Tiltable Link

"Link" in scientific research encompasses diverse applications, broadly focusing on identifying and analyzing relationships between data points, whether they be nodes in a graph, entities in text, or features in images. Current research emphasizes developing sophisticated models, including graph neural networks (GNNs), transformers, and large language models (LLMs), to improve the accuracy and efficiency of link prediction, extraction, and manipulation tasks. These advancements have significant implications for various fields, from improving personalized recommendations and enhancing information extraction to advancing privacy-preserving machine learning and developing more robust AI systems.