TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: The two main data sets that we will use to evaluate our architecture are the 2014 i2b2 de-identification challenge data set BIBREF2 and the nursing notes corpus BIBREF3 .

SOLUTION: Which two datasets is the system tested on?

PROBLEM: Thus, SIM has many fewer parameters than existing dialogue state tracking models. To compensate for the exclusion of slot-specific parameters, we incorporate better feature representation of user utterance and dialogue states using syntactic information and convolutional neural networks (CNN). 

SOLUTION: How do they prevent the model complexity increasing with the increased number of slots?

PROBLEM: Similar equations were discovered using Euclidean distance computed between the context vector representations of the equations ( INLINEFORM2 ). We give additional example results in Appendix B.

SOLUTION:
How do they define similar equations?