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.
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Question: We make copies of the monolingual model for each language and add additional crosslingual latent variables (CLVs) to couple the monolingual models, capturing crosslingual semantic role patterns. Concretely, when training on parallel sentences, whenever the head words of the arguments are aligned, we add a CLV as a parent of the two corresponding role variables. 
 Question: Do they add one latent variable for each language pair in their Bayesian model?

Answer: Yes


Question: To make the annotated data publicly available, we selected 70 news articles from Arabic WikiNews site. These articles cover recent news from year 2013 to year 2015 in multiple genres (politics, economics, health, science and technology, sports, arts, and culture.) Articles contain 18,300 words, and they are evenly distributed among these 7 genres with 10 articles per each. 
 Question: Where did they collect their dataset from?

Answer: from Arabic WikiNews site


Question: We use the dropout technique of Gal & Ghahramani gal as a baseline because it is the most similar dropout technique to our approach and denote it VBD (variational binary dropout). 
 Question: What is binary variational dropout?

Answer:
the dropout technique of Gal & Ghahramani gal