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Benno Stein

17 accepted papers

2025

Argumentation and Domain Discourse in Scholarly Articles on the Theory of International Relations

Magdalena Wolska, Sassan Gholiagha, Mitja Sienknecht, Dora Kiesel, Irene Lopez Garcia, Patrick Riehmann +5
COLING 2025main

We present the first dataset, an annotation scheme, discourse analysis, and baseline experiments on argumentation and domain content types in scholarly articles on political science, specifically on the theory of International Relations (IR). The dataset comprises over 1 600 sentences stemming from…

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2025

The Two Paradigms of LLM Detection: Authorship Attribution vs. Authorship Verification

Janek Bevendorff, Matti Wiegmann, Emmelie Richter, Martin Potthast, Benno Stein
ACL 2025finding

The detection of texts generated by LLMs has quickly become an important research problem. Many supervised and zero-shot detectors have already been proposed, yet their effectiveness and precision remain disputed. Current research therefore focuses on making detectors robust against domain shifts an…

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2024

Improving Argument Effectiveness Across Ideologies using Instruction-tuned Large Language Models

Roxanne El Baff, Khalid Al Khatib, Milad Alshomary, Kai Konen, Benno Stein, Henning Wachsmuth
EMNLP 2024finding

Different political ideologies (e.g., liberal and conservative Americans) hold different worldviews, which leads to opposing stances on different issues (e.g., gun control) and, thereby, fostering societal polarization. Arguments are a means of bringing the perspectives of people with different ideo…

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2024

Reference-guided Style-Consistent Content Transfer

Wei-Fan Chen, Milad Alshomary, Maja Stahl, Khalid Al Khatib, Benno Stein, Henning Wachsmuth
COLING 2024main

In this paper, we introduce the task of style-consistent content transfer, which concerns modifying a text’s content based on a provided reference statement while preserving its original style. We approach the task by employing multi-task learning to ensure that the modified text meets three importa…

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2024

The Information Retrieval Experiment Platform (Extended Abstract)

Maik Fröbe, Jan Heinrich Reimer, Sean MacAvaney, Niklas Deckers, Simon Reich, Janek Bevendorff +3
IJCAI 2024poster

We have built TIREx, the information retrieval experiment platform, to promote standardized, reproducible, scalable, and blinded retrieval experiments. Standardization is achieved through integration with PyTerrier's interfaces and compatibility with ir_datasets and ir_measures. Reproducibility and…

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2024

The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments

Nailia Mirzakhmedova, Johannes Kiesel, Milad Alshomary, Maximilian Heinrich, Nicolas Handke, Xiaoni Cai +8
COLING 2024main

While human values play a crucial role in making arguments persuasive, we currently lack the necessary extensive datasets to develop methods for analyzing the values underlying these arguments on a large scale. To address this gap, we present the Touché23-ValueEval dataset, an expansion of the Webis…

Cited by 39Source ↗PDF ↗code ↗Scholar ↗
2023

Shared Tasks as Tutorials: A Methodical Approach

Theresa Elstner, Frank Loebe, Yamen Ajjour, Christopher Akiki, Alexander Bondarenko, Maik Fröbe +11
AAAI 2023technical

In this paper, we discuss the benefits and challenges of shared tasks as a teaching method. A shared task is a scientific event and a friendly competition to solve a research problem, the task. In terms of linking research and teaching, shared-task-based tutorials fulfill several faculty desires: th…

Cited by 8Source ↗PDF ↗Scholar ↗
2023

Trigger Warning Assignment as a Multi-Label Document Classification Problem

Matti Wiegmann, Magdalena Wolska, Christopher Schröder, Ole Borchardt, Benno Stein, Martin Potthast
ACL 2023long

A trigger warning is used to warn people about potentially disturbing content. We introduce trigger warning assignment as a multi-label classification task, create the Webis Trigger Warning Corpus 2022, and with it the first dataset of 1 million fanfiction works from Archive of our Own with up to 36…

Cited by 20Source ↗PDF ↗code ↗Scholar ↗
2023

Unveiling the Power of Argument Arrangement in Online Persuasive Discussions

Nailia Mirzakhmedova, Johannes Kiesel, Khalid Al Khatib, Benno Stein
EMNLP 2023long findings

Previous research on argumentation in online discussions has largely focused on examining individual comments and neglected the interactive nature of discussions. In line with previous work, we represent individual comments as sequences of semantic argumentative unit types. However, because it is in…

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2022

Analyzing Persuasion Strategies of Debaters on Social Media

Matti Wiegmann, Khalid Al Khatib, Vishal Khanna, Benno Stein
COLING 2022main

Existing studies on the analysis of persuasion in online discussions focus on investigating the effectiveness of comments in discussions and ignore the analysis of the effectiveness of debaters over multiple discussions. In this paper, we propose to quantify debaters effectiveness in the online disc…

Cited by 8Source ↗PDF ↗Scholar ↗
2022

CausalQA: A Benchmark for Causal Question Answering

Alexander Bondarenko, Magdalena Wolska, Stefan Heindorf, Lukas Blübaum, Axel-Cyrille Ngonga Ngomo, Benno Stein +3
COLING 2022main

At least 5% of questions submitted to search engines ask about cause-effect relationships in some way. To support the development of tailored approaches that can answer such questions, we construct Webis-CausalQA-22, a benchmark corpus of 1.1 million causal questions with answers. We distinguish dif…

Cited by 22Source ↗PDF ↗code ↗Scholar ↗
2022

Identifying the Human Values behind Arguments

Johannes Kiesel, Milad Alshomary, Nicolas Handke, Xiaoni Cai, Henning Wachsmuth, Benno Stein
ACL 2022long

This paper studies the (often implicit) human values behind natural language arguments, such as to have freedom of thought or to be broadminded. Values are commonly accepted answers to why some option is desirable in the ethical sense and are thus essential both in real-world argumentation and theor…

Cited by 96Source ↗PDF ↗code ↗Scholar ↗
2022

Mining Health-related Cause-Effect Statements with High Precision at Large Scale

Ferdinand Schlatt, Dieter Bettin, Matthias Hagen, Benno Stein, Martin Potthast
COLING 2022main

An efficient assessment of the health relatedness of text passages is important to mine the web at scale to conduct health sociological analyses or to develop a health search engine. We propose a new efficient and effective termhood score for predicting the health relatedness of phrases and sentence…

Cited by 3Source ↗PDF ↗code ↗Scholar ↗
2021

Controlled Neural Sentence-Level Reframing of News Articles

Wei-Fan Chen, Khalid Al Khatib, Benno Stein, Henning Wachsmuth
EMNLP 2021finding

Framing a news article means to portray the reported event from a specific perspective, e.g., from an economic or a health perspective. Reframing means to change this perspective. Depending on the audience or the submessage, reframing can become necessary to achieve the desired effect on the readers…

Cited by 16Source ↗PDF ↗code ↗Scholar ↗
2021

Employing Argumentation Knowledge Graphs for Neural Argument Generation

Khalid Al Khatib, Lukas Trautner, Henning Wachsmuth, Yufang Hou, Benno Stein
ACL 2021long

Generating high-quality arguments, while being challenging, may benefit a wide range of downstream applications, such as writing assistants and argument search engines. Motivated by the effectiveness of utilizing knowledge graphs for supporting general text generation tasks, this paper investigates…

Cited by 32Source ↗PDF ↗code ↗Scholar ↗
2020

News Editorials: Towards Summarizing Long Argumentative Texts

Shahbaz Syed, Roxanne El Baff, Johannes Kiesel, Khalid Al Khatib, Benno Stein, Martin Potthast
COLING 2020main

The automatic summarization of argumentative texts has hardly been explored. This paper takes a further step in this direction, targeting news editorials, i.e., opinionated articles with a well-defined argumentation structure. With Webis-EditorialSum-2020, we present a corpus of 1330 carefully curat…

Cited by 19Source ↗PDF ↗Scholar ↗