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@@ -238,9 +238,8 @@ Native Russian speakers who passed the language exam.
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  ### Discussion of Biases
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  The datasets we collected include large segments representing the Internet domain, and
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- therefore, they may contain various stereotypes and biases, as well as the pre-train models.
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- We acknowledge the potential for biases to emerge in both the training data and the model’s predictions.
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- Proper evaluation is still needed to explore possible model vulnerabilities in terms of generalizing on the new data and specific new data.
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  ### Other Known Limitations
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@@ -252,13 +251,13 @@ The proposed generative methodology of spell checking and the created models hav
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  - Context;
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  - Languages.
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- More detaild could be found in the paper (see 'Citation Information' below)
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  ## Additional Information
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  ### Dataset Curators
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- [More Information Needed]
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  ### Licensing Information
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  ### Discussion of Biases
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  The datasets we collected include large segments representing the Internet domain, and
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+ therefore, they may contain various stereotypes and biases.
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+ We acknowledge the potential for biases to emerge in the training data.
 
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  ### Other Known Limitations
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  - Context;
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  - Languages.
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+ More detailes could be found in the paper (see 'Citation Information' below)
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  ## Additional Information
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  ### Dataset Curators
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+ Nikita Martynov nikita.martynov.98@list.ru
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  ### Licensing Information
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