Jan Trienes

Hi there, I'm Jan Trienes, a fourth year PhD student of computer science at the University of Marburg, advised by Prof. Christin Seifert. My research in natural language processing focuses on generation, in particular text summarization and simplification. Using applications in the medical domain, I aim to better understand how to evaluate generated text and how to improve the robustness of generation models.

For the fall semester of 2023, I visited the University of Texas at Austin to work with Jessy Li. Prior to my PhD, I worked as machine learning engineer at Nedap Healthcare. During my master studies at the University of Twente, I did a research internship at the University of Stavanger, visiting Prof. Krisztian Balog.





FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence
Sebastian Joseph, Lily Chen, Jan Trienes, Hannah Louisa Göke, Monika Coers, Wei Xu, Byron C. Wallace, Junyi Jessy Li
62nd Annual Meeting of the Association for Computational Linguistics (ACL), to appear, 2024
[pdf] [code] [data]

InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
Jan Trienes, Sebastian Joseph, Jörg Schlötterer, Christin Seifert, Kyle Lo, Wei Xu, Byron C. Wallace, Junyi Jessy Li
62nd Annual Meeting of the Association for Computational Linguistics (ACL), to appear, 2024
[pdf] [website] [code] [data]

Guidance in Radiology Report Summarization: An Empirical Evaluation and Error Analysis
Jan Trienes, Paul Youssef, Jörg Schlötterer, Christin Seifert
16th International Natural Language Generation Conference (INLG), 2023, ⭐ Nomination for Best Evaluation Award
[pdf] [code] [slides]

From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, Michelle Peters, Yasmin Schmitt, Jörg Schlötterer, Maurice van Keulen, Christin Seifert
ACM Computing Surveys (CSUR), 2023
[pdf] [website]

Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset
Jan Trienes, Jörg Schlötterer, Hans-Ulrich Schildhaus, Christin Seifert
EMNLP Workshop on Text Simplification, Accessibility, and Readability (TSAR), 2022
[pdf] [code] [slides] [poster]

Generating Synthetic Training Data for Supervised De-Identification of Electronic Health Records
Claudia A. Libbi, Jan Trienes, Dolf Trieschnigg, Christin Seifert
Future Internet, 13(5):136, 2021
[pdf] [code]

Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records
Jan Trienes, Dolf Trieschnigg, Christin Seifert, Djoerd Hiemstra
1st ACM WSDM Health Search and Data Mining Workshop (HSDM’20), 2020, ⭐ Best Paper Award
[pdf] [code] [slides]

Identifying Unclear Questions in Community Question Answering Websites
Jan Trienes, Krisztian Balog
41st European Conference on Information Retrieval (ECIR’19), 2019
[pdf] [code]

Recommending Users: Whom to Follow on Federated Social Networks
Jan Trienes, Andrés Torres Cano, Djoerd Hiemstra
17th Dutch-Belgian Information Retrieval Workshop (DIR’18), 2018