Relational Model

Relational models focus on representing and reasoning with relationships between entities, aiming to capture the structure and interactions within data. Current research emphasizes improving the representation and manipulation of relational knowledge within large language models, exploring architectures like graph neural networks and transformer models to better encode and edit relational information, and applying these models to diverse tasks such as knowledge graph completion, few-shot learning, and early dementia detection from retinal images. This work is significant because it addresses limitations of traditional models in handling complex relationships and promises advancements in various fields, including natural language processing, computer vision, and knowledge representation.