The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …

The birthdate of both generative linguistics and neural networks can be taken as 1957, the
year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt …

This study addresses a series of methodological questions that arise when modeling
inflectional morphology with Linear Discriminative Learning. Taking the semi-productive …

Inflectional morphology has since long been a useful testing ground for broader questions
about generalisation in language and the viability of neural network models as cognitive …

The staggering pace with which the capabilities of large language models (LLMs) are
increasing, as measured by a range of commonly used natural language understanding …

In the domain of Morphology, Inflection is a fundamental and important task that gained a lot
of traction in recent years, mostly via SIGMORPHON's shared-tasks. With average accuracy …

Only a fraction of lexemes are encountered in all their paradigm forms in any corpus or even
in the lifetime of any speaker. This raises a question as to how it is that native speakers …

Abstract The Paradigm Cell Filling Problem in morphology asks to complete word inflection
tables from partial ones. We implement novel neural models for this task, evaluating them on …

Dans les systèmes flexionnels, il arrive que des propriétés morphosyntaxiques soient
exprimées différemment d'un lexème à l'autre. Pour décrire ces systèmes, il est usuel …

This paper presents VeLeRo, an inflected lexicon of Standard Romanian which contains the
full paradigm of 7297 verbs in phonological form. We explain the process by which the …