The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments

1 code implementation • ACL 2022 • Milad Alshomary, Roxanne El Baff, Timon Gurcke, Henning Wachsmuth

An audience's prior beliefs and morals are strong indicators of how likely they will be affected by a given argument.

Assessing the Sufficiency of Arguments through Conclusion Generation

1 code implementation • EMNLP (ArgMining) 2021 • Timon Gurcke, Milad Alshomary, Henning Wachsmuth

An argument whose premises make its conclusion rationally worthy to be drawn is called sufficient in argument quality research.

text-classification Text Classification

Key Point Analysis via Contrastive Learning and Extractive Argument Summarization

1 code implementation • EMNLP (ArgMining) 2021 • Milad Alshomary, Timon Gurcke, Shahbaz Syed, Philipp Heinrich, Maximilian Spliethöver, Philipp Cimiano, Martin Potthast, Henning Wachsmuth

Key point analysis is the task of extracting a set of concise and high-level statements from a given collection of arguments, representing the gist of these arguments.

Argument Mining Contrastive Learning +1

Belief-based Generation of Argumentative Claims

1 code implementation • EACL 2021 • Milad Alshomary, Wei-Fan Chen, Timon Gurcke, Henning Wachsmuth

In this work, we aim to bridge this gap by studying the task of belief-based claim generation: Given a controversial topic and a set of beliefs, generate an argumentative claim tailored to the beliefs.

Informativeness Text Generation