Papers by Samuel Rönnqvist
Beyond the English Web: Zero-Shot Cross-Lingual and Lightweight Monolingual Classification of Registers (2021.eacl-srw)
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Liina Repo, Valtteri Skantsi, Samuel Rönnqvist, Saara Hellström, Miika Oinonen, Anna Salmela, Douglas Biber, Jesse Egbert, Sampo Pyysalo, Veronika Laippala
| Challenge: | Existing studies on register classification for web documents have limited results due to skewed datasets and low performance. |
| Approach: | They propose two new register-annotated corpora for French and Swedish . they show that deep pre-trained language models perform strongly in these languages . |
| Outcome: | The proposed models outperform existing models in English and Finnish and can match or surpass existing models. |
Explaining Classes through Stable Word Attributions (2022.findings-acl)
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| Challenge: | Input saliency methods have become popular for explaining predictions of deep learning models, but there has been little work investigating methods for aggregating prediction-level explanations to the class level. |
| Approach: | They propose a method to aggregate prediction-level explanations to the class level using XLM-R and Integrated Gradients input attribution methods. |
| Outcome: | The proposed method extracts keyword lists of classes from text classification tasks and evaluates them on web register data. |