Search Results for author: Khalid Al-Khatib

Found 17 papers, 4 papers with code

Differential Bias: On the Perceptibility of Stance Imbalance in Argumentation

no code implementations13 Oct 2022 Alonso Palomino, Martin Potthast, Khalid Al-Khatib, Benno Stein

We see the problem not in the complexity of interpreting language phenomena but in the diversity of sociocultural backgrounds of the readers, which cannot be handled uniformly: To decide whether a text has crossed the proverbial line between non-biased and biased is subjective.

Controlled Neural Sentence-Level Reframing of News Articles

no code implementations Findings (EMNLP) 2021 Wei-Fan Chen, Khalid Al-Khatib, Benno Stein, Henning Wachsmuth

Reframing is related to adapting style and sentiment, which can be tackled with neural text generation techniques.

Text Generation

Summary Explorer: Visualizing the State of the Art in Text Summarization

1 code implementation EMNLP (ACL) 2021 Shahbaz Syed, Tariq Yousef, Khalid Al-Khatib, Stefan Jänicke, Martin Potthast

This paper introduces Summary Explorer, a new tool to support the manual inspection of text summarization systems by compiling the outputs of 55~state-of-the-art single document summarization approaches on three benchmark datasets, and visually exploring them during a qualitative assessment.

Document Summarization

Generating Informative Conclusions for Argumentative Texts

1 code implementation Findings (ACL) 2021 Shahbaz Syed, Khalid Al-Khatib, Milad Alshomary, Henning Wachsmuth, Martin Potthast

Third, insights are provided into the suitability of our corpus for the task, the differences between the two generation paradigms, the trade-off between informativeness and conciseness, and the impact of encoding argumentative knowledge.


Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity

1 code implementation EMNLP (NLP+CSS) 2020 Wei-Fan Chen, Khalid Al-Khatib, Henning Wachsmuth, Benno Stein

Media organizations bear great reponsibility because of their considerable influence on shaping beliefs and positions of our society.

Detecting Media Bias in News Articles using Gaussian Bias Distributions

1 code implementation Findings of the Association for Computational Linguistics 2020 Wei-Fan Chen, Khalid Al-Khatib, Benno Stein, Henning Wachsmuth

In particular, we utilize the probability distributions of the frequency, positions, and sequential order of lexical and informational sentence-level bias in a Gaussian Mixture Model.

Bias Detection text-classification +1

Learning to Flip the Bias of News Headlines

no code implementations WS 2018 Wei-Fan Chen, Henning Wachsmuth, Khalid Al-Khatib, Benno Stein

This paper introduces the task of {``}flipping{''} the bias of news articles: Given an article with a political bias (left or right), generate an article with the same topic but opposite bias.

Text Generation

Modeling Deliberative Argumentation Strategies on Wikipedia

no code implementations ACL 2018 Khalid Al-Khatib, Henning Wachsmuth, Kevin Lang, Jakob Herpel, Matthias Hagen, Benno Stein

This paper studies how the argumentation strategies of participants in deliberative discussions can be supported computationally.

A News Editorial Corpus for Mining Argumentation Strategies

no code implementations COLING 2016 Khalid Al-Khatib, Henning Wachsmuth, Johannes Kiesel, Matthias Hagen, Benno Stein

Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude.

Argument Mining

Using Argument Mining to Assess the Argumentation Quality of Essays

no code implementations COLING 2016 Henning Wachsmuth, Khalid Al-Khatib, Benno Stein

In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays.

Argument Mining

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