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.
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Question: We empirically test our approach on a series of experiments on WikiTableQuestions, to our knowledge the only dataset designed for this task. In Algorithm 1 we describe how logical forms are transformed into interpretable textual representations called "paraphrases".
Question: What is the source of the paraphrases of the questions?

Answer: WikiTableQuestions

Question: The corpus is freely available at the following link
Question: Is this dataset publicly available?

Answer: Yes

Question: Multimodal representation.
We combined textual and image representations in two simple ways. The first method is concatenation of the text and image representation (concat). Before concatenation we applied the L2 normalization to each of the modalities. The second method it to learn a common space for the two modalities before concatenation (project).

The projection of each modality learns a space of $d$-dimensions, so that $h_{1}, h_{2} \in \mathbb {R}^{d}$. Once the multimodal representation is produced ($h_{m}$) for the left and right pairs, vectors are directly plugged into the regression layers. Projections are learned end-to-end with the regression layers and the MSE as loss function.
Question: What multimodal representations are used in the experiments?

Answer:
The second method it to learn a common space for the two modalities before concatenation (project) The first method is concatenation of the text and image representation (concat)