Papers by Michael Jungo

2 papers
How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers (2022.findings-emnlp)

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Challenge: Pretrained language models use the attention mechanism to contextualize input inputs . but, we find that it is not as important as thought for pretrained models .
Approach: They propose a probing method that replaces input-dependent attention matrices with constant ones.
Outcome: The proposed method improves performance of pretrained language models without input-dependent attention.
Automatic Creation of Text Corpora for Low-Resource Languages from the Internet: The Case of Swiss German (2020.lrec-1)

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Challenge: Despite the small pool of speakers, there are still few natural language processing corpora, studies or tools for Swiss German.
Approach: They propose to use a web scraper to generate the largest Swiss German text corpus . they show that the tool can be applied to other low-resource languages as well .
Outcome: The proposed tool significantly improves language modeling in Swiss German, the authors show .

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