Papers with automatic perturbation

1 papers
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA (2021.naacl-main)

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Challenge: Recent studies show that supervised models exploit data artifacts to achieve good test scores while their performance severely degrades on samples outside their training distribution.
Approach: They propose a method which automatically generates contrast sets for the visual question answering task by using a semantic input representation.
Outcome: The proposed method computes the answer of perturbed questions, thus reducing annotation cost and enabling thorough evaluation of models’ performance on various semantic aspects.

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