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]: TABREF5 displays the output behavior of models that we damaged to resemble the damage that causes aphasia. Because the output languages in all of our domains use tokens to represent meanings in many cases, it is expected that the analog to Wernicke's area is responsible for maintaining a high precision. 
 Question: Do they perform a quantitative analysis of their model displaying knowledge distortions?
[EX A]: Yes

[EX Q]: The seq2seq model with global attention gives the best results with an average target BLEU score of 29.65 on the style transfer dataset, compared with an average target BLEU score of 26.97 using the seq2seq model with pointer networks. 
 Question: What is best BLEU score of language style transfer authors got?
[EX A]: seq2seq model with global attention gives the best results with an average target BLEU score of 29.65

[EX Q]: Experimental results on public datasets show that our CRU model could substantially outperform various systems by a large margin, and set up new state-of-the-art performances on related datasets. 
 Question: Are there some results better than state of the art on these tasks?
[EX A]:
Yes