Henning Wachsmuth

4.0k total citations
89 papers, 1.3k citations indexed

About

Henning Wachsmuth is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Henning Wachsmuth has authored 89 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Artificial Intelligence, 32 papers in Information Systems and 8 papers in Sociology and Political Science. Recurrent topics in Henning Wachsmuth's work include Topic Modeling (50 papers), Natural Language Processing Techniques (33 papers) and Software Engineering Research (23 papers). Henning Wachsmuth is often cited by papers focused on Topic Modeling (50 papers), Natural Language Processing Techniques (33 papers) and Software Engineering Research (23 papers). Henning Wachsmuth collaborates with scholars based in Germany, United States and Poland. Henning Wachsmuth's co-authors include Benno Stein, Khalid Al‐Khatib, Matthias Hagen, Johannes Kiesel, Yamen Ajjour, Martin Potthast, Giovanni Da San Martino, Shahbaz Syed, Wei-Fan Chen and Alberto Barrón‐Cedeño and has published in prestigious journals such as SHILAP Revista de lepidopterología, Communications of the ACM and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Henning Wachsmuth

78 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Henning Wachsmuth Germany	21	1.1k	421	204	58	46	89	1.3k
Swapna Somasundaran United States	17	1.2k 1.0×	198 0.5×	125 0.6×	59 1.0×	40 0.9×	35	1.3k
Patricio Martínez-Barco Spain	19	834 0.7×	186 0.4×	179 0.9×	41 0.7×	32 0.7×	93	1.0k
Pierpaolo Basile Italy	15	776 0.7×	455 1.1×	85 0.4×	37 0.6×	55 1.2×	89	1.0k
Muhammad Abdul-Mageed Canada	19	1.5k 1.3×	249 0.6×	137 0.7×	61 1.1×	27 0.6×	88	1.7k
Maria Soledad Pera United States	15	423 0.4×	454 1.1×	118 0.6×	43 0.7×	48 1.0×	117	805
Kim Schouten Netherlands	10	748 0.7×	180 0.4×	129 0.6×	24 0.4×	58 1.3×	22	888
Yohan Jo United States	12	745 0.7×	227 0.5×	142 0.7×	43 0.7×	26 0.6×	31	1.0k
Jan Šnajder Croatia	18	1.1k 0.9×	218 0.5×	70 0.3×	40 0.7×	42 0.9×	110	1.2k
Tony Mullen Japan	10	704 0.6×	157 0.4×	70 0.3×	33 0.6×	28 0.6×	18	839
Sara Tonelli Italy	20	1.0k 0.9×	158 0.4×	52 0.3×	47 0.8×	51 1.1×	108	1.2k

Countries citing papers authored by Henning Wachsmuth

Since Specialization

Citations

This map shows the geographic impact of Henning Wachsmuth's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Henning Wachsmuth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Henning Wachsmuth more than expected).

Fields of papers citing papers by Henning Wachsmuth

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Henning Wachsmuth. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Henning Wachsmuth. The network helps show where Henning Wachsmuth may publish in the future.

Co-authorship network of co-authors of Henning Wachsmuth

This figure shows the co-authorship network connecting the top 25 collaborators of Henning Wachsmuth. A scholar is included among the top collaborators of Henning Wachsmuth based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Henning Wachsmuth. Henning Wachsmuth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Hüllermeier, Eyke, Stefan Kopp, Axel-Cyrille Ngonga Ngomo, et al.. (2025). Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues. 1 indexed citations

Park, Joonsuk, et al.. (2025). ArgInstruct: Specialized Instruction Fine-Tuning for Computational Argumentation. 11103–11127.

Wachsmuth, Henning, et al.. (2024). Towards Modeling and Evaluating Instructional Explanations in Teacher-Student Dialogues. 225–230.

Wachsmuth, Henning, et al.. (2024). Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness. 9294–9313.

Syed, Shahbaz, et al.. (2023). Frame-oriented Summarization of Argumentative Discussions. 114–129. 1 indexed citations

Faggioli, Guglielmo, Laura Dietz, Charles L. A. Clarke, et al.. (2023). Perspectives on Large Language Models for Relevance Judgment. Research Padua Archive (University of Padua). 39–50. 63 indexed citations

Gadiraju, Ujwal, et al.. (2023). Supporting Requesters in Writing Clear Crowdsourcing Task Descriptions Through Computational Flaw Assessment. Research Repository (Delft University of Technology). 737–749. 3 indexed citations

Lapesa, Gabriella, et al.. (2023). Mining, Assessing, and Improving Arguments in NLP and the Social Sciences. 1–6. 1 indexed citations

Syed, Shahbaz, et al.. (2023). Modeling Appropriate Language in Argumentation. 4344–4363. 3 indexed citations

10.

Wachsmuth, Henning, et al.. (2022). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Institutional Repository of Leibniz Universität Hannover (Leibniz Universität Hannover). 137–142. 2 indexed citations

11.

Rohlfing, Katharina J., Philipp Cimiano, Ingrid Scharlau, et al.. (2020). Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions on Cognitive and Developmental Systems. 13(3). 717–728. 45 indexed citations

12.

Chen, Wei-Fan, Khalid Al‐Khatib, Benno Stein, & Henning Wachsmuth. (2020). Detecting Media Bias in News Articles using Gaussian Bias Distributions. 4290–4300. 15 indexed citations

13.

Wachsmuth, Henning, et al.. (2018). Argumentation Synthesis following Rhetorical Strategies. Data Archiving and Networked Services (DANS). 3753–3765. 25 indexed citations

14.

Wachsmuth, Henning, Nona Naderi, Ivan Habernal, et al.. (2017). Argumentation Quality Assessment: Theory vs. Practice. 250–255. 27 indexed citations

15.

Wachsmuth, Henning, Khalid Al‐Khatib, & Benno Stein. (2016). Using Argument Mining to Assess the Argumentation Quality of Essays. Data Archiving and Networked Services (DANS). 1680–1691. 47 indexed citations

16.

Al‐Khatib, Khalid, Henning Wachsmuth, Johannes Kiesel, Matthias Hagen, & Benno Stein. (2016). A News Editorial Corpus for Mining Argumentation Strategies. Data Archiving and Networked Services (DANS). 3433–3443. 51 indexed citations

17.

Wachsmuth, Henning, et al.. (2014). Modeling Review Argumentation for Robust Sentiment Analysis. International Conference on Computational Linguistics. 553–564. 19 indexed citations

18.

Wachsmuth, Henning, Benno Stein, & Gregor Engels. (2013). Learning Efficient Information Extraction on Heterogeneous Texts. International Joint Conference on Natural Language Processing. 534–542. 1 indexed citations

19.

Wachsmuth, Henning & Benno Stein. (2012). Optimal Scheduling of Information Extraction Algorithms. International Conference on Computational Linguistics. 1281–1290. 4 indexed citations

20.

Wachsmuth, Henning, Peter Prettenhofer, & Benno Stein. (2010). Efficient Statement Identification for Automatic Market Forecasting. International Conference on Computational Linguistics. 1128–1136. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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