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.

Ex Input:
Various multilingual extensions of NMT have already been proposed in the literature. The authors of BIBREF18 , BIBREF19 apply multitask learning to train models for multiple languages. Zoph and Knight BIBREF20 propose a multi-source model and BIBREF21 introduces a character-level encoder that is shared across several source languages. In our setup, we will follow the main idea proposed by Johnson et al. BIBREF22 . The authors of that paper suggest a simple addition by means of a language flag on the source language side (see Figure 2 ) to indicate the target language that needs to be produced by the decoder. This flag will be mapped on a dense vector representation and can be used to trigger the generation of the selected language. The authors of the paper argue that the model enables transfer learning and supports the translation between languages that are not explicitly available in training. 
 Question: What neural machine translation models can learn in terms of transfer learning?

Ex Output:
Multilingual Neural Machine Translation Models


Ex Input:
Unlike the SQuAD dataset, which only has one passage given a question, there are several related passages for each question in the MS-MARCO dataset. In addition to annotating the answer, MS-MARCO also annotates which passage is correct.  
 Question: Why MS-MARCO is different from SQuAD?

Ex Output:
there are several related passages for each question in the MS-MARCO dataset. MS-MARCO also annotates which passage is correct


Ex Input:
We segment a hashtag into meaningful English phrases. In order to achieve this, we use a dictionary of English words. The sentiment of url: Since almost all the articles are written in well-formatted english, we analyze the sentiment of the first paragraph of the article using Standford Sentiment Analysis tool BIBREF4 .  
 Question: Do the authors report only on English language data?

Ex Output:

Yes