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.

[EX Q]: We test mgru on two well-known datasets, the Penn Treebank and Text8.
Question: Which dataset do they train their models on?
[EX A]: Penn Treebank Text8

[EX Q]: Our experiments are run using the English$
ightarrow $Italian/German portions of the MuST-C corpus BIBREF25, which is extracted from TED talks, using the same train/validation/test split as provided with the corpus (see Table TABREF18). As additional data, we use a mix of public and proprietary data for about 16 million sentence pairs for English-Italian (En-It) and $4.4$ million WMT14 sentence pairs for the English-German (En-De).
Question: What dataset do they use?
[EX A]: English$
ightarrow $Italian/German portions of the MuST-C corpus As additional data, we use a mix of public and proprietary data for about 16 million sentence pairs for English-Italian (En-It) and $4.4$ million WMT14 sentence pairs for the English-German (En-De)

[EX Q]: The approaches we use and what we mean by 'success' are thus guided by our research questions.

Domain experts and fellow researchers can provide feedback on questions and help with dynamically revising them. Sometimes we also hope to connect to multiple disciplines. Questions about potential "dual use" may also arise.
Question: What approaches do they use towards text analysis?
[EX A]:
Domain experts and fellow researchers can provide feedback on questions and help with dynamically revising them. connect to multiple disciplines dual use