Papers by Dusan Varis

3 papers
Sequence Length is a Domain: Length-based Overfitting in Transformer Models (2021.emnlp-main)

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Challenge: Current Transformer-based sequence-to-sequence architectures can suffer from overfitting during training.
Approach: They propose to use Transformer-based sequence-to-sequence architectures to overcome overfitting problems when generating very long sequences.
Outcome: The proposed model performs worse on very long sequences than previous approaches on string editing and translation tasks when faced with sequences of length diverging from the length distribution in training data.
End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages (2021.acl-long)

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Challenge: Existing approaches to enforce word forms in translations struggle to make them agree with the rest of the output.
Approach: They propose to train neural machine translation models with lemmatized constraints to infer correct word inflection.
Outcome: The proposed model reduces errors in translation of constrained terms in automatic and manual evaluations on English-Czech language pairs.

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