TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: On the same architecture, our RCRN outperforms ablative baselines BiLSTM by INLINEFORM2 and 3L-BiLSTM by INLINEFORM3 on average across 16 datasets.

SOLUTION: By how much do they outperform BiLSTMs in Sentiment Analysis?

PROBLEM: We incorporate typing information by concatenating to the embedding vector of each input symbol one of three embedding vectors, S, E or R, where S is concatenated to structural elements (opening and closing brackets), E to entity symbols and R to relation symbol

SOLUTION: How are typing hints suggested?

PROBLEM: We use the unshuffled version of the French OSCAR corpus, which amounts to 138GB of uncompressed text and 32.7B SentencePiece tokens.

SOLUTION:
What is CamemBERT trained on?