Semantic Composition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

21 shown of 21 papers with code (110 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models
  8 Nov 2019 3 repositories listed
  Human and metrics evaluation on both LSTM models and BERT Transformer models on multiple datasets show that our algorithms outperform prior hierarchical explanation algorithms.
• SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data
  9 Dec 2020 2 repositories listed
  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.
• SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics
  8 May 2020 2 repositories listed
  We propose SentiBERT, a variant of BERT that effectively captures compositional sentiment semantics.
• The Lifted Matrix-Space Model for Semantic Composition
  9 Nov 2017 2 repositories listed
  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…
• Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference
  11 Jul 2023 1 repository listed
  To this end, we modify the original texts using a set of phrases - modifiers that correspond to universal quantifiers, existential quantifiers, negation, and other concept modifiers in Natural Logic (NL) (MacCartney,…
• Semantic Composition with PSHRG for Derivation Tree Reconstruction from Graph-Based Meaning Representations
  1 May 2022 1 repository listed
  We introduce a data-driven approach to generating derivation trees from meaning representation graphs with probabilistic synchronous hyperedge replacement grammar (PSHRG).
• Semantic Prediction: Which One Should Come First, Recognition or Prediction?
  6 Oct 2021 1 repository listed
  The ultimate goal of video prediction is not forecasting future pixel-values given some previous frames.
• Ontology-guided Semantic Composition for Zero-Shot Learning
  30 Jun 2020 1 repository listed
  Zero-shot learning (ZSL) is a popular research problem that aims at predicting for those classes that have never appeared in the training stage by utilizing the inter-class relationship with some side information.
• Autoencoding Pixies: Amortised Variational Inference with Graph Convolutions for Functional Distributional Semantics
  6 May 2020 1 repository listed
  Functional Distributional Semantics provides a linguistically interpretable framework for distributional semantics, by representing the meaning of a word as a function (a binary classifier), instead of a vector.
• No Word is an Island -- A Transformation Weighting Model for Semantic Composition
  11 Jul 2019 1 repository listed
  Composition models of distributional semantics are used to construct phrase representations from the representations of their words.
• Semantic Hilbert Space for Text Representation Learning
  26 Feb 2019 1 repository listed
  To address this issue, we propose a new framework that models different levels of semantic units (e.
• A Survey on Deep Learning for Named Entity Recognition
  22 Dec 2018 1 repository listed
  In this paper, we provide a comprehensive review on existing deep learning techniques for NER.
• From Characters to Time Intervals: New Paradigms for Evaluation and Neural Parsing of Time Normalizations
  1 Jan 2018 1 repository listed
  This paper presents the first model for time normalization trained on the SCATE corpus.
• Improving Semantic Composition with Offset Inference
  21 Apr 2017 1 repository listed
  Count-based distributional semantic models suffer from sparsity due to unobserved but plausible co-occurrences in any text collection.
• Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction
  1 Dec 2016 1 repository listed
  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…
• Semantic Compositional Networks for Visual Captioning
  23 Nov 2016 1 repository listed
  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.
• Improving Sparse Word Representations with Distributional Inference for Semantic Composition
  24 Aug 2016 1 repository listed
  Distributional models are derived from co-occurrences in a corpus, where only a small proportion of all possible plausible co-occurrences will be observed.
• A Semantically Compositional Annotation Scheme for Time Normalization
  1 May 2016 1 repository listed
  We present a new annotation scheme for normalizing time expressions, such as {``}three days ago{''}, to computer-readable forms, such as 2016-03-07.
• Higher-order logical inference with compositional semantics
  1 Sep 2015 1 repository listed
• Modeling Relation Paths for Representation Learning of Knowledge Bases
  1 Jun 2015 1 repository listed
  Representation learning of knowledge bases (KBs) aims to embed both entities and relations into a low-dimensional space.
• Domain and Function: A Dual-Space Model of Semantic Relations and Compositions
  16 Sep 2013 1 repository listed
  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…