Linguistically Conditioned Semantic Textual Similarity

doi:doi:10.57702/w30y94lu

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.

BibTex:

@dataset{Jingxuan_Tu_and_Keer_Xu_and_Liulu_Yue_and_Bingyang_Ye_and_Kyeongmin_Rim_and_James_Pustejovsky_2025,
    abstract = {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.},
    author = {Jingxuan Tu and Keer Xu and Liulu Yue and Bingyang Ye and Kyeongmin Rim and James Pustejovsky},
    doi = {10.57702/w30y94lu},
    institution = {No Organization},
    keyword = {'conditional', 'linguistically', 'semantic', 'similarity', 'textual'},
    month = {jan},
    publisher = {TIB},
    title = {Linguistically Conditioned Semantic Textual Similarity},
    url = {https://service.tib.eu/ldmservice/dataset/linguistically-conditioned-semantic-textual-similarity},
    year = {2025}
}