Semantic Composition
20 papers with code • 0 benchmarks • 2 datasets
Understanding the meaning of text by composing the meanings of the individual words in the text (Source: https://arxiv.org/pdf/1405.7908.pdf)
Benchmarks
These leaderboards are used to track progress in Semantic Composition
Polish CDSCorpus
Most implemented papers
The Lifted Matrix-Space Model for Semantic Composition
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.
Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models
g8a9/ferret
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ICLR 2020
Human and metrics evaluation on both LSTM models and BERT Transformer models on multiple datasets show that our algorithms outperform prior hierarchical explanation algorithms.
SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics
WadeYin9712/SentiBERT
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ACL 2020
We propose SentiBERT, a variant of BERT that effectively captures compositional sentiment semantics.
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data
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.
Domain and Function: A Dual-Space Model of Semantic Relations and Compositions
Given appropriate representations of the semantic relations between carpenter and wood and between mason and stone (for example, vectors in a vector space model), a suitable algorithm should be able to recognize that these relations are highly similar (carpenter is to wood as mason is to stone; the relations are analogous).
Modeling Relation Paths for Representation Learning of Knowledge Bases
Representation learning of knowledge bases (KBs) aims to embed both entities and relations into a low-dimensional space.
A Semantically Compositional Annotation Scheme for Time Normalization
We present a new annotation scheme for normalizing time expressions, such as {``}three days ago{''}, to computer-readable forms, such as 2016-03-07.
Improving Sparse Word Representations with Distributional Inference for Semantic Composition
Distributional models are derived from co-occurrences in a corpus, where only a small proportion of all possible plausible co-occurrences will be observed.
Semantic Compositional Networks for Visual Captioning
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.
