Given the task definition and input, reply with output. 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.

Since the input of our method is textual data, we follow the approach of BIBREF15 and map the text into a fixed-size vector representation. To this end, we use word embeddings that were successfully applied in other domains. We follow BIBREF5 and use pre-trained GloVe word vectors BIBREF16 to initialize the embedding layer (also known as look-up table). Section SECREF18 discusses the embedding layer in more details.
Question: Which pretrained word vectors did they use?
pre-trained GloVe word vectors