Generating Informative Conclusions for Argumentative Texts

Generating Informative Conclusions for Argumentative Texts

2 June 2021

Khalid Al Khatib

Milad Alshomary

Henning Wachsmuth

Martin Potthast

Papers citing "Generating Informative Conclusions for Argumentative Texts"

8 / 8 papers shown

Title
Dynamic Knowledge Integration for Evidence-Driven Counter-Argument Generation with Large Language Models Anar Yeginbergen Maite Oronoz Rodrigo Agerri 60 0 0 07 Mar 2025
ArgU: A Controllable Factual Argument Generator Sougata Saha Rohini Srihari 30 13 0 09 May 2023
Summary Workbench: Unifying Application and Evaluation of Text Summarization Models S. Syed Dominik Schwabe Martin Potthast 22 0 0 18 Oct 2022
The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments Milad Alshomary Roxanne El Baff Timon Ziegenbein Henning Wachsmuth 19 33 0 28 Mar 2022
Assessing the Sufficiency of Arguments through Conclusion Generation Timon Ziegenbein Milad Alshomary Henning Wachsmuth ELM 19 25 0 26 Oct 2021
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models Gregor Betz Kyle Richardson 22 8 0 04 Oct 2021
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization Milad Alshomary Timon Ziegenbein S. Syed Philipp Heinisch Maximilian Spliethover Philipp Cimiano Martin Potthast Henning Wachsmuth 59 15 0 30 Sep 2021
Text Summarization with Pretrained Encoders Yang Liu Mirella Lapata MILM 261 1,436 0 22 Aug 2019