Lemmas Matter, But Not Like That: Predictors of Lemma-Based Generalization in Morphological Inflection (2025.findings-acl)
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| Challenge: | Recent work suggests that lemma overlap drives model performance on morphological inflection tasks, but the impact of lemmm overlap is debated. |
| Approach: | They propose a novel algorithm to investigate predictors of accuracy on seen and unseen lemmas by combining the number of lema in train with the number in train. |
| Outcome: | The proposed algorithm shows that the number of lemmas in train has a stronger effect on accuracy on unseen than seen lemmes. |
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