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Preview of SemEval-2023 Task 4
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SemEval-2023 Task 4 (2023.semeval-1.31.pdf)

233 KBEN 9 pages
Researchers proposed a model that leverages definitions of human values to improve prediction of human values behind arguments, achieving up to 18% improvement...
Preview of IXAmed-semeval2014-final.pdf
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IXAmed-semeval2014-final.pdf (IXAmed-semeval2014-final.pdf)

109 KBEN 5 pages
IxaMed team participated in SemEval-2014 Shared Task 7 on Analyzing Clinical Texts, developing three systems: exact match, a general-purpose morphosyntactic...
Preview of NUIG-UNLP at SemEval-2016 Task 1: Soft Alignment and Deep Learning for Semantic Textual Similarity
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NUIG-UNLP at SemEval-2016 Task 1: Soft Alignment and Deep Learning for Semantic Textual Similarity (S16-1110.pdf)

475 KBJohn Philip McCrae ; Kartik Asooja ; Nitish Aggarwal ; Paul BuitelaarEN 6 pages
The paper introduces a multi-feature system for semantic text similarity, utilizing soft alignment and Explicit Semantic Analysis techniques, achieving top performance in 4 out of 5 datasets at SemEval-2016 Task 1.

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