TASK DEFINITION: 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.
PROBLEM: Our Pointer-Gen+ARL-SEN model achieves the best performance of 60.8%. This is an absolute improvement of 18.2% over the Pointer-Gen baseline.
Question: What is this method improvement over the best performing state-of-the-art?

SOLUTION: absolute improvement of 18.2% over the Pointer-Gen baseline

PROBLEM: We use the unshuffled version of the French OSCAR corpus, which amounts to 138GB of uncompressed text and 32.7B SentencePiece tokens.
Question: What data is used for training CamemBERT?

SOLUTION: unshuffled version of the French OSCAR corpus

PROBLEM: Causal documents were chosen to contain one occurrence only of the exact unigrams: 'caused', 'causing', or 'causes'.
Question: What are the selection criteria for "causal statements"?

SOLUTION:
Presence of only the exact unigrams 'caused', 'causing', or 'causes'