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.

[Q]: We introduce our proposed diversity, density, and homogeneity metrics with their detailed formulations and key intuitions. 
 Question: Did they propose other metrics?
[A]: Yes


[Q]: In Table TABREF1, we summarize the quantitative results of the above previous studies. In Table TABREF1, we summarize the quantitative results of the above previous studies. 
 Question: What is the accuracy reported by state-of-the-art methods?
[A]: Answer with content missing: (Table 1)
Previous state-of-the art on same dataset: ResNet50 89% (6 languages), SVM-HMM 70% (4 languages)


[Q]: For each variable in encoding set, learn the new embeddings using the embeddings train set . Since there is stochasticity in the embeddings training model, we will repeat the above multiple times, for the different experiments in the paper (and report the respective mean and standard deviation statistics). 
 Question: How do their train their embeddings?
[A]:
The embeddings are learned several times using the training set, then the average is taken.