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.

The experimental results are shown in Table 1, where it can be seen that autoencoders outperformed MLP and CNN outperformed autoencoders with the highest achieved accuracy of 82.6%.
Question: What was their performance on the dataset?
accuracy of 82.6%

Non-contextual properties of a word. These features are derived directly from the word and capture the general tendency of a word being echoed in explanations.
Question: What non-contextual properties do they refer to?
These features are derived directly from the word and capture the general tendency of a word being echoed in explanations.

Next, for emergent language, we show that the MASC architecture can achieve very high localization accuracy, significantly outperforming the baseline that does not include this mechanism.
Question: What evaluation metrics did the authors look at?
localization accuracy