Web: http://arxiv.org/abs/2209.10335

Sept. 23, 2022, 1:16 a.m. | Thiemo Wambsganss, Vinitra Swamy, Roman Rietsche, Tanja Käser

cs.CL updates on arXiv.org arxiv.org

Natural Language Processing (NLP) has become increasingly utilized to provide
adaptivity in educational applications. However, recent research has
highlighted a variety of biases in pre-trained language models. While existing
studies investigate bias in different domains, they are limited in addressing
fine-grained analysis on educational and multilingual corpora. In this work, we
analyze bias across text and through multiple architectures on a corpus of
9,165 German peer-reviews collected from university students over five years.
Notably, our corpus includes labels such as …

arxiv bias data data modeling deep dive educational german modeling peer peer-review review

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