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AbstractAdversarial learning can learn fairer and less biased models of language processing than standard training. However, current adversarial techniques only partially mitigate the problem of model bias, added to which …...

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AbstractCounterfactually Augmented Data (CAD) aims to improve out-of-domain generalizability, an indicator of model robustness. The improvement is credited to promoting core features of the construct over spurious artifacts that happen …...

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