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.

Attention-base translation model We use the system of BIBREF6 , a convolutional sequence to sequence model. 
 Question: Which translation system do they use to translate to English?
Attention-based translation model with convolution sequence to sequence model

We modeled the relationship between word count and the two metrics of user engagement (overall rating, mean number of turns) in separate linear regressions.

Results showed that users who, on average, produced utterances with more words gave significantly higher ratings ($\beta $=0.01, SE=0.002, t=4.79, p$<$0.001)(see Figure 2) and engaged with Gunrock for significantly greater number of turns ($\beta $=1.85, SE=0.05, t=35.58, p$<$0.001) (see Figure 2). These results can be interpreted as evidence for Gunrock's ability to handle complex sentences, where users are not constrained to simple responses to be understood and feel engaged in the conversation – and evidence that individuals are more satisfied with the conversation when they take a more active role, rather than the system dominating the dialog. On the other hand, another interpretation is that users who are more talkative may enjoy talking to the bot in general, and thus give higher ratings in tandem with higher average word counts. 
 Question: How do they correlate user backstory queries to user satisfaction?
modeled the relationship between word count and the two metrics of user engagement (overall rating, mean number of turns) in separate linear regressions

For our study, we consider that a tweet went viral if it was retweeted more than 1000 times. 
 Question: What is the threshold for determining that a tweet has gone viral?

1000