806 citations · 888 across the 5 of their papers we have counts for
7 papers
From Obligation to Specification: A Survey on Validating EU AI Act Requirements in RE
T. Y. Emmy Lai, Sven Giesselbach, Matthias Koch +1
With the EU AI Act entering into force, organizations developing or operating AI systems face new obligations on transparency, risk management, and traceability. For Requirements E…
Foundation Models for Natural Language Processing -- Pre-trained Language Models Integrating Media
Gerhard Paaß, Sven Giesselbach
This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Na…
Supporting verification of news articles with automated search for semantically similar articles
Vishwani Gupta, Katharina Beckh, Sven Giesselbach +2
Fake information poses one of the major threats for society in the 21st century. Identifying misinformation has become a key challenge due to the amount of fake news that is publis…
Systematic Comparison of the Influence of Different Data Preprocessing Methods on the Performance of Gait Classifications Using Machine Learning
Johannes Burdack, Fabian Horst, Sven Giesselbach +3
Human movements are characterized by highly non-linear and multi-dimensional interactions within the motor system. Recently, an increasing emphasis on machine-learning applications…
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Laura von Rueden, Sebastian Mayer, Katharina Beckh +11
Despite its great success, machine learning can have its limits when dealing with insufficient training data. A potential solution is the additional integration of prior knowledge…
Corresponding Projections for Orphan Screening
Sven Giesselbach, Katrin Ullrich, Michael Kamp +2
We propose a novel transfer learning approach for orphan screening called corresponding projections. In orphan screening the learning task is to predict the binding affinities of c…
Making Efficient Use of a Domain Expert's Time in Relation Extraction
Linara Adilova, Sven Giesselbach, Stefan Rüping
Scarcity of labeled data is one of the most frequent problems faced in machine learning. This is particularly true in relation extraction in text mining, where large corpora of tex…