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:
word embedding, input encoder, alignment, aggregation, and prediction
Question: what is the architecture of the baseline model?

Ex Output:
word embedding, input encoder, alignment, aggregation, and prediction.

Ex Input:
Our model contains five independent decoders, one for each image in the sequence. This allows each decoder to learn a specific language model for each position of the sequence.
Question: Do the decoder LSTMs all have the same weights?

Ex Output:
No

Ex Input:
Then we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0 We note that the similarity metric defined above for sentences is equally applicable for n-gram retrieval.
Question: Which similarity measure do they use in their n-gram retrieval approach?

Ex Output:
we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0