Neural Machine Translation for English-Kazakh with Morphological Segmentation and Synthetic Data. - Antonio Toral; Lukas Edman; Galiya Yeshmagambetova; Jennifer Spenader (WMT (2), 2019)

Low-Resource Unsupervised NMT: Diagnosing the Problem and Providing a Linguistically Motivated Solution. - Lukas Edman; Antonio Toral; Gertjan van Noord (EAMT, 2020)

Data Selection for Unsupervised Translation of German-Upper Sorbian. - Lukas Edman; Antonio Toral; Gertjan van Noord (WMT@EMNLP, 2020)

Machine Translation for English-Inuktitut with Segmentation, Data Acquisition and Pre-Training. - Christian Roest; Lukas Edman; Gosse Minnema; Kevin Kelly; Jennifer Spenader; Antonio Toral (WMT@EMNLP, 2020)

The Importance of Context in Very Low Resource Language Modeling. - Lukas Edman; Antonio Toral; Gertjan van Noord (ICON, 2021)

Unsupervised Translation of German-Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language. - Lukas Edman; Ahmet Üstün; Antonio Toral; Gertjan van Noord (WMT@EMNLP, 2021)

Subword-Delimited Downsampling for Better Character-Level Translation. - Lukas Edman; Antonio Toral; Gertjan van Noord (EMNLP (Findings), 2022)

RUG-1-Pegasussers at SemEval-2022 Task 3: Data Generation Methods to Improve Recognizing Appropriate Taxonomic Word Relations. - Wessel Poelman; Gijs Danoe; Esther Ploeger; Frank van den Berg; Tommaso Caselli; Lukas Edman (SemEval@NAACL, 2022)

Patching Leaks in the Charformer for Efficient Character-Level Generation. - Lukas Edman; Antonio Toral; Gertjan van Noord (CoRR, 2022)

LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification. - Konstantin Chernyshev; Ekaterina Garanina; Duygu Bayram; Qiankun Zheng; Lukas Edman (SemEval@ACL, 2023)

Are Character-level Translations Worth the Wait? An Extensive Comparison of Character- and Subword-level Models for Machine Translation. - Lukas Edman; Antonio Toral; Gertjan van Noord (CoRR, 2023)

Too Much Information: Keeping Training Simple for BabyLMs. - Lukas Edman; Lisa Bylinina (CoRR, 2023)

CUTE: Measuring LLMs' Understanding of Their Tokens. - Lukas Edman; Helmut Schmid; Alexander Fraser 001 (EMNLP, 2024)

Are BabyLMs Second Language Learners? - Lukas Edman; Lisa Bylinina; Faeze Ghorbanpour; Alexander Fraser 001 (CoRR, 2024)

Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine Translation. - Lukas Edman; Gabriele Sarti; Antonio Toral; Gertjan van Noord; Arianna Bisazza (Trans. Assoc. Comput. Linguistics, 2024)

EXECUTE: A Multilingual Benchmark for LLM Token Understanding. - Lukas Edman; Helmut Schmid; Alexander Fraser 001 (ACL (Findings), 2025)

Positional Overload: Positional Debiasing and Context Window Extension for Large Language Models using Set Encoding. - Lukas Kinder; Lukas Edman; Alexander Fraser 001; Tobias Käfer (ACL (1), 2025)