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: We conduct various experiments to illustrate the properties that are encouraged via different KL magnitudes. In particular, we revisit the interdependence between rate and distortion, and shed light on the impact of KL on the sharpness of the approximated posteriors. Then, through a set of qualitative and quantitative experiments for text generation, we demonstrate how certain generative behaviours could be imposed on VAEs via a range of maximum channel capacities. Finally, we run some experiments to find if any form of syntactic information is encoded in the latent space.

SOLUTION: What different properties of the posterior distribution are explored in the paper?

PROBLEM: We map each relation type $R(x,y)$ to at least one parametrized natural-language question $q_x$ whose answer is $y$ .

SOLUTION: How is the input triple translated to a slot-filling task?

PROBLEM: Secondly, we examine the effect of Washington Post on the views of the users. This is done by looking at the sentiments of the candidates (to predict winners) of a debate before and after the winners are announced by the experts in Washington Post. This way, we can see if Washington Post has had any effect on the sentiments of the users. One can see the winners suggested by the Washington Post in Table TABREF35.

SOLUTION:
How do you establish the ground truth of who won a debate?