Papers with SIGMORPHON

2 papers
Can a Transformer Pass the Wug Test? Tuning Copying Bias in Neural Morphological Inflection Models (2022.acl-short)

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Challenge: morphological inflection models have been successful with shared tasks . but they fail at generalizing inflation patterns when trained on a limited number of lemmata .
Approach: They find that standard models fail at generalizing inflection patterns when trained on a limited number of lemmata and asked to inflect previously unseen lemma.
Outcome: The proposed model can perform well on morphological inflection tasks if training data covers a diversity of lemmata or some variant of the input lemma has been witnessed during training.
(Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models’ Performance (2022.acl-short)

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Challenge: Inflection tasks have gained a lot of traction in recent years, mostly via SIGMORPHON's shared-tasks.
Approach: They propose to use split-by-lemma to challenge the generalization capacity of morphological inflection models by employing harder train-test splits.
Outcome: The proposed method is based on a split-by-lemma method that challenges the generalization capacity of the models.

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