
Researcher
Building C7.1
Room 0.14
Universität des Saarlandes (Saarland University)
66123 Saarbrücken
druiter (at) lsv dot uni-saarland dot de
+49 681 302 58 58133
Research Interests
- Self-Supervised Learning
- Low Resource Machine Translation
- Low Resource Text Classification
With a general enthusiasm for all kinds of low-resource settings, unsupervised machine learning approaches as well as multitask learning, representation learning and multilingual systems.
Publications
- Awantee Deshpande, Dana Ruiter, Marius Mosbach, Dietrich Klakow. 2022. StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and Stereotypes. In Workshop of Online Abuse and Harms at NAACL 2022.
- Dana Ruiter, Thomas Kleinbauer, Cristina España-Bonet, Josef van Genabith, Dietrich Klakow. 2022. Exploiting Social Media Content for Self-Spervised Style Transfer. In SocialNLP 2022 at NAACL 2022.
- Dana Ruiter, Liane Reiners, Ashwin Geet D’Sa, Thomas Kleinbauer, Dominique Fohr, Irina Illina, Dietrich Klakow, Christian Schemer, Angeliki Monnier. 2022. Placing M-Phasis on the Plurality of Hate: A Feautre-Based Corpus of Hate Online. In Proceedings of the Language Resources and Evaluation Conference 2022.
- Svetlana Tchistiakova, Jesujoba Alabi, Koel Dutta Chowdhury, Sourav Dutta, Dana Ruiter. 2021. EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT. In Proceedings of the Sixth Conference on Machine Translation.
- Dana Ruiter, Dietrich Klakow, Josef van Genabith, Cristina España-Bonet. 2021. Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages. In MT-Summit 2021 (Research Track).
- David Adelani, Dana Ruiter, Jesujoba Alabi, Damilola Adebonojo, Adesina Ayeni, Mofetoluwa Adeyemi, Ayodele Awokoya, Cristina España-Bonet. 2021. The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation. In MT-Summit 2021 (Research Track).
- Vanessa Hahn, Dana Ruiter, Thomas Kleinbauer, Dietrich Klakow. 2021. Modeling Profanity and Hate Speech in Social Media with Semantic Subspaces. In Processings of the 5th Workshop on Online Abuse and Harms (WOAH 2021) at ACL 2021.
- Susann Boy, Dana Ruiter, Dietrich Klakow. 2021. Emoji-Based Transfer Learning for Sentiment Tasks. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop.
- Sourav Dutta, Jesujoba Alabi, Saptarashmi Bandyopadhyay, Dana Ruiter, Josef van Genabith. 2020. UdS-DFKI@WMT20: Unsupervised MT and Very Low Resource Supervised MT for German-Upper Sorbian. In Proceedings of the Fifth Conference on Machine Translation.
- Moritz Wolf, Dana Ruiter, Ashwin Geet D’Sa, Liane Reiners, Jan Alexandersson, Dietrich Klakow. 2020. HUMAN: Hierarchical Universal Modular ANnotator. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations.
- Dana Ruiter, Josef van Genabith, Cristina España-Bonet. 2020. Self-Induced Curriculum Learning in Self-Supervised Neural Machine Translation. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Virtual.
- Ashwin Geet D’Sa, Irina Illina, Dominique Fohr, Dietrich Klakow, Dana Ruiter. 2020. Label Propagation-Based Semi-Supervised Learning for Hate Speeh Classification. In Proceedings of the First Workshop on Insights from Negative Results in NLP.
- Dana Ruiter, Md. Ataur Rahman, Dietrich Klakow. 2019. LSV-UdS at HASOC 2019: The Problem of Defining Hate. In Forum for Information Retrieval Evaluation, Kolkata, India.
- Dana Ruiter, Cristina España-Bonet, Josef van Genabith. 2019.
Self-Supervised Neural Machine Translation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Volume 2: Short Papers, Florence, Italy. Association for Computational Linguistics. - Cristina España-Bonet, Dana Ruiter, Josef van Genabith. 2019. UdS-DFKI Participation at WMT 2019: Low-Resource (en-gu) and Coreference-Aware (en-de) Systems. In Fourth Conference on Machine Translation, Florence, Italy.