Papers with easy-to-hard order

1 papers
Uncertainty-Aware Curriculum Learning for Neural Machine Translation (2020.acl-main)

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Challenge: Neural machine translation (NMT) has proven to be facilitated by curriculum learning which presents examples in an easy-to-hard order at different training stages.
Approach: They propose to use an uncertainty-aware curriculum learning approach to assess data difficulty and model competence to provide examples in an easy-to-hard order at different training stages.
Outcome: The proposed approach outperforms baseline and related methods on translation quality and convergence speed.

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