| 2025 | EMNLP | Learning to Translate Ambiguous Terminology by Preference Optimization on Post-Edits. | Nathaniel Berger, Johannes Eschbach-Dymanus, Miriam Exel, Matthias Huck, Stefan Riezler |
| 2024 | AMTA | How Effective is Synthetic Data and Instruction Fine-tuning for Translation with Markup using LLMs? | Raj Dabre, Haiyue Song, Miriam Exel, Bianka Buschbeck, Johannes Eschbach-Dymanus, Hideki Tanaka |
| 2024 | EAMT | Prompting Large Language Models with Human Error Markings for Self-Correcting Machine Translation. | Nathaniel Berger, Stefan Riezler, Miriam Exel, Matthias Huck |
| 2024 | EAMT | Exploring the Effectiveness of LLM Domain Adaptation for Business IT Machine Translation. | Johannes Eschbach-Dymanus, Frank Essenberger, Bianka Buschbeck, Miriam Exel |
| 2024 | NAACL | Contextual Refinement of Translations: Large Language Models for Sentence and Document-Level Post-Editing. | Sai Koneru, Miriam Exel, Matthias Huck, Jan Niehues |
| 2023 | EACL | Analyzing Challenges in Neural Machine Translation for Software Localization. | Sai Koneru, Matthias Huck, Miriam Exel, Jan Niehues |
| 2023 | EAMT | Enhancing Supervised Learning with Contrastive Markings in Neural Machine Translation Training. | Nathaniel Berger, Miriam Exel, Matthias Huck, Stefan Riezler |
| 2022 | EAMT | "Hi, how can I help you?" Improving Machine Translation of Conversational Content in a Business Context. | Bianka Buschbeck, Jennifer Mell, Miriam Exel, Matthias Huck |
| 2022 | IJCNLP | A Multilingual Multiway Evaluation Data Set for Structured Document Translation of Asian Languages. | Bianka Buschbeck, Raj Dabre, Miriam Exel, Matthias Huck, Patrick Huy, Raphael Rubino, Hideki Tanaka |
| 2020 | EAMT | Terminology-Constrained Neural Machine Translation at SAP. | Miriam Exel, Bianka Buschbeck, Lauritz Brandt, Simona Doneva |
| 2020 | EAMT | Incorporating External Annotation to improve Named Entity Translation in NMT. | Maciej Modrzejewski, Miriam Exel, Bianka Buschbeck, Thanh-Le Ha, Alexander Waibel |