mlsanityData to 14 Oct 2026

MasonTigers at SemEval-2024 Task 1: An Ensemble Approach for Semantic Textual Relatedness

arXiv 2403.14990 ↗First posted 22 Mar 2024cs.CLcited by 1

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Abstract (arXiv)

This paper presents the MasonTigers entry to the SemEval-2024 Task 1 - Semantic Textual Relatedness. The task encompasses supervised (Track A), unsupervised (Track B), and cross-lingual (Track C) approaches across 14 different languages. MasonTigers stands out as one of the two teams who participated in all languages across the three tracks. Our approaches achieved rankings ranging from 11th to 21st in Track A, from 1st to 8th in Track B, and from 5th to 12th in Track C. Adhering to the task-specific constraints, our best performing approaches utilize ensemble of statistical machine learning approaches combined with language-specific BERT based models and sentence transformers.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 47 references that are in the map. First posted on arXiv 22 Mar 2024.

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17 of 47 references.

References · 17

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5 more
  1. 2021DziriBERT: a Pre-trained Language Model for the Algerian Dialectcited by 18
  2. 2024SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languagescited by 16
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Citing papers per year: 2024: 1.

1 paper.

  1. 2024SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languagescited by 7