Corpus ID: 211076210

Adversarial Filters of Dataset Biases

@inproceedings{Bras2020AdversarialFO,
  title={Adversarial Filters of Dataset Biases},
  author={Ronan Le Bras and Swabha Swayamdipta and Chandra Bhagavatula and Rowan Zellers and Matthew E. Peters and A. Sabharwal and Yejin Choi},
  booktitle={ICML},
  year={2020}
}

Ronan Le Bras, Swabha Swayamdipta, +4 authors Yejin Choi

Published in ICML 2020

Computer Science, Mathematics

Large neural models have demonstrated human-level performance on language and vision benchmarks, while their performance degrades considerably on adversarial or out-of-distribution samples. This raises the question of whether these models have learned to solve a dataset rather than the underlying task by overfitting to spurious dataset biases. We investigate one recently proposed approach, AFLite, which adversarially filters such dataset biases, as a means to mitigate the prevalent… CONTINUE READING

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