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
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Polish CDSCorpus
Latest papers with no code
DiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation
Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and background, showing great importance in photograph.
Distributed Intelligent Integrated Sensing and Communications: The 6G-DISAC Approach
This paper introduces the concept of Distributed Intelligent integrated Sensing and Communications (DISAC), which expands the capabilities of Integrated Sensing and Communications (ISAC) towards distributed architectures.
Semantic Composition in Visually Grounded Language Models
What is sentence meaning and its ideal representation?
Syntax-guided Neural Module Distillation to Probe Compositionality in Sentence Embeddings
Past work probing compositionality in sentence embedding models faces issues determining the causal impact of implicit syntax representations.
Categorizing Semantic Representations for Neural Machine Translation
Modern neural machine translation (NMT) models have achieved competitive performance in standard benchmarks.
BOSS: Bottom-up Cross-modal Semantic Composition with Hybrid Counterfactual Training for Robust Content-based Image Retrieval
In this scenario, the input image serves as an intuitive context and background for the search, while the corresponding language expressly requests new traits on how specific characteristics of the query image should be modified in order to get the intended target image.
Modeling Semantic Composition with Syntactic Hypergraph for Video Question Answering
A key challenge in video question answering is how to realize the cross-modal semantic alignment between textual concepts and corresponding visual objects.
Design considerations for a hierarchical semantic compositional framework for medical natural language understanding
Medical natural language processing (NLP) systems are a key enabling technology for transforming Big Data from clinical report repositories to information used to support disease models and validate intervention methods.
MixSyn: Learning Composition and Style for Multi-Source Image Synthesis
Synthetic images created by generative models increase in quality and expressiveness as newer models utilize larger datasets and novel architectures.
A Well-Composed Text is Half Done! Semantic Composition Sampling for Diverse Conditional Generation
We propose Composition Sampling, a simple but effective method to generate higher quality diverse outputs for conditional generation tasks, compared to previous stochastic decoding strategies.
