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This paper probes character-level transformers to investigate whether they encode the Spanish L-shaped morphome, an irregular morphological pattern, as an abstract class or just surface alternations. The authors find that the encoding is item-specific and localized, but does not generalize like human learners.
Introduces MORFES, a benchmark of 500 expert-verified items for testing productive inflectional competence in Modern Greek, and evaluates open language models including their own Sophea-Genesis-1, which leads on inflectional morphology.
本文提出Morpheus,一种面向土耳其语的神经分词器与词嵌入器,它在无需字符串归一化的情况下学习语素边界,实现了无损分词并在词汇检索中获得了具有竞争力的嵌入表示,同时比子词分词器使用更少的GPU内存。
介绍PACUTE,一个包含4600项任务的诊断基准,用于评估菲律宾语的形态理解能力。结果显示,即使是前沿模型在语素分解和能产性形态组合方面仍存在困难。
提出了一种新颖的词根与模式模型来描述阿拉伯语名词的屈折形态,重点关注破碎复数,包含160个类别的分类法以及应用于3200个词条的编码方案,旨在改进计算语言资源。
本文研究了字符级Transformer模型如何泛化到日语过去时屈折中的不规则动词子类型。控制实验表明,包含不规则示例可以改善泛化,挑战了规则性简化学习的假设。