In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
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Question: We acquired the data in two rounds of annotation. In the first one, we were looking for original and uncommon sentence change suggestions.

Answer: How do they introduce language variation?


Question: Our ASR and ST models follow the architecture in berard2018end, but have 3 decoder layers like that in pino2019harnessing.

Answer: What is the architecture of their model?


Question: Throughout this article, we use two different embedding spaces. The first is the widely used representation built on GoogleNews BIBREF8 . The second is taken from BIBREF2 , and was trained on a Reddit dataset BIBREF9 .

Answer:
Which embeddings do they detect biases in?