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]: The summaries generated by our ILP-based approach were compared with the corresponding manual summaries using the ROUGE BIBREF22 unigram score.
Question: What evaluation metrics were used for the summarization task?
[A]: ROUGE BIBREF22 unigram score

[Q]: replacing this single GRU with two different components first component is a sentence reader second component is the input fusion layer
Question: What changes they did on input module?
[A]: For the DMN+, we propose replacing this single GRU with two different components. The first component is a sentence reader The second component is the input fusion layer

[Q]: Throughout all our experiments, we used BERT-Base BIBREF2 to provide the state-of-the-art contextualized modeling of the input text.

Semantic Retrieval: We treated the neural semantic retrieval at both the paragraph and sentence level as binary classification problems with models' parameters updated by minimizing binary cross entropy loss.
Question: How do they model the neural retrieval modules?
[A]:
BERT-Base BIBREF2 to provide the state-of-the-art contextualized modeling