Browse State-of-the-Art › Morphological Inflection
Morphological Inflection
39 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
Morphological Inflection is the task of generating a target (inflected form) word from a source word (base form), given a morphological attribute, e.g. number, tense, and person etc. It is useful for alleviating data sparsity issues in translating morphologically rich languages. The transformation from a base form to an inflected form usually includes concatenating the base form with a prefix or a suffix and substituting some characters. For example, the inflected form of a Finnish stem eläkeikä (retirement age) is eläkeiittä when the case is abessive and the number is plural.
Source: Tackling Sequence to Sequence Mapping Problems with Neural Networks
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
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Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
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Most implemented papers archive 2025-07-28
30 shown of 39 papers with code (135 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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16 Aug 2019 4 repositories listedRecent years have seen exceptional strides in the task of automatic morphological inflection generation.
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20 May 2020 3 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 2 pointer-only (licence)The transformer has been shown to outperform recurrent neural network-based sequence-to-sequence models in various word-level NLP tasks.
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12 Feb 2023 2 repositories listedWe extend a current sequence-tagging approach to Grammatical Error Correction (GEC) by introducing specialised tags for spelling correction and morphological inflection using the SymSpell and LemmInflect algorithms.
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13 Oct 2021 2 repositories listed Syntology ran 2 of 6 samples · 4 unverified · 6 pointer-only (licence)Natural language processing (NLP) systems have become a central technology in communication, education, medicine, artificial intelligence, and many other domains of research and development.
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15 May 2019 2 repositories listedOur models achieve state-of-the-art performance on morphological inflection.
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10 Jun 2018 2 repositories listedStatistical morphological inflectors are typically trained on fully supervised, type-level data.
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22 Sep 2024 1 repository listedLinguistic fieldwork is an important component in language documentation and preservation.
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13 Apr 2024 1 repository listedFor testing in OOV conditions, we automatically extracted a large dataset of nouns in the morphologically rich Czech language, with lemma-disjoint data splits, and we further manually annotated a real-world OOV dataset…
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21 Jun 2023 1 repository listedRecent years have brought great advances into solving morphological tasks, mostly due to powerful neural models applied to various tasks as (re)inflection and analysis.
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26 May 2023 1 repository listedWe aim at closing this gap by investigating the types of noise encountered within a pipeline for truly unsupervised morphological paradigm completion and its impact on morphological inflection systems: First, we propose…
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25 May 2023 1 repository listedMorphological inflection is a popular task in sub-word NLP with both practical and cognitive applications.
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23 May 2023 1 repository listedIn this study, we aim to shed light on the theoretical aspects of the prominent data augmentation strategy StemCorrupt (Silfverberg et al., 2017; Anastasopoulos and Neubig, 2019), a method that generates synthetic…
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21 May 2023 1 repository listedTransformer-based encoder-decoder models that generate outputs in a left-to-right fashion have become standard for sequence-to-sequence tasks.
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26 Oct 2022 1 repository listedIn this paper, we explore four sampling strategies for the task of morphological inflection using a Transformer model: a pair of oracle experiments where data is chosen based on whether the model already can or cannot…
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1 Jul 2022 1 repository listedThis year’s iteration of the SIGMORPHONUniMorph shared task on “human-like” morphological inflection generation focuses on generalization and errors in language acquisition.
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1 Jul 2022 1 repository listedThe 2022 SIGMORPHON–UniMorph shared task on large scale morphological inflection generation included a wide range of typologically diverse languages: 33 languages from 11 top-level language families: Arabic (Modern…
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1 Jul 2022 1 repository listedWe report competitive results for morpheme segmentation (including sharing first place in part 2 of the challenge).
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1 May 2022 1 repository listedNatural language processing (NLP) systems have become a central technology in communication, education, medicine, artificial intelligence, and many other domains of research and development.
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10 Sep 2021 1 repository listedCurrent approaches to incorporating terminology constraints in machine translation (MT) typically assume that the constraint terms are provided in their correct morphological forms.
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12 Aug 2021 1 repository listedThe effect is most significant for low-resourced languages with a drop as high as 95 points, but even high-resourced languages lose about 10 points on average.
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1 Aug 2021 1 repository listedIn this work, we analyze the robustness of neural machine translation systems towards grammatical perturbations in the source.
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8 May 2021 1 repository listedWe evaluate the Transformer as a model of morphological rule learning and compare it with Recurrent Neural Networks (RNN) on English, German, and Russian.
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17 Apr 2021 1 repository listedNeural models for the various flavours of morphological inflection tasks have proven to be extremely accurate given ample labeled data -- data that may be slow and costly to obtain.
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8 Apr 2021 1 repository listedMany sequence-to-sequence tasks in natural language processing are roughly monotonic in the alignment between source and target sequence, and previous work has facilitated or enforced learning of monotonic attention…
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1 Apr 2021 1 repository listedWe apply our methodology to analyze the model{'}s decisions on three typologically-different languages and find that a) our pattern extraction method applied to cross-attention weights uncovers variation in form of…
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18 Mar 2021 1 repository listedCurrent sequence-to-sequence models are trained to minimize cross-entropy and use softmax to compute the locally normalized probabilities over target sequences.
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20 Jun 2020 1 repository listedSystems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages.
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1 May 2020 1 repository listedWe present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python.
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30 Apr 2020 1 repository listedInflectional variation is a common feature of World Englishes such as Colloquial Singapore English and African American Vernacular English.
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30 Oct 2019 1 repository listedTranslation into morphologically-rich languages challenges neural machine translation (NMT) models with extremely sparse vocabularies where atomic treatment of surface forms is unrealistic.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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