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Learning Semantic Representations

4 papers with code · Methodology

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Multilingual Models for Compositional Distributed Semantics

ACL 2014 karlmoritz/bicvm

We present a novel technique for learning semantic representations, which extends the distributional hypothesis to multilingual data and joint-space embeddings.

CROSS-LINGUAL DOCUMENT CLASSIFICATION DOCUMENT CLASSIFICATION LEARNING SEMANTIC REPRESENTATIONS

Learning Semantic Representations for Novel Words: Leveraging Both Form and Context

9 Nov 2018timoschick/form-context-model

The general problem setting is that word embeddings are induced on an unlabeled training corpus and then a model is trained that embeds novel words into this induced embedding space.

LEARNING SEMANTIC REPRESENTATIONS WORD EMBEDDINGS

Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning

20 Jun 2019DeepLearnXMU/RRWEL

However, most neural collective EL methods depend entirely upon neural networks to automatically model the semantic dependencies between different EL decisions, which lack of the guidance from external knowledge.

ENTITY DISAMBIGUATION ENTITY LINKING LEARNING SEMANTIC REPRESENTATIONS

Learning semantic sentence representations from visually grounded language without lexical knowledge

27 Mar 2019DannyMerkx/caption2image

The system achieves state-of-the-art results on several of these benchmarks, which shows that a system trained solely on multimodal data, without assuming any word representations, is able to capture sentence level semantics.

LEARNING SEMANTIC REPRESENTATIONS SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY SENTENCE EMBEDDINGS WORD EMBEDDINGS