2021

From Argument Search to Argumentive Dialogue: A Topic-Independent Approach to Argument Acquisition for Dialogue Systems (Best Paper Award at SIGDIAL 2021!)


Niklas Rach, Carolin Schindler, Isabel Feustel, Johannes Daxenberger, Wolfgang Minker, Stefan Ultes

Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue.

From Argument Search to Argumentative Dialogue: A Topic-independent Approach to Argument Acquisition for Dialogue Systems

Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks


Nandan Thakur, Nils Reimers, Johannes Daxenberger, Iryna Gurevych

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks

Stance Detection Benchmark: How Robust Is Your Stance Detection?


Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych

KI - Künstliche Intelligenz.

Stance Detection Benchmark: How Robust Is Your Stance Detection?

Aspect-Controlled Neural Argument Generation


Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

Aspect-Controlled Neural Argument Generation

2020

Arguments as Social Good: Good Arguments in Times of Crisis


Johannes Daxenberger, Iryna Gurevych

AI for Social Good - AAAI Fall Symposium 2020.

Arguments as Social Good: Good Arguments in Times of Crisis

ArgumenText: Argument Classification and Clustering in a Generalized Search Scenario


Johannes Daxenberger, Benjamin Schiller, Chris Stahlhut, Erik Kaiser, Iryna Gurevych

Datenbank-Spektrum 20:115–121 (2020).

ArgumenText: Argument Classification and Clustering in a Generalized Search Scenario

Aspect-Controlled Neural Argument Generation


Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych

arxiv preprint: arXiv:2005.00084

Aspect-Controlled Neural Argument Generation. Arxiv Preprint.

Stance Detection Benchmark: How Robust Is Your Stance Detection?


Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych

arxiv preprint: arXiv:2001.01565

Stance Detection Benchmark: How Robust Is Your Stance Detection? Arxiv Preprint.

Fine-Grained Argument Unit Recognition and Classification


Dietrich Trautmann, Johannes Daxenberger, Christian Stab, Hinrich Schütze, Iryna Gurevych

The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, USA

Fine-Grained Argument Unit Recognition and Classification. In: The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, USA.

Evaluation of Argument Search Approaches in the Context of Argumentative Dialogue Systems


Niklas Rach, Yuki Matsuda, Johannes Daxenberger, Stefan Ultes, Keiichi Yaumoto, Wolfgang Minker

Evaluation of Argument Search Approaches in the Context of Argumentative Dialogue Systems. In: Proceedings of Language Resources and Evaluation Conference (LREC 2020), Marseille, France.

2019

Classification and Clustering of Arguments with Contextualized Word Embeddings


Nils Reimers, Benjamin Schiller, Tilman Beck, Johannes Daxenberger, Christian Stab, Iryna Gurevych

Association for Computational Linguistics, Florence, Italy

Classification and Clustering of Arguments with Contextualized Word Embeddings. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.

Robust Argument Unit Recognition and Classification


Dietrich Trautmann, Johannes Daxenberger, Christian Stab, Hinrich Schütze, Iryna Gurevych

arxiv preprint: arXiv:1904.09688, 10 pages

Robust Argument Unit Recognition and Classification. Arxiv Preprint.

2018

Cross-topic Argument Mining from Heterogeneous Sources


Christian Stab, Tristan Miller, Benjamin Schiller, Pranav Rai, Iryna Gurevych

Association for Computational Linguistics, Brussels, Belgium, pages 3664–3674

Cross-topic Argument Mining from Heterogeneous Sources. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP).

PD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation Projection


Steffen Eger, Andreas Rücklé, Iryna Gurevych

Association for Computational Linguistics, Brussels, Belgium, pages 131–143

PD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation Projection. In 5th Workshop on Argument Mining at the 2018 Conference on Empirical Methods in Natural Language Processing.

Cross-Lingual Argumentative Relation Identification: from English to Portuguese


Gil Rocha, Christian Stab, Henrique Lopes Cardoso, Iryna Gurevych

Association for Computational Linguistics, Brussels, Belgium, pages 144–154

Cross-Lingual Argumentative Relation Identification: from English to Portuguese. In 5th Workshop on Argument Mining at the 2018 Conference on Empirical Methods in Natural Language Processing.

Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!


Steffen Eger, Johannes Daxenberger, Christian Stab, Iryna Gurevych

Association for Computational Linguistics, Santa Fe, NM, USA, pages 831-844

Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need! In Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018).

ArgumenText: Searching for Arguments in Heterogeneous Sources


Christian Stab, Johannes Daxenberger, Chris Stahlhut, Tristan Miller, Benjamin Schiller, Christopher Tauchmann, Steffen Eger, Iryna Gurevych

Association for Computational Linguistics, New Orleans, LA, USA, pages 21–25

ArgumenText: Searching for Arguments in Heterogeneous Sources. In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Demo).

Multi-Task Learning for Argumentation Mining in Low-Resource Settings


Claudia Schulz, Steffen Eger, Johannes Daxenberger, Tobias Kahse, Iryna Gurevych

Association for Computational Linguistics, New Orleans, LA, USA, pages 35–41

Multi-Task Learning for Argumentation Mining in Low-Resource Settings. In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks


Christian Stab, Tristan Miller, Iryna Gurevych. 2018.

arxiv preprint: arXiv:1802.05758

Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks. Arxiv Preprint.

2017

What is the essence of a claim?


Johannes Daxenberger, Steffen Eger, Ivan Habernal, Christian Stab, and Iryna Gurevych. 2017.

Association for Computational Linguistics, Copenhagen, Denmark, pages 2045–2056.

What is the essence of a claim? Cross-domain claim identification. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing.

Neural end-to-end learning for computational argumentation mining.


Steffen Eger, Johannes Daxenberger, and Iryna Gurevych. 2017.

Association for Computational Linguistics, Vancouver, Canada, pages 11–22.

Neural end-to-end learning for computational argumentation mining. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

Parsing argumentation structures in persuasive essays.


Christian Stab and Iryna Gurevych. 2017.

Computational Linguistics 43(3):619–659.

Parsing argumentation structures in persuasive essays.

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