Papers with eQASC

1 papers
Learning to Explain: Datasets and Models for Identifying Valid Reasoning Chains in Multihop Question-Answering (2020.emnlp-main)

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Challenge: despite rapid progress in multihop question-answering, models still have trouble explaining why an answer is correct.
Approach: They propose three explanation datasets in which explanations from corpus facts are annotated . they first annotate multiple candidate explanations for each answer, then use crowd-sourcing perturbations to test generalization .
Outcome: The proposed datasets improve explanation quality but still behind the upper bound . the proposed dataset can be used to improve explanations using a BERT-based classifier .

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