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- W2806017957 abstract "The semantic relations between two short texts can be defined in multiple ways. Yet, all the systems to date designed to capture such relations target one relation at a time. We propose a novel multi-label transfer learning approach to jointly learn the information provided by the multiple annotations, rather than treating them as separate tasks. Not only does this approach outperform the traditional multi-task learning approach, it also achieves state-of-the-art performance on the SICK Entailment task and all but one dimensions of the Human Activity Phrase dataset." @default.
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- W2806017957 date "2018-05-31" @default.
- W2806017957 modified "2023-09-24" @default.
- W2806017957 title "Multi-Label Transfer Learning for Semantic Similarity." @default.
- W2806017957 hasPublicationYear "2018" @default.
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