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Understanding the meaning of text by composing the meanings of the individual words in the text (Source: https://arxiv.org/pdf/1405.7908.pdf)

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Greatest papers with code

The Lifted Matrix-Space Model for Semantic Composition

CONLL 2018 NYU-MLL/spinn

Tree-structured neural network architectures for sentence encoding draw inspiration from the approach to semantic composition generally seen in formal linguistics, and have shown empirical improvements over comparable sequence models by doing so.

SEMANTIC COMPOSITION WORD EMBEDDINGS

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data

9 Dec 2020Shaoli-Huang/SnapMix

As the main discriminative information of a fine-grained image usually resides in subtle regions, methods along this line are prone to heavy label noise in fine-grained recognition.

FINE-GRAINED IMAGE CLASSIFICATION SEMANTIC COMPOSITION

Semantic Compositional Networks for Visual Captioning

CVPR 2017 zhegan27/Semantic_Compositional_Nets

The degree to which each member of the ensemble is used to generate an image caption is tied to the image-dependent probability of the corresponding tag.

IMAGE CAPTIONING SEMANTIC COMPOSITION

A Semantically Compositional Annotation Scheme for Time Normalization

LREC 2016 bethard/timenorm

We present a new annotation scheme for normalizing time expressions, such as {``}three days ago{''}, to computer-readable forms, such as 2016-03-07.

SEMANTIC COMPOSITION

Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction

COLING 2016 pgcool/TF-MTRNN

This paper proposes a novel context-aware joint entity and word-level relation extraction approach through semantic composition of words, introducing a Table Filling Multi-Task Recurrent Neural Network (TF-MTRNN) model that reduces the entity recognition and relation classification tasks to a table-filling problem and models their interdependencies.

ENTITY EXTRACTION USING GAN JOINT ENTITY AND RELATION EXTRACTION RELATION CLASSIFICATION SEMANTIC COMPOSITION STRUCTURED PREDICTION

Improving Semantic Composition with Offset Inference

ACL 2017 tttthomasssss/acl2017

Count-based distributional semantic models suffer from sparsity due to unobserved but plausible co-occurrences in any text collection.

SEMANTIC COMPOSITION