Prof. Dr. Margot Mieskes

• Application of machine language processing methods in other domains (e.g. education research, psychotherapy, financial market analyses, teaching support).
• Automatic summary of spoken and written natural language data
• Evaluation of automatic summary methods
• Reproducibility, transparency and ethical issues of NLP/CL field
• Information extraction from informal language data (e.g. Web 2.0 content) or transcribed spoken language
• Creation of corpora and annotations
• Evaluation of annotations and evaluation metrics

2023

Manon Reusens, Philipp Borchert, Margot Mieskes, Jochen De Weerdt, Bart Baesens: Investigating
Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques. Accepted to EMNLP 2023 main conference, https://doi.org/10.48550/arXiv.2310.10310, 16.10.2023

Nadine Probol and Margot Mieskes. 2023. Emotions in Spoken Language - Do we need acoustics?. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 71–84, Toronto, Canada. Conference: Association for Computational Linguistics.

Anya Belz, Craig Thomson, Ehud Reiter, Gavin Abercrombie, Jose M Alonso-Moral, Mohammad Arvan, Jackie Cheung, Mark Cieliebak, Elizabeth Clark, Kees van Deemter, Tanvi Dinkar, Ondřej Dušek, Steffen Eger, Qixiang Fang, Albert Gatt, Dimitra Gkatzia, Javier González-Corbelle, Dirk Hovy, Manuela Hürlimann, Takumi Ito, John D Kelleher, Filip Klubicka, Huiyuan Lai, Chris van der Lee, Emiel van Miltenburg, Yiru Li, Saad Mahamood, Margot Mieskes, Malvina Nissim, Natalie Parde, Ondřej Plátek, Verena Rieser, Pablo Mosteiro Romero, Joel Tetreault, Antonio Toral, Xiaojun Wan, Leo Wanner,
Lewis Watson, Diyi Yang: Missing information, unresponsive authors, experimental flaws:
The impossibility of assessing the reproducibility of previous human evaluations in NLP. arXiv preprint arXiv:2305.01633, 02.05.2023.

Margot Mieskes, Jacob Benz: h da@ ReproHum–Reproduction of Human Evaluation and Technical Pipeline. In: Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems, HumEval’23.

2022

Mieskes, Margot (2022). Replicability under near-perfect conditions – a case-study from automatic
summarization. In Proceedings of the Third Workshop on Insights from Negative Results in NLP,
pages 165–171, Dublin, Ireland. Association for Computational Linguistics

2021

Tuggener, D., Mieskes, Margot, Deriu, J., and Cieliebak, M. (2021). Are we summarizing the
right way? a survey of dialogue summarization data sets. In Proceedings of the Third Workshop on
New Frontiers in Summarization, pages 107–118, Online and in Dominican Republic. Association
for Computational Linguistics

Jurgens, D., Kolhatkar, V., Li, L., Mieskes, M., and Pedersen, T. (2021). Teaching NLP. In
Proceedings of the 2021 Annual Conference of the North American Chapter of the Association for
Computational Linguistics. to appear

Cohen, K., Fort, K., Mieskes, M., Névéol, A., and Gold, A. (2021). Reviewing natural language
processing research. In Proceedings of the 16th Conference of the European Chapter of the
Association for Computational Linguistics: Tutorial Abstracts, Online. Association for Computational
Linguistics

2020

Cohen, K., Fort, K., Mieskes, M., and Névéol, A. (2020). Reviewing natural language processing
research. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics:
Tutorial Abstracts, pages 16–18, Online. Association for Computational Linguistics

Mieskes, M., Loza Mencía, E., and Kronsbein, T. (2020). A data set for the analysis of text
quality dimensions in summarization evaluation. In Proceedings of the 12th Language Resources
and Evaluation Conference, pages 6690–6699, Marseille, France. European Language Resources
Association

Tauchmann, C. and Mieskes, M. (2020). Language agnostic automatic summarization evaluation.
In Proceedings of the 12th Language Resources and Evaluation Conference, pages 6656–6662,
Marseille, France. European Language Resources Association

Tauchmann, C., Daxenberger, J., and Mieskes, M (2020). The influence of input data complexity
on crowdsourcing quality. In Proceedings of the 25th International Conference on Intelligent User
Interfaces Companion, IUI ’20, page 71–72, New York, NY, USA. Association for Computing
Machinery

2019

Mieskes, M. and Padó, U. (2019). Summarization Evaluation meets Short-Answer Grading.
In Proceedings of the 8th Workshop for Natural Language Processing for Computer-Assisted
Language Learning (NLP4CALL), Turku, Finland, 30 September 2019

Blazevic, M., Börner, I., Komander, M., and Mieskes, M. (2019). 2019 germeval shared task on
offensive tweet detection h_da submission. In Proceedings of the GermEval 2019 Shared Task on
the Identification of Offensive Language (GermEval 2019), Erlangen, Germany, 8 October 2019

Mieskes, M., Fort, K., Névól, A., Grouin, C., and Cohen, K. (2019). Community perspective on
replicability in natural language processing. In Proceedings of the Conference on Recent Advances
in Natural Language Processing (RANLP 2019), Varna, Bulgaria, 2 – 4 September 2019

Mieskes, M. and Schmunk, S. (2019). OCR Quality and NLP Preprocessing. In Third Workshop
on Widening NLP (WiNLP 2019), Florence, Italy, 28 July 2019. non-archival publication

Preisler, B., Mieskes, M., and Becker, C. (2019). Bitcoin value and sentiment expressed in tweets.
In Proceedings of the Fourth Swiss Text Analytics Conference, Winterthur, Switzerland, 18 – 19
June 2019

2018

Mieskes, M. and Padó, U. (2018). Work smart - reducing effort in short-answer grading. In
Proceedings of the 7thWorkshop for Natural Language Processing for Computer-Assisted Language
Learning (NLP4CALL), Stockholm, Sweden, 07 November 2018

Mieskes, M. and Shutyi, S. (2018). Emotionality in Patients and Therapists speaking German. In
SecondWorkshop onWidening NLP (WiNLP 2018), New Orleans, USA, 01 June 2018. Unarchived
Paper

Tauchmann, C., Arnold, T., Hanselowski, A., Meyer, C. M., and Mieskes, M. (2018). Beyond
Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous
Data. In Proceedings of the Eleventh International Conference on Language Resources and
Evaluation (LREC 2018), Miyazaki, Japan, 7 – 12 May 2018

Mieskes, M. and Stiegelmayr, A. (2018). Preparing Data from Psychotherapy for Natural Language
Processing. In Proceedings of the Eleventh International Conference on Language Resources and
Evaluation (LREC 2018), Miyazaki, Japan, 7 – 12 May 2018

Siegel, M. and Mieskes, M. (2018). Information science education in darmstadt. In Proceedings of
the Future of Education in Information Science – International EINFOSE Symposium, Pisa, Italy

2017

Stiegelmayr, A. and Mieskes, M. (2017). Using argumentative structure to grade persuasive
essays. In GSCL 2017 – Language Technologies for the Challenges of the Digital Age

Mieskes, M. (2017a). A Quantitative Study of Data in the NLP community. In Proceedings of
the First ACL Workshop on Ethics in Natural Language Processing, pages 23–29, Valencia, Spain.
Association for Computational Linguistics

Schulz, K., Mieskes, M., and Becker, C. (2017). h-da Participation at Germeval Subtask B:
Document-level Polarity. In Proceedings of the GermEval 2017: Shared Task on Aspect-based
Sentiment in Social Media Customer Feedback, Berlin, Germany

Mieskes, M. (2017b). How Machines understand Speech. Babel – The Language Magazine, (20).
Pull-Out Poster

2016

Benikova, D., Mieskes, M., Meyer, C. M., and Gurevych, I. (2016). Bridging the gap between
extractive and abstractive summaries: Creation and evaluation of coherent extracts from
heterogeneous sources. In Proceedings of the 26th International Conference on Computational
Linguistics (COLING), Osaka, Japan, December 13–16 2016, pages 1039–1050

Remus, S., Hintz, G., Benikova, D., Arnold, T., Eckle-Kohler, J., Meyer, C. M., Mieskes, M., and
Biemann, C. (2016). EmpiriST: AIPHES Robust Tokenization and POS-Tagging for Different
Genres. In Proceedings of the 10th Web as Corpus Workshop (WAC-X), pages 106–114

Meyer, C. M., Benikova, D., Mieskes, M., and Gurevych, I. (2016). MDSWriter: Annotation
tool for creating high-quality multi-document summarization corpora. In Proceedings of the 54th
Annual Meeting of the Association for Computational Linguistics (ACL 2016): System Demonstrations,
Berlin, Germany, 7–12 August 2016, pages 97–102. Association for Computational Linguistics

Henß, S., Mieskes, M., and Gurevych, I. (2015). A reinforcement learning approach for adaptive
single- and multi-document summarization. In International Conference of the German Society for
Computational Linguistics and Language Technology (GSCL-2015), Duisburg-Essen, Germany,
30 September – 2 October 2015, pages 3–12

Further publications under:

ACL-Anthology