Papers with SCT dataset

2 papers
Tackling the Story Ending Biases in The Story Cloze Test (P18-2)

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Challenge: Story Cloze Test (SCT) is a recent framework for evaluating story comprehension and script learning.
Approach: They propose to use a crowdsourcing scheme to create a new SCT dataset to overcome some of the biases discovered in the original SCT.
Outcome: The proposed model performs better than the baselines on the SCT dataset, despite human-authorship biases.
A Corpus for Commonsense Inference in Story Cloze Test (2022.lrec-1)

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Challenge: Story Cloze Test (SOTA) models can achieve over 90% accuracy on predicting the last sentence, but high accuracy can be achieved by merely using surface-level features.
Approach: They constructed a human-labeled and human-verified commonsense knowledge inference dataset using data from 1871 stories and three human workers labeled each story.
Outcome: The proposed models can achieve 90% accuracy on predicting the last sentence, but they don't perform well on new and more challenging tasks.

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