Papers with Paradigm Cell Filling Problem

3 papers
Minimal Supervision for Morphological Inflection (2021.emnlp-main)

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Challenge: Neural models for morphological reinflection tasks have proved to be extremely accurate given ample labeled data, yet labele d data may be slow and costly to obtain.
Approach: They exploit orthographic and semantic regularities in morphological systems to exploit the orthographic regularities on their own to achieve respectable accuracy.
Outcome: The bootstrapping method outperforms hallucination-based methods for morphological reinflection tasks.
Frequency matters: Modeling irregular morphological patterns in Spanish with Transformers (2025.findings-acl)

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Challenge: A common generation task in morphology is morphological inflection, where a target form has to be generated from its corresponding lemma and feature tag.
Approach: They propose to solve the Paradigm Cell Filling Problem (PCFP) by using encoder-decoder transformers to generate inflected verbs in Spanish.
Outcome: The proposed model performs better on L-shaped verbs than regular verbs, but no consistent recency effects are observed.
An Encoder-Decoder Approach to the Paradigm Cell Filling Problem (D18-1)

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Challenge: a Paradigm cell filling problem is a problem that asks how speakers of a language can reliably produce inflectional forms without ever witnessing them before.
Approach: They implement novel neural models for the Paradigm Cell Filling Problem in morphology . they evaluate models on 18 data sets in 8 languages and implement them in a new dataset .
Outcome: The proposed model performs comparable to previous work with less training data.

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