ACCEPT: Perspectivized Argument Knowledge Graphs for Deliberation SupportA joint project between Prof. Anette Frank (ICL, Heidelberg University) and Prof. Philipp Cimiano (University of Bielefeld) in the 2nd phase of the DFG priority program RATIO: Robust Argumentation Machines
In ACCEPT we aim to create systems that are able to perform deep understanding of debated issues and analysis of
in order to find optimal and widely accepted solutions on debated issues.
The project aims to push the limits beyond prior work in computational argumentation, by designing systems that are able to
We aim to do this
- by creating argumentation systems that leverage knowledge resources to perform knowledge-based reasoning, using both sub-symbolic modeling using neural models and symbolic modeling using knowledge graphs, and
- by representing, contextualizing and enriching arguments in a multi-factorial argument knowledge graph that includes stakeholder perspectives and their interests, values and goals.
Based on the argument knowledge graph we will develop methods that analyze debated issues from multiple perspectives and learn to reason towards solutions, in order to support users with interpretable deliberation support.
New paper by Philipp Heinisch and members of ACCEPT
on Strategies for Framing Argumentative Conclusion Generation, to be presented at the 15th International Natural Language Generation Conference (INLG 2022).
Congratulations to Juri Opitz and all team members for earning the Best Paper Award in the Eighth ArgMining Workshop@EMNLP, for Explainable Unsupervised Argument Similarity Rating with Abstract Meaning Representation and Conclusion Generation !
Anette Frank will give a panel talk in the Eighth ArgMining Workshop @EMNLP.
Philipp Cimiano will give an invited talk at ArgKG @ AKBC 2021.
Anette Frank will give an invited talk at CLAR 2021, the 4th International Conference on Logic and Argumentation, Hangzhou, China.
Two papers accepted from members of ACCEPT
- Explainable Unsupervised Argument Similarity Rating with Abstract Meaning Representation and Conclusion Generation, by Juri Opitz, Philipp Heinisch, Philipp Wiesenbach, Philipp Cimiano and Anette Frank, in the ArgMining Workshop @EMNLP.
- Key Point Analysis via Contrastive Learning and Extractive Argument Summarization, by Milad Alshomary, Timon Gurcke, Shahbaz Syed, Philipp Heinisch, Maximilian Spliethöver, Philipp Cimiano, Martin Potthast, and Henning Wachsmuth in the ArgMining Workshop @EMNLP.
|Email (click to copy)|
|Semantic NLP for advanced & situated Natural Language Understanding|
|Email (click to copy)|
|Knowledge Representation and Natural Language Processing|
|Email (click to copy)||Heidelberg University|