Papers by Alastair Roberts

1 papers
Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension (2020.tacl-1)

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Challenge: Innovations in annotation methodologies have been a catalyst for Reading Comprehension (RC) datasets and models.
Approach: They propose to use a model-in-the-annotation-loop approach to train adversarial models in three different settings to explore reproducibility of the adversarial effect, transfer from data collected with varying model- in-the loop strengths, and generalization to data collected without a modeling model.
Outcome: The proposed approach achieves 39.9F1 on questions it cannot answer when trained on SQUAD, but lower than when trained using RoBERTa itself (41.0F1).

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