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 Q]: (2) Different from LEM and DPEMM, AEM uses a generator network to capture the event-related patterns and is able to mine events from different text sources (short and long). Moreover, unlike traditional inference procedure, such as Gibbs sampling used in LEM and DPEMM, AEM could extract the events more efficiently due to the CUDA acceleration; 
 Question: What alternative to Gibbs sampling is used?
[EX A]: generator network to capture the event-related patterns

[EX Q]: We create a new manually annotated multimodal hate speech dataset formed by $150,000$ tweets, each one of them containing text and an image. We call the dataset MMHS150K, and made it available online . In this section, we explain the dataset creation steps. 
 Question: How many tweats does MMHS150k contains, 150000?
[EX A]: $150,000$ tweets

[EX Q]: For the sake of interpretability, we will also project back coefficients from the embeddings as well as PCA models into the dummy variable space. 
 Question: How do their interpret the coefficients?
[EX A]:
The coefficients are projected back to the dummy variable space.