Papers by Yvonne Adesam

2 papers
Superlim: A Swedish Language Understanding Evaluation Benchmark (2023.emnlp-main)

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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.
Training a Swedish Constituency Parser on Six Incompatible Treebanks (2020.lrec-1)

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Challenge: Syntactic parsing is a widely used intermediate step in several natural language processing tasks.
Approach: They propose to use a function-tagged constituent treebank for Swedish which includes discontinuous constituents to improve the accuracy.
Outcome: The proposed parser can be trained on additional treebanks that use other annotation models.

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