Papers by Martin Malmsten
Superlim: A Swedish Language Understanding Evaluation Benchmark (2023.emnlp-main)
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Aleksandrs Berdicevskis, Gerlof Bouma, Robin Kurtz, Felix Morger, Joey Öhman, Yvonne Adesam, Lars Borin, Dana Dannélls, Markus Forsberg, Tim Isbister, Anna Lindahl, Martin Malmsten, Faton Rekathati, Magnus Sahlgren, Elena Volodina, Love Börjeson, Simon Hengchen, Nina Tahmasebi
| Challenge: | In this paper, we present a multi-task benchmark for Swedish language models . we address methodological challenges, such as mitigating the Anglocentric bias when creating datasets for a less-resourced language . |
| Approach: | They propose a multi-task NLP benchmark for Swedish language models . they propose to use superlim to evaluate Swedish language model performance . |
| Outcome: | The proposed benchmark does not approach ceiling performance on any of the tasks, suggesting it is difficult to implement. |