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Whereas much of the success of the current generation of neural languagemodels has been driven by increasingly large training corpora, relativelylittle research has been dedicated to analyzing these massive sources oftextual data. In this exploratory analysis, we delve deeper into the CommonCrawl, a colossal web corpus that is extensively used for training languagemodels. We find that it contains a significant amount of undesirable content,including hate speech and sexually explicit content, even after filteringprocedures. We discuss the potential impacts of this content on language modelsand conclude with future research directions and a more mindful approach tocorpus collection and analysis.

What's in the Box? A Preliminary Analysis of Undesirable Content in the Common Crawl Corpus