Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Myeongho Jeong"'
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:10526-10534
Despite the super-human accuracy of recent deep models in NLP tasks, their robustness is reportedly limited due to their reliance on spurious patterns. We thus aim to leverage contrastive learning and counterfactual augmentation for robustness. For a
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 29:2541-2550
This paper studies the dialogue response selection task. As state-of-the-arts are neural models requiring a large training set, data augmentation has been considered as a means to overcome the sparsity of observational annotation, where only one obse
Publikováno v:
CIKM
Classification datasets are often biased in observations, leaving onlya few observations for minority classes. Our key contribution is de-tecting and reducing Under-represented (U-) and Over-represented(O-) artifacts from dataset imbalance, by propos
Publikováno v:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
Publikováno v:
INTERSPEECH
Publikováno v:
Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing.