Papers with data augmentation protocol

2 papers
Exploring Text Recombination for Automatic Narrative Level Detection (2022.lrec-1)

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Challenge: Existing annotation workflows do not scale well to the annotation of complex narrative phenomena.
Approach: They propose a workflow for narrative level detection that includes operationalization and a model . they propose generating training data synthetically to improve the prediction results .
Outcome: The proposed workflow improves predictions by using training data synthetically.
Good-Enough Example Extrapolation (2021.emnlp-main)

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Challenge: GE3 is a data augmentation protocol that can be used to increase text examples from one class onto another.
Approach: They propose a data augmentation protocol that extrapolates the hidden space distribution of text examples from one class onto another to investigate whether this bias is valid for data augmented.
Outcome: The proposed protocol improves on three text classification datasets for various data imbalance scenarios.

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