instruction:
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.
question:
The dataset consists of 198,112 news articles. 
 Question: How many articles did they have?
answer:
198,112


question:
The input document/summary that may have unordered sentences is processed so that it will have sentences clustered together. To test our approach, we jumble the ordering of sentences in a document, process the unordered document and compare the similarity of the output document with the original document. To structure an unordered document is an essential task in many applications. It is a post-requisite for applications like multiple document extractive text summarization where we have to present a summary of multiple documents. It is a prerequisite for applications like question answering from multiple documents where we have to present an answer by processing multiple documents. 
 Question: What is an unordered text document, do these arise in real-world corpora?
answer:
A unordered text document is one where sentences in the document are disordered or jumbled. It doesn't appear that unordered text documents appear in corpora, but rather are introduced as part of processing pipeline.


question:
In the first one, shown in Figure FIGREF12, a special dedicated discriminator is added to the model to control that the latent representation does not contain stylistic information. The second extension of the baseline architecture does not use an adversarial component $D_z$ that is trying to eradicate information on $c$ from component $z$. Instead, the system, shown in Figure FIGREF16 feeds the "soft" generated sentence $\tilde{G}$ into encoder $E$ and checks how close is the representation $E(\tilde{G} )$ to the original representation $z = E(x)$ in terms of the cosine distance. We further refer to it as shifted autoencoder or SAE. We also study a combination of both approaches described above, shown on Figure FIGREF17. 
 Question: What are three new proposed architectures?
answer:

special dedicated discriminator is added to the model to control that the latent representation does not contain stylistic information shifted autoencoder or SAE combination of both approaches