Papers by Dana Dannélls
Transformer-based Swedish Semantic Role Labeling through Transfer Learning (2024.lrec-main)
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| Challenge: | Semantic Role Labeling (SRL) is a task in natural language understanding where the goal is to extract semantic roles for a given sentence. |
| Approach: | They propose to build a Transformer-based SRL system for Swedish by exploring multilingual and cross-lingual transfer learning methods and leveraging the Swedish FrameNet resource. |
| Outcome: | The proposed model outperforms two different cross-lingual transfer models and shows that the multilingual learning outperformed the other models. |
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. |