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Linguistically Conditioned Semantic Textual Similarity

Semantic textual similarity (STS) is a fundamental NLP task that measures the semantic similarity between a pair of sentences. In order to reduce the inherent ambiguity posed from the sentences, a recent work called Conditional STS (C-STS) has been proposed to measure the sentences' similarity conditioned on a certain aspect. Despite the popularity of C-STS, we find that the current C-STS dataset suffers from various issues that could impede proper evaluation on this task.

Data and Resources

Cite this as

Jingxuan Tu, Keer Xu, Liulu Yue, Bingyang Ye, Kyeongmin Rim, James Pustejovsky (2025). Dataset: Linguistically Conditioned Semantic Textual Similarity. https://doi.org/10.57702/w30y94lu

DOI retrieved: January 2, 2025

Additional Info

Field Value
Created January 2, 2025
Last update January 2, 2025
Defined In https://doi.org/10.48550/arXiv.2406.03673
Author Jingxuan Tu
More Authors
Keer Xu
Liulu Yue
Bingyang Ye
Kyeongmin Rim
James Pustejovsky
Homepage https://github.com/brandeis-llc/L-CSTS