Less is More: The Effectiveness of Compact Typological Language Representations

Fuente: arXiv
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Main Authors: Ng, York Hay, Hoang, Phuong Hanh, Lee, En-Shiun Annie
Format: Preprint
Published: 2025
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author Ng, York Hay
Hoang, Phuong Hanh
Lee, En-Shiun Annie
author_facet Ng, York Hay
Hoang, Phuong Hanh
Lee, En-Shiun Annie
contents Linguistic feature datasets such as URIEL+ are valuable for modelling cross-lingual relationships, but their high dimensionality and sparsity, especially for low-resource languages, limit the effectiveness of distance metrics. We propose a pipeline to optimize the URIEL+ typological feature space by combining feature selection and imputation, producing compact yet interpretable typological representations. We evaluate these feature subsets on linguistic distance alignment and downstream tasks, demonstrating that reduced-size representations of language typology can yield more informative distance metrics and improve performance in multilingual NLP applications.
format Preprint
id arxiv_https___arxiv_org_abs_2509_20129
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Less is More: The Effectiveness of Compact Typological Language Representations
Ng, York Hay
Hoang, Phuong Hanh
Lee, En-Shiun Annie
Computation and Language
Linguistic feature datasets such as URIEL+ are valuable for modelling cross-lingual relationships, but their high dimensionality and sparsity, especially for low-resource languages, limit the effectiveness of distance metrics. We propose a pipeline to optimize the URIEL+ typological feature space by combining feature selection and imputation, producing compact yet interpretable typological representations. We evaluate these feature subsets on linguistic distance alignment and downstream tasks, demonstrating that reduced-size representations of language typology can yield more informative distance metrics and improve performance in multilingual NLP applications.
title Less is More: The Effectiveness of Compact Typological Language Representations
topic Computation and Language
url https://arxiv.org/abs/2509.20129