Thomas Arnold


DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting
Timour Igamberdiev | Thomas Arnold | Ivan Habernal
Proceedings of the 29th International Conference on Computational Linguistics

Text rewriting with differential privacy (DP) provides concrete theoretical guarantees for protecting the privacy of individuals in textual documents. In practice, existing systems may lack the means to validate their privacy-preserving claims, leading to problems of transparency and reproducibility. We introduce DP-Rewrite, an open-source framework for differentially private text rewriting which aims to solve these problems by being modular, extensible, and highly customizable. Our system incorporates a variety of downstream datasets, models, pre-training procedures, and evaluation metrics to provide a flexible way to lead and validate private text rewriting research. To demonstrate our software in practice, we provide a set of experiments as a case study on the ADePT DP text rewriting system, detecting a privacy leak in its pre-training approach. Our system is publicly available, and we hope that it will help the community to make DP text rewriting research more accessible and transparent.


Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous Data
Christopher Tauchmann | Thomas Arnold | Andreas Hanselowski | Christian M. Meyer | Margot Mieskes
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


Network Motifs May Improve Quality Assessment of Text Documents
Thomas Arnold | Karsten Weihe
Proceedings of TextGraphs-10: the Workshop on Graph-based Methods for Natural Language Processing

EmpiriST: AIPHES - Robust Tokenization and POS-Tagging for Different Genres
Steffen Remus | Gerold Hintz | Chris Biemann | Christian M. Meyer | Darina Benikova | Judith Eckle-Kohler | Margot Mieskes | Thomas Arnold
Proceedings of the 10th Web as Corpus Workshop