papers

Publications (10)

cs.CL2024

InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification

Jan Trienes, Sebastian Joseph, Jörg Schlötterer +5

Text simplification aims to make technical texts more accessible to laypeople but often results in deletion of information and vagueness. This work proposes InfoLossQA, a framework…

cs.CL2025

Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support

Jan Trienes, Anastasiia Derzhanskaia, Roland Schwarzkopf +3

We present Marcel, a lightweight and open-source conversational agent designed to support prospective students with admission-related inquiries. The system aims to provide fast and…

cs.CL2024

FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence

Sebastian Antony Joseph, Lily Chen, Jan Trienes +5

Plain language summarization with LLMs can be useful for improving textual accessibility of technical content. But how factual are these summaries in a high-stakes domain like medi…

cs.AI2023

From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI

Meike Nauta, Jan Trienes, Shreyasi Pathak +6

The rising popularity of explainable artificial intelligence (XAI) to understand high-performing black boxes raised the question of how to evaluate explanations of machine learning…

cs.CL2020

Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records

Jan Trienes, Dolf Trieschnigg, Christin Seifert +1

Unstructured information in electronic health records provide an invaluable resource for medical research. To protect the confidentiality of patients and to conform to privacy regu…

cs.CL2024

Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding

Ahmad Idrissi-Yaghir, Amin Dada, Henning Schäfer +17

Recent advances in natural language processing (NLP) can be largely attributed to the advent of pre-trained language models such as BERT and RoBERTa. While these models demonstrate…