instruction:
In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
question:
In particular, we aggregate documents from the CommonCrawl dataset that has the most overlapping n-grams with the questions. We name this dataset STORIES since most of the constituent documents take the form of a story with long chain of coherent events. Figure 5 -left and middle show that STORIES always yield the highest accuracy for both types of input processing.
Question: Which of their training domains improves performance the most?
answer:
documents from the CommonCrawl dataset that has the most overlapping n-grams with the question

question:
In this work, we develop a technique to rapidly transfer an existing pre-trained model from English to other languages in an energy efficient way BIBREF8.
Question: How much training data from the non-English language is used by the system?
answer:
No data. Pretrained model is used.

question:
This framework has potential applications when comparing different gold standards, considering the design choices for a new gold standard and performing qualitative error analyses for a proposed approach.
Question: Have they made any attempt to correct MRC gold standards according to their findings?
answer:
Yes