1 code implementation • EMNLP (ArgMining) 2021 • Jan Heinrich Reimer, Thi Kim Hanh Luu, Max Henze, Yamen Ajjour
We contribute to the ArgMining 2021 shared task on Quantitative Summarization and Key Point Analysis with two approaches for argument key point matching.
no code implementations • 23 Jan 2023 • Yamen Ajjour, Johannes Kiesel, Benno Stein, Martin Potthast
Many computational argumentation tasks, like stance classification, are topic-dependent: the effectiveness of approaches to these tasks significantly depends on whether the approaches were trained on arguments from the same topics as those they are tested on.
no code implementations • IJCNLP 2019 • Yamen Ajjour, Milad Alshomary, Henning Wachsmuth, Benno Stein
In general, we call a set of arguments that focus on the same aspect a frame.
no code implementations • EMNLP 2018 • Yamen Ajjour, Henning Wachsmuth, Dora Kiesel, Patrick Riehmann, Fan Fan, Giuliano Castiglia, Rosemary Adejoh, Bernd Fr{\"o}hlich, Benno Stein
In times of fake news and alternative facts, pro and con arguments on controversial topics are of increasing importance.
1 code implementation • WS 2017 • Yamen Ajjour, Wei-Fan Chen, Johannes Kiesel, Henning Wachsmuth, Benno Stein
The segmentation of an argumentative text into argument units and their non-argumentative counterparts is the first step in identifying the argumentative structure of the text.
no code implementations • WS 2017 • Henning Wachsmuth, Martin Potthast, Khalid Al-Khatib, Yamen Ajjour, Jana Puschmann, Jiani Qu, Jonas Dorsch, Viorel Morari, Janek Bevendorff, Benno Stein
Computational argumentation is expected to play a critical role in the future of web search.
no code implementations • EACL 2017 • Henning Wachsmuth, Benno Stein, Yamen Ajjour
Future search engines are expected to deliver pro and con arguments in response to queries on controversial topics.