Papers with morphological models

2 papers
Morphological Inflection with Phonological Features (2023.acl-short)

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Challenge: Recent advances in morphological tasks can be difficult to solve when little training data is available or when generalizing to previously unseen lemmas.
Approach: They propose two methods to manipulate phonemic data to include phonological features instead of characters.
Outcome: The proposed methods yield comparable results to baseline models, with minor improvements in some languages.
Probing Subphonemes in Morphology Models (2025.findings-acl)

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Challenge: morphological inflection models have achieved state-of-the-art performance, yet their ability to generalize across languages and morphology rules remains limited.
Approach: They propose a language-agnostic probing method to investigate phonological feature encoding in transformers trained directly on phonemes and perform it across seven morphologically diverse languages.
Outcome: The proposed method shows that phonological features which are local are captured well in phoneme embeddings, whereas long-distance dependencies like vowel harmony are better represented in the transformer’s encoder.

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