Knowledge graphs meet multi-modal learning: A comprehensive survey
Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal
Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
Zero-shot and few-shot learning with knowledge graphs: A comprehensive survey
Machine learning (ML), especially deep neural networks, has achieved great success, but
many of them often rely on a number of labeled samples for supervision. As sufficient …
many of them often rely on a number of labeled samples for supervision. As sufficient …
Ontology-enhanced Prompt-tuning for Few-shot Learning
Few-shot Learning (FSL) is aimed to make predictions based on a limited number of
samples. Structured data such as knowledge graphs and ontology libraries has been …
samples. Structured data such as knowledge graphs and ontology libraries has been …
Duet: Cross-modal semantic grounding for contrastive zero-shot learning
Zero-shot learning (ZSL) aims to predict unseen classes whose samples have never
appeared during training. One of the most effective and widely used semantic information for …
appeared during training. One of the most effective and widely used semantic information for …
Bi-directional distribution alignment for transductive zero-shot learning
It is well-known that zero-shot learning (ZSL) can suffer severely from the problem of domain
shift, where the true and learned data distributions for the unseen classes do not match …
shift, where the true and learned data distributions for the unseen classes do not match …
Meaformer: Multi-modal entity alignment transformer for meta modality hybrid
Multi-modal entity alignment (MMEA) aims to discover identical entities across different
knowledge graphs (KGs) whose entities are associated with relevant images. However …
knowledge graphs (KGs) whose entities are associated with relevant images. However …
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning
F Mumuni, A Mumuni - Cognitive Systems Research, 2024 - Elsevier
We review current and emerging knowledge-informed and brain-inspired cognitive systems
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
Knowledge-aware zero-shot learning: Survey and perspective
Zero-shot learning (ZSL) which aims at predicting classes that have never appeared during
the training using external knowledge (aka side information) has been widely investigated …
the training using external knowledge (aka side information) has been widely investigated …
Zero-shot visual question answering using knowledge graph
Incorporating external knowledge to Visual Question Answering (VQA) has become a vital
practical need. Existing methods mostly adopt pipeline approaches with different …
practical need. Existing methods mostly adopt pipeline approaches with different …