A structurally specific irregular verb subclass under 1% of Japanese past-tense data drives disproportionate errors in neural morphology models, with ablation showing its removal aids generalization more than removing all irregulars.
InProceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5117–5126, Florence, Italy
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When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphology
A structurally specific irregular verb subclass under 1% of Japanese past-tense data drives disproportionate errors in neural morphology models, with ablation showing its removal aids generalization more than removing all irregulars.