concept

multimodal data integration

Also known as: multimodal data, multimodal data types, multimodal unstructured data, multimodal data integration

Facts (18)

Sources

A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Springer Nov 4, 2024 2 facts

claimThe 'Synergized LLMs + KG' approach aims to create a unified framework where Large Language Models and Knowledge Graphs mutually enhance each other's capabilities by integrating multimodal data and techniques from both fields.

claimKnowledge graphs face the challenge of multi-modal integration, which involves combining different data types, such as text and images, into one knowledge graph.

How NATO can integrate AI to prevail in future algorithmic warfare atlanticcouncil.org Atlantic Council 4 days ago 2 facts

claimMultimodal data fusion and analytics are important for the transition to multidomain operations.

claimNATO political and military leaders intend to use advanced analytics combined with multimodal data from sensor networks to achieve consolidated multidomain situational awareness in real time.

Practices, opportunities and challenges in the fusion of knowledge ... frontiersin.org Frontiers 2 facts

claimMultimodal integration in knowledge graphs improves accuracy but consumes a significant amount of resources.

claimCurrent hybrid approaches for LLM-KG fusion suffer from three core limitations: they introduce semantic noise during context augmentation (Ayoola et al., 2022; Xin et al., 2024), they remain constrained by LLM training biases in candidate generation (Ding Y. et al., 2024), and they create new modality-specific dependencies in multimodal fusion (Liu Q. et al., 2024).

LLM-empowered knowledge graph construction: A survey - arXiv arxiv.org arXiv Oct 23, 2025 2 facts

claimFuture advances in prompt design, multimodal integration, and knowledge-grounded reasoning are identified as key requirements for realizing autonomous and explainable knowledge-centric AI systems.

claimFuture research on dynamic knowledge graphs for autonomous agents will focus on improving scalability, temporal coherence, and multimodal integration.

Neuro-insights: a systematic review of neuromarketing perspectives ... frontiersin.org Frontiers 2 facts

claimApplying deep learning models to multimodal data, including brain signals, eye-tracking, facial expressions, and physiological indicators, enables more accurate prediction of consumer purchasing decisions, preferences, and emotional reactions.

claimMultimodal data provides a more comprehensive representation of human cognition and emotion than isolated data sources.

LLM-Powered Knowledge Graphs for Enterprise Intelligence and ... arxiv.org arXiv Mar 11, 2025 2 facts

perspectiveThe authors plan to enrich the knowledge graph with multimodal data, including images and audio, to provide more comprehensive visual and auditory signals.

claimThe LLM-powered user-centric activity knowledge graph framework supports multimodal data integration, including textual, temporal, and behavioral data, to enable comprehensive reasoning, trend analysis, and advanced query capabilities.

The construction and refined extraction techniques of knowledge ... nature.com Nature Feb 10, 2026 1 fact

claimIntegrating domain triples as pseudo-text or combining multimodal data like sensor logs enhances model specialization and cross-modal understanding.

Integrating allostasis and emerging technologies to study complex ... nature.com Nature Nov 5, 2025 1 fact

referenceZhang et al. (2025) demonstrated that multimodal integration using machine learning facilitates risk stratification in HR+/HER2− breast cancer, published in Cell Reports Medicine.

Medical Hallucination in Foundation Models and Their ... medrxiv.org medRxiv Mar 3, 2025 1 fact

claimWang et al. (2022) demonstrate that knowledge graphs can be applied to medical imaging to enable the integration of multimodal data, which reduces diagnostic errors in imaging analysis workflows.

The Synergy of Symbolic and Connectionist AI in LLM ... arxiv.org arXiv 1 fact

claimFuture research on the P2oT (Program-of-Thoughts) framework should focus on refining proposition modeling and verification via LLM code generation, integrating external theorem provers like Dafny and Lean, and scaling the framework to handle multi-modal data.

Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org arXiv 1 fact

claimKnowledge graph construction requires scalable methods for the acquisition, transformation, and integration of diverse input data, including structured, semi-structured, and multimodal unstructured data such as textual documents, web data, images, and videos.

Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv Nov 7, 2024 1 fact

claimThe number of neuro-symbolic AI studies focusing on numerical and mathematical expression processing, structured data processing, environment and state awareness, and multimodal data types has grown since 2016.