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.

Input: Consider Input: While the performances of a purely content-based model naturally stays stable, the performance of the other systems decrease notably – they perform worse than the content-based model. 
 Question: How do they demonstrate the robustness of their results?

Output: performances of a purely content-based model naturally stays stable


Input: Consider Input: To tackle this issue, we investigate how to improve the generalization of BERT-based MCQA models with the constraint of limited training data using four representative MCQA datasets: DREAM, MCTest, TOEFL, and SemEval-2018 Task 11. 
 Question: What four representative datasets are used for bechmark?

Output: DREAM, MCTest, TOEFL, and SemEval-2018 Task 11


Input: Consider Input: Routines were developed to simulate input data based on the authors experience with real healthcare data. The reasons for this choice were twofold: One, healthcare data can be high in incidental complexity, requiring one-off code to handle unusual inputs, but not necessarily in such a way as to significantly alter the fundamental engineering choices in a semantic enrichment engine such as this one. Two, healthcare data is strictly regulated, and the process for obtaining access to healthcare data for research can be cumbersome and time-consuming.

A simplified set of input data, in a variety of different formats that occur frequently in a healthcare setting, was used for simulation. 
 Question: What type of simulations of real-time data feeds are used for validaton?


Output: simplified set of input data, in a variety of different formats that occur frequently in a healthcare setting