret which hinders the understanding of natural language processing (NLP) models. In this work, we introduce a new method…