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: To study the lexical and semantic diversities of responses, we performed three analyses. First, we aggregated all worker responses to a particular question into a single list corresponding to that question. Second, we compared the diversity of individual responses between Control and AUI for each question. To measure diversity for a question, we computed the number of responses divided by the number of unique responses to that question. We call this the response density.  
 Question: How was lexical diversity measured?

A: By computing number of unique responses and number of responses divided by the number of unique responses to that question for each of the questions
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Q: Although no perfect matches exist, we decided upon the Quora duplicate question dataset BIBREF22 as the best match. To study the embeddings, we computed the euclidean distance between the two questions using various embeddings, to study the distance between semantically similar and dissimilar questions. 
 Question: What existing corpus is used for comparison in these experiments?

A: Quora duplicate question dataset BIBREF22
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Q: More specifically, in our model we use the context of the word to predict its label and by doing so our model learns label-aware context for each word in the sentence. In order to improve the interactivity between the word representation and its context, we increase the mutual information between the word representations and its context. 
 Question: How does their model utilize contextual information for each work in the given sentence in a multi-task setting? setting?

A:
we use the context of the word to predict its label and by doing so our model learns label-aware context for each word in the sentence
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