instruction:
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.
question:
We evaluate our approach for six target languages: French (fr), Russian (ru), Arabic (ar), Chinese (zh), Hindi (hi), and Vietnamese (vi).
Question: What languages are the model transferred to?
answer:
French (fr), Russian (ru), Arabic (ar), Chinese (zh), Hindi (hi), and Vietnamese (vi)

question:
Building on these results, we take a somewhat more systematic approach to looking for interpretable hidden state dimensions, by using decision trees to predict individual hidden state dimensions (Figure 2 ). We visualize the overall dynamics of the hidden states by coloring the training data with the k-means clusters on the state vectors (Figures 3 , 3 ). In Figures 3 and 3 , we color-code the training data with the 10 HMM states. In Figures 3 and 3 , we apply k-means clustering to the LSTM state vectors, and color-code the training data with the clusters.
Question: Which methods do the authors use to reach the conclusion that LSTMs and HMMs learn complementary information?
answer:
decision trees to predict individual hidden state dimensions apply k-means clustering to the LSTM state vectors, and color-code the training data with the clusters

question:
INSIGHT 1: Political handles are more likely to engage in profile changing behavior as compared to their followers. We analyze the trends in Figure FIGREF12 and find that the political handles do not change their usernames at all. This is in contrast to the trend in Figure FIGREF15 where we see that there are a lot of handles that change their usernames multiple times. INSIGHT 3: Political handles tend to make new changes related to previous attribute values. However, the followers make comparatively less related changes to previous attribute values.
Question: How do profile changes vary for influential leads and their followers over the social movement?
answer:
Influential leaders are more likely to change their profile attributes than their followers; the leaders do not change their usernames, while their followers change their usernames a lot; the leaders tend to make new changes related to previous attribute values, while the followers make comparatively less related changes to previous attribute values.