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Found 6 papers, 2 papers with code
Adaptor Grammars for Unsupervised Paradigm Clustering
This work describes the Edinburgh submission to the SIGMORPHON 2021 Shared Task 2 on unsupervised morphological paradigm clustering.
Conditioning, but on Which Distribution? Grammatical Gender in German Plural Inflection
Grammatical gender is a consistent and informative cue to the plural class of German nouns.
Generalising to German Plural Noun Classes, from the Perspective of a Recurrent Neural Network
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 models of language.
Differentiable Tree Operations Promote Compositional Generalization
To facilitate the learning of these symbolic sequences, we introduce a differentiable tree interpreter that compiles high-level symbolic tree operations into subsymbolic matrix operations on tensors.
Inflecting when there's no majority: Limitations of encoder-decoder neural networks as cognitive models for German plurals
Encoder-decoder models do generalize the most frequently produced plural class, but do not show human-like variability or 'regular' extension of these other plural markers.
Linked Data for Language-Learning Applications
The use of linked data within language-learning applications is an open research question.
