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.

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

Example Input: As previous systems collect relevant data from knowledge bases after observing questions during evaluation BIBREF24 , BIBREF25 , we also explore using this option. Namely, we build a customized text corpus based on questions in commonsense reasoning tasks.  
 Question: Do they fine-tune their model on the end task?
Example Output: Yes

Example Input: We first use state-of-the-art PDTB taggers for our baseline BIBREF13 , BIBREF12 for the evaluation of the causality prediction of our models ( BIBREF12 requires sentences extracted from the text as its input, so we used our parser to extract sentences from the message). 
 Question: What baselines did they consider?
Example Output:
state-of-the-art PDTB taggers