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Found 7 papers, 1 papers with code
This is a BERT. Now there are several of them. Can they generalize to novel words?
This type of generalization is exhibited by humans, and is intimately related to morphology—humans are in many cases able to identify inflections of novel words in the appropriate context.
How to encode arbitrarily complex morphology in word embeddings, no corpus needed
In this paper, we present a straightforward technique for constructing interpretable word embeddings from morphologically analyzed examples (such as interlinear glosses) for all of the world’s languages.
Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages
Machine translation has seen rapid progress with the advent of Transformer-based models.
Morphology Matters: A Multilingual Language Modeling Analysis
We fill in missing typological data for several languages and consider corpus-based measures of morphological complexity in addition to expert-produced typological features.
Invertible Tree Embeddings using a Cryptographic Role Embedding Scheme
We present a novel method for embedding trees in a vector space based on Tensor-Product Representations (TPRs) which allows for inversion: the retrieval of the original tree structure and nodes from the vectorial embedding.
Neural Polysynthetic Language Modelling
In the literature, languages like Finnish or Turkish are held up as extreme examples of complexity that challenge common modelling assumptions.
