Johannes Daxenberger

About Johannes Daxenberger

Johannes Daxenberger, With an exceptional h-index of 17 and a recent h-index of 15 (since 2020), a distinguished researcher at Technische Universität Darmstadt, specializes in the field of Natural Language Processing, Computational Linguistics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting

Using information-seeking argument mining to improve service

Information-Seeking Argument Mining: A Step Towards Identifying Reasons in Textual Analysis to Improve Services

On the Effect of Sample and Topic Sizes for Argument Mining Datasets

Stance detection benchmark: How robust is your stance detection?

From argument search to argumentative dialogue: A topic-independent approach to argument acquisition for dialogue systems

Multilingual UKP Sentential Argument Mining Corpus

Evaluation of argument search approaches in the context of argumentative dialogue systems

Johannes Daxenberger Information

University

Position

Ubiquitous Knowledge Processing (UKP) Lab

Citations(all)

1658

Citations(since 2020)

1368

Cited By

737

hIndex(all)

17

hIndex(since 2020)

15

i10Index(all)

21

i10Index(since 2020)

18

Email

University Profile Page

Google Scholar

Johannes Daxenberger Skills & Research Interests

Natural Language Processing

Computational Linguistics

Top articles of Johannes Daxenberger

Title

Journal

Author(s)

Publication Date

Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting

arXiv preprint arXiv:2303.03053

Nina Mouhammad

Johannes Daxenberger

Benjamin Schiller

Ivan Habernal

2023/3/6

Using information-seeking argument mining to improve service

Journal of Service Research

Bernd Skiera

Shunyao Yan

Johannes Daxenberger

Marcus Dombois

Iryna Gurevych

2022/11

Information-Seeking Argument Mining: A Step Towards Identifying Reasons in Textual Analysis to Improve Services

Skiera, Bernd, Shunyao Yan, Johannes Daxenberger, Marcus Dombois, Iryna Gurevych. Using Information-Seeking Argument Mining to Improve Service. Journal of Service Research

Bernd Skiera

Shunyao Yan

Johannes Daxenberger

Marcus Dombois

Iryna Gurevych

2022/6/22

On the Effect of Sample and Topic Sizes for Argument Mining Datasets

arXiv preprint arXiv:2205.11472

Benjamin Schiller

Johannes Daxenberger

Iryna Gurevych

2022/5/23

Stance detection benchmark: How robust is your stance detection?

KI-Künstliche Intelligenz

Benjamin Schiller

Johannes Daxenberger

Iryna Gurevych

2021/11

From argument search to argumentative dialogue: A topic-independent approach to argument acquisition for dialogue systems

Niklas Rach

Carolin Schindler

Isabel Feustel

Johannes Daxenberger

Wolfgang Minker

...

2021/7

Multilingual UKP Sentential Argument Mining Corpus

Christian Stab

Tristan Miller

Pranav Rai

Benjamin Schiller

Iryna Gurevych

...

2020

Evaluation of argument search approaches in the context of argumentative dialogue systems

Niklas Rach

Yuki Matsuda

Johannes Daxenberger

Stefan Ultes

Keiichi Yasumoto

...

2020/5

Arguments as social good: Good arguments in times of crisis

Proocedings of the AAAI Fall 2020 Symposium on AI for Social Good

Johannes Daxenberger

Irina Gurevych

2020

Aspect-controlled neural argument generation

arXiv preprint arXiv:2005.00084

Benjamin Schiller

Johannes Daxenberger

Iryna Gurevych

2020/4/30

BWS Argument Similarity Corpus

Nandan Thakur

Johannes Daxenberger

Iryna Gurevych

2020

Fine-grained argument unit recognition and classification

Proceedings of the AAAI Conference on Artificial Intelligence

Dietrich Trautmann

Johannes Daxenberger

Christian Stab

Hinrich Schütze

Iryna Gurevych

2020/4/3

Augmented SBERT: Data augmentation method for improving bi-encoders for pairwise sentence scoring tasks

Nandan Thakur

Nils Reimers

Johannes Daxenberger

Iryna Gurevych

2020/10/16

Training Data for Aspect-Controlled Neural Argument Generation

Benjamin Schiller

Iryna Gurevych

Johannes Daxenberger

2020

The influence of input data complexity on crowdsourcing quality

Christopher Tauchmann

Johannes Daxenberger

Margot Mieskes

2020/3/17

Argumentext: argument classification and clustering in a generalized search scenario

Datenbank-Spektrum

Johannes Daxenberger

Benjamin Schiller

Chris Stahlhut

Erik Kaiser

Iryna Gurevych

2020/6/16

Weights for Aspect-Controlled Neural Argument Generation

Benjamin Schiller

Johannes Daxenberger

Iryna Gurevych

2020

Aspect-controlled neural argument generation (version 1)

arXiv eprint archive

Benjamin Schiller

Johannes Daxenberger

Iryna Gurevych

2020

How to probe sentence embeddings in low-resource languages: On structural design choices for probing task evaluation

arXiv preprint arXiv:2006.09109

Steffen Eger

Johannes Daxenberger

Iryna Gurevych

2020/6/16

See List of Professors in Johannes Daxenberger University(Technische Universität Darmstadt)

Co-Authors

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