Papers with question answering approaches

1 papers
Question Generation and Answering for exploring Digital Humanities collections (2022.lrec-1)

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Challenge: Recent advances in representation learning of text have achieved impressive results on benchmark Natural Language Understanding (NLU) tasks.
Approach: They propose a question answering paradigm that uses a BART Transformer based generative model to generate question data.
Outcome: The proposed approach is validated on a new corpus of digitized archive collections of a French Social Science journal.

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