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Composition of Sentence Embeddings: Lessons from Statistical Relational Learning
2019
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*
Various NLP problems -such as the prediction of sentence similarity, entailment, and discourse relations -are all instances of the same general task: the modeling of semantic relations between a pair of textual elements. A popular model for such problems is to embed sentences into fixed size vectors, and use composition functions (e.g. concatenation or sum) of those vectors as features for the prediction. At the same time, composition of embeddings has been a main focus within the field of
doi:10.18653/v1/s19-1004
dblp:conf/starsem/SileoCPM19
fatcat:e5dtyzh3hfffvesvw42642w5iq