Papers with word swapping

1 papers
Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation (2022.emnlp-main)

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Challenge: Existing models for text generation are weak enough to handle perturbations in inputs, leading to degeneration in faithfulness and informativeness.
Approach: They propose a framework for improving faithfulness and informativeness of Seq2Seq models by perturbing word representations and word swapping.
Outcome: The proposed framework improves faithfulness and informativeness of Seq2Seq models under automatic and human evaluation settings.

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