{"id":5083,"date":"2024-01-12T15:10:57","date_gmt":"2024-01-12T15:10:57","guid":{"rendered":"https:\/\/www.summetix.com\/wissenschaftliche-veroeffentlichungen\/"},"modified":"2025-11-11T08:36:23","modified_gmt":"2025-11-11T08:36:23","slug":"wissenschaftliche-veroffentlichungen","status":"publish","type":"page","link":"https:\/\/www.summetix.com\/de\/wissenschaftliche-veroffentlichungen\/","title":{"rendered":"Wissenschaftliche Ver\u00f6ffentlichungen"},"content":{"rendered":"\t\t
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KUNDENINFORMATIONEN DER N\u00c4CHSTEN GENERATION<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Wissenschaftliche Ver\u00f6ffentlichungen<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Entdecken Sie verborgene Erkenntnisse in Kundenfeedback<\/strong> und komplexen qualitativen Daten. Summetix verwendet propriet\u00e4res Argument Mining<\/strong> und gro\u00dfe Sprachmodelle, um Muster und Trends <\/strong>zu entdecken, die Ihr Gesch\u00e4ft ver\u00e4ndern k\u00f6nnen.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tDemo anfordern<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\u00a02025<\/h2>\n

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Argument Summarization and its Evaluation in the Era of Large Language Models<\/h3>\n
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Moritz Altemeyer, Steffen Eger, Johannes Daxenberger, Tim Altendorf, Philipp Cimiano, Benjamin Schiller<\/h6>\n

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing<\/em><\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

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<\/div>\n

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<\/h3>\n

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2024<\/h2>\n

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Diversity Over Size: On the Effect of Sample and Topic Sizes for Topic-Dependent Argument Mining Datasets<\/h3>\n
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Benjamin Schiller, Johannes Daxenberger, Andreas Waldis, Iryna Gurevych<\/h6>\n

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing<\/em><\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

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<\/div>\n

<\/p>\n

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Exploring Argument Mining and Bayesian Networks for Assessing Topics for City Project Proposals<\/h3>\n
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Galia Weidl, Stefan Berres, Anders L Madsen, Johannes Daxenberger, Annegret Aulbach<\/h6>\n

International Conference on Probabilistic Graphical Models<\/p>\n

Exploring Argument Mining and Bayesian Networks for Assessing Topics for City Project Proposals<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

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2023<\/h2>\n

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Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting<\/h3>\n
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Nina Mouhammad, Johannes Daxenberger, Benjamin Schiller, Ivan Habernal<\/h6>\n

Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)<\/p>\n

Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

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<\/div>\n

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<\/h2>\n

<\/p>\n

2022<\/h2>\n

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Using Information-Seeking Argument Mining to Improve Service<\/h3>\n
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Bernd Skiera, Shunyao Yan, Johannes Daxenberger, Marcus Dombois, Iryna Gurevych<\/h6>\n

Journal of Service Research<\/p>\n

Using Information-Seeking Argument Mining to Improve Service<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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On the Effect of Sample and Topic Sizes for Argument Mining Datasets<\/h3>\n
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Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych<\/h6>\n

arXiv preprint arXiv:2205.11472<\/p>\n

On the Effect of Sample and Topic Sizes for Argument Mining Datasets<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/div>\n

<\/p>\n

<\/h2>\n

<\/p>\n

2021<\/h2>\n

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From Argument Search to Argumentive Dialogue: A Topic-Independent Approach to Argument Acquisition for Dialogue Systems (Best Paper Award at SIGDIAL 2021!)<\/h3>\n
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Niklas Rach, Carolin Schindler, Isabel Feustel, Johannes Daxenberger, Wolfgang Minker, Stefan Ultes<\/h6>\n

Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue.<\/p>\n

From Argument Search to Argumentative Dialogue: A Topic-independent Approach to Argument Acquisition for Dialogue Systems<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks<\/h3>\n
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Nandan Thakur, Nils Reimers, Johannes Daxenberger, Iryna Gurevych<\/h6>\n

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.<\/p>\n

Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Stance Detection Benchmark: How Robust Is Your Stance Detection?<\/h3>\n
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Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych<\/h6>\n

KI – K\u00fcnstliche Intelligenz.<\/p>\n

Stance Detection Benchmark: How Robust Is Your Stance Detection?<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Aspect-Controlled Neural Argument Generation<\/h3>\n
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Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych<\/h6>\n

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.<\/p>\n

Aspect-Controlled Neural Argument Generation<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

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<\/h2>\n

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2020<\/h2>\n

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Arguments as Social Good: Good Arguments in Times of Crisis<\/h3>\n
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Johannes Daxenberger, Iryna Gurevych<\/h6>\n

AI for Social Good – AAAI Fall Symposium 2020.<\/p>\n

Arguments as Social Good: Good Arguments in Times of Crisis<\/p>\n

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Link to presentation<\/a><\/h5>\n<\/div>\n

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ArgumenText: Argument Classification and Clustering in a Generalized Search Scenario<\/h3>\n
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Johannes Daxenberger, Benjamin Schiller, Chris Stahlhut, Erik Kaiser, Iryna Gurevych<\/h6>\n

Datenbank-Spektrum 20:115\u2013121 (2020).<\/p>\n

ArgumenText: Argument Classification and Clustering in a Generalized Search Scenario<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Aspect-Controlled Neural Argument Generation<\/h3>\n
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Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych<\/h6>\n

arxiv preprint: arXiv:2005.00084<\/p>\n

Aspect-Controlled Neural Argument Generation. Arxiv Preprint.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Stance Detection Benchmark: How Robust Is Your Stance Detection?<\/h3>\n
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Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych<\/h6>\n

arxiv preprint: arXiv:2001.01565<\/p>\n

Stance Detection Benchmark: How Robust Is Your Stance Detection? Arxiv Preprint.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Fine-Grained Argument Unit Recognition and Classification<\/h3>\n
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Dietrich Trautmann, Johannes Daxenberger, Christian Stab, Hinrich Sch\u00fctze, Iryna Gurevych<\/h6>\n

The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, USA<\/p>\n

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

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Evaluation of Argument Search Approaches in the Context of Argumentative Dialogue Systems<\/h3>\n
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Niklas Rach, Yuki Matsuda, Johannes Daxenberger, Stefan Ultes, Keiichi Yaumoto, Wolfgang Minker<\/h6>\n

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

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Read the paper<\/a><\/h5>\n<\/div>\n

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<\/h2>\n

<\/p>\n

2019<\/h2>\n

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Classification and Clustering of Arguments with Contextualized Word Embeddings<\/h3>\n
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Nils Reimers, Benjamin Schiller, Tilman Beck, Johannes Daxenberger, Christian Stab, Iryna Gurevych<\/h6>\n

Association for Computational Linguistics, Florence, Italy<\/p>\n

Classification and Clustering of Arguments with Contextualized Word Embeddings. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Robust Argument Unit Recognition and Classification<\/h3>\n
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Dietrich Trautmann, Johannes Daxenberger, Christian Stab, Hinrich Sch\u00fctze, Iryna Gurevych<\/h6>\n

arxiv preprint: arXiv:1904.09688, 10 pages<\/p>\n

Robust Argument Unit Recognition and Classification. Arxiv Preprint.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/div>\n

<\/p>\n

<\/h2>\n

<\/p>\n

2018<\/h2>\n

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Cross-topic Argument Mining from Heterogeneous Sources<\/h3>\n
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Christian Stab, Tristan Miller, Benjamin Schiller, Pranav Rai, Iryna Gurevych<\/h6>\n

Association for Computational Linguistics, Brussels, Belgium, pages 3664\u20133674<\/p>\n

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

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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PD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation Projection<\/h3>\n
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Steffen Eger, Andreas R\u00fcckl\u00e9, Iryna Gurevych<\/h6>\n

Association for Computational Linguistics, Brussels, Belgium, pages 131\u2013143<\/p>\n

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.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Cross-Lingual Argumentative Relation Identification: from English to Portuguese<\/h3>\n
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Gil Rocha, Christian Stab, Henrique Lopes Cardoso, Iryna Gurevych<\/h6>\n

Association for Computational Linguistics, Brussels, Belgium, pages 144\u2013154<\/p>\n

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.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!<\/h3>\n
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Steffen Eger, Johannes Daxenberger, Christian Stab, Iryna Gurevych<\/h6>\n

Association for Computational Linguistics, Santa Fe, NM, USA, pages 831-844<\/p>\n

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).<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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ArgumenText: Searching for Arguments in Heterogeneous Sources<\/h3>\n
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Christian Stab, Johannes Daxenberger, Chris Stahlhut, Tristan Miller, Benjamin Schiller, Christopher Tauchmann, Steffen Eger, Iryna Gurevych<\/h6>\n

Association for Computational Linguistics, New Orleans, LA, USA, pages 21\u201325<\/p>\n

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).<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Multi-Task Learning for Argumentation Mining in Low-Resource Settings<\/h3>\n
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Claudia Schulz, Steffen Eger, Johannes Daxenberger, Tobias Kahse, Iryna Gurevych<\/h6>\n

Association for Computational Linguistics, New Orleans, LA, USA, pages 35\u201341<\/p>\n

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.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks<\/h3>\n
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Christian Stab, Tristan Miller, Iryna Gurevych. 2018.<\/h6>\n

arxiv preprint: arXiv:1802.05758<\/p>\n

Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks. Arxiv Preprint.<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/div>\n

<\/p>\n

<\/h2>\n

<\/p>\n

2017<\/h2>\n

<\/p>\n

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What is the essence of a claim?<\/h3>\n
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Johannes Daxenberger, Steffen Eger, Ivan Habernal, Christian Stab, and Iryna Gurevych. 2017.<\/h6>\n

Association for Computational Linguistics, Copenhagen, Denmark, pages 2045\u20132056.<\/p>\n

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

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Neural end-to-end learning for computational argumentation mining.<\/h3>\n
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Steffen Eger, Johannes Daxenberger, and Iryna Gurevych. 2017.<\/h6>\n

Association for Computational Linguistics, Vancouver, Canada, pages 11\u201322.<\/p>\n

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).<\/p>\n

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Read the paper<\/a><\/h5>\n<\/div>\n

<\/div>\n

<\/p>\n

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Parsing argumentation structures in persuasive essays.<\/h3>\n
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Christian Stab and Iryna Gurevych. 2017.<\/h6>\n

Computational Linguistics 43(3):619\u2013659.<\/p>\n

Parsing argumentation structures in persuasive essays.<\/p>\n

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KUNDENINFORMATIONEN DER N\u00c4CHSTEN GENERATION Wissenschaftliche Ver\u00f6ffentlichungen Entdecken Sie verborgene Erkenntnisse in Kundenfeedback und komplexen qualitativen Daten. Summetix verwendet propriet\u00e4res Argument Mining und gro\u00dfe Sprachmodelle, um Muster und Trends zu entdecken, die Ihr Gesch\u00e4ft ver\u00e4ndern k\u00f6nnen. Demo anfordern \u00a02025 Argument Summarization and its Evaluation in the Era of Large Language Models Moritz Altemeyer, Steffen Eger, Johannes […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"content-type":"","footnotes":""},"class_list":["post-5083","page","type-page","status-publish","hentry"],"yoast_head":"\nWissenschaftliche Ver\u00f6ffentlichungen - summetix<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.summetix.com\/de\/wissenschaftliche-veroffentlichungen\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Wissenschaftliche Ver\u00f6ffentlichungen - summetix\" \/>\n<meta property=\"og:description\" content=\"KUNDENINFORMATIONEN DER N\u00c4CHSTEN GENERATION Wissenschaftliche Ver\u00f6ffentlichungen Entdecken Sie verborgene Erkenntnisse in Kundenfeedback und komplexen qualitativen Daten. Summetix verwendet propriet\u00e4res Argument Mining und gro\u00dfe Sprachmodelle, um Muster und Trends zu entdecken, die Ihr Gesch\u00e4ft ver\u00e4ndern k\u00f6nnen. Demo anfordern \u00a02025 Argument Summarization and its Evaluation in the Era of Large Language Models Moritz Altemeyer, Steffen Eger, Johannes […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.summetix.com\/de\/wissenschaftliche-veroffentlichungen\/\" \/>\n<meta property=\"og:site_name\" content=\"summetix\" \/>\n<meta property=\"article:modified_time\" content=\"2025-11-11T08:36:23+00:00\" \/>\n<meta name=\"twitter:label1\" content=\"Gesch\u00e4tzte Lesezeit\" \/>\n\t<meta name=\"twitter:data1\" content=\"5\u00a0Minuten\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.summetix.com\\\/de\\\/wissenschaftliche-veroffentlichungen\\\/\",\"url\":\"https:\\\/\\\/www.summetix.com\\\/de\\\/wissenschaftliche-veroffentlichungen\\\/\",\"name\":\"Wissenschaftliche Ver\u00f6ffentlichungen - summetix\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/summetix.com\\\/#website\"},\"datePublished\":\"2024-01-12T15:10:57+00:00\",\"dateModified\":\"2025-11-11T08:36:23+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.summetix.com\\\/de\\\/wissenschaftliche-veroffentlichungen\\\/#breadcrumb\"},\"inLanguage\":\"de\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.summetix.com\\\/de\\\/wissenschaftliche-veroffentlichungen\\\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.summetix.com\\\/de\\\/wissenschaftliche-veroffentlichungen\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.summetix.com\\\/de\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Wissenschaftliche Ver\u00f6ffentlichungen\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/summetix.com\\\/#website\",\"url\":\"https:\\\/\\\/summetix.com\\\/\",\"name\":\"summetix\",\"description\":\"Discover hidden insights in customer feedback and complex qualitative data. summetix uses proprietary Argument Mining and large language models to discover patterns and trends that help your business save and make money.\",\"publisher\":{\"@id\":\"https:\\\/\\\/summetix.com\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/summetix.com\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"de\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/summetix.com\\\/#organization\",\"name\":\"summetix\",\"url\":\"https:\\\/\\\/summetix.com\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"de\",\"@id\":\"https:\\\/\\\/summetix.com\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/www.summetix.com\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/summetix_smooth_text.png\",\"contentUrl\":\"https:\\\/\\\/www.summetix.com\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/summetix_smooth_text.png\",\"width\":2000,\"height\":304,\"caption\":\"summetix\"},\"image\":{\"@id\":\"https:\\\/\\\/summetix.com\\\/#\\\/schema\\\/logo\\\/image\\\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Wissenschaftliche Ver\u00f6ffentlichungen - summetix","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.summetix.com\/de\/wissenschaftliche-veroffentlichungen\/","og_locale":"de_DE","og_type":"article","og_title":"Wissenschaftliche Ver\u00f6ffentlichungen - summetix","og_description":"KUNDENINFORMATIONEN DER N\u00c4CHSTEN GENERATION Wissenschaftliche Ver\u00f6ffentlichungen Entdecken Sie verborgene Erkenntnisse in Kundenfeedback und komplexen qualitativen Daten. 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