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: Our model contains five independent decoders, one for each image in the sequence. This allows each decoder to learn a specific language model for each position of the sequence. 
 Question: Do the decoder LSTMs all have the same weights?

Answer: No


Question: We used dataset, HEOT obtained from one of the past studies done by Mathur et al. where they annotated a set of cleaned tweets obtained from twitter for the conversations happening in Indian subcontinent. A labelled dataset for a corresponding english tweets were also obtained from a study conducted by Davidson et al. 
 Question: How is the dataset collected?

Answer: A labelled dataset for a corresponding english tweets were also obtained from a study conducted by Davidson et al HEOT obtained from one of the past studies done by Mathur et al


Question: Based on Euclidean distance between vector representations of visits we applied and compared two clustering algorithms: k-means and hierarchical clustering with Ward's method for merging clusters BIBREF23 . 
 Question: Which clustering technique do they use on partients' visits texts?

Answer:
k-means hierarchical clustering with Ward's method for merging clusters BIBREF23