The SIGMORPHON 2019 shared task: Morphological analysis in context and cross-lingual transfer for inflection

AD McCarthy, E Vylomova, S Wu, C Malaviya… - arxiv preprint arxiv …, 2019‏ - arxiv.org
The SIGMORPHON 2019 shared task on cross-lingual transfer and contextual analysis in
morphology examined transfer learning of inflection between 100 language pairs, as well as …

Applying the transformer to character-level transduction

S Wu, R Cotterell, M Hulden - arxiv preprint arxiv:2005.10213, 2020‏ - arxiv.org
The transformer has been shown to outperform recurrent neural network-based sequence-to-
sequence models in various word-level NLP tasks. Yet for character-level transduction tasks …

SIGMORPHON 2020 shared task 0: Typologically diverse morphological inflection

E Vylomova, J White, E Salesky, SJ Mielke… - arxiv preprint arxiv …, 2020‏ - arxiv.org
A broad goal in natural language processing (NLP) is to develop a system that has the
capacity to process any natural language. Most systems, however, are developed using data …

Inducing and using alignments for transition-based AMR parsing

A Drozdov, J Zhou, R Florian, A McCallum… - arxiv preprint arxiv …, 2022‏ - arxiv.org
Transition-based parsers for Abstract Meaning Representation (AMR) rely on node-to-word
alignments. These alignments are learned separately from parser training and require a …

A survey on syntactic processing techniques

X Zhang, R Mao, E Cambria - Artificial Intelligence Review, 2023‏ - Springer
Computational syntactic processing is a fundamental technique in natural language
processing. It normally serves as a pre-processing method to transform natural language …

Dialect-to-standard normalization: A large-scale multilingual evaluation

O Kuparinen, A Miletić, Y Scherrer - Findings of the Association for …, 2023‏ - aclanthology.org
Text normalization methods have been commonly applied to historical language or user-
generated content, but less often to dialectal transcriptions. In this paper, we introduce …

Benchmarking compositionality with formal languages

J Valvoda, N Saphra, J Rawski, A Williams… - arxiv preprint arxiv …, 2022‏ - arxiv.org
Recombining known primitive concepts into larger novel combinations is a quintessentially
human cognitive capability. Whether large neural models in NLP can acquire this ability …

Automatic interlinear glossing for under-resourced languages leveraging translations

X Zhao, S Ozaki, A Anastasopoulos… - Proceedings of the …, 2020‏ - aclanthology.org
Abstract Interlinear Glossed Text (IGT) is a widely used format for encoding linguistic
information in language documentation projects and scholarly papers. Manual production of …

Can a transformer pass the wug test? tuning copying bias in neural morphological inflection models

L Liu, M Hulden - arxiv preprint arxiv:2104.06483, 2021‏ - arxiv.org
Deep learning sequence models have been successfully applied to the task of
morphological inflection. The results of the SIGMORPHON shared tasks in the past several …

Morphological irregularity correlates with frequency

S Wu, R Cotterell, TJ O'Donnell - arxiv preprint arxiv:1906.11483, 2019‏ - arxiv.org
We present a study of morphological irregularity. Following recent work, we define an
information-theoretic measure of irregularity based on the predictability of forms in a …