Papers with attention-based contrastive adaptation

1 papers
QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive Adaptation (2022.emnlp-main)

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Challenge: Question answering models often suffer from performance deterioration upon deployment .
Approach: They propose a self-supervised framework called QADA for QA domain adaptation . they propose to augment training QA samples with hidden space augmentation .
Outcome: The proposed framework improves on multiple target datasets over state-of-the-art methods.

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