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.

Q: We took inspiration from these works to design our experiments to solve the CSKS task. 
 Question: What problem do they apply transfer learning to?

A: CSKS task
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Q: 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?

A: Yes
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Q: We evaluate the sequence-to-sequence QRNN architecture described in SECREF5 on a challenging neural machine translation task, IWSLT German–English spoken-domain translation, applying fully character-level segmentation.  
 Question: What languages pairs are used in machine translation?

A:
German–English
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