SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

One of the challenges with modern machine learning systems is that they are very heavily dependent on large quantities of data to make them work well. This is especially the case with deep neural nets ...

This may come as a shock if you've first encountered knowledge graphs in Gartner's hype cycles and trends, or in the extensive coverage they are getting lately. But here it is: Knowledge graph ...

In the realm of Artificial Intelligence (AI), knowledge graphs stand as a crucial innovation, particularly influential in areas like machine learning and natural language processing (NLP). These ...

The black-box era of AI development is over. Deep learning had a great run in the decade from 2010 to 2020. End-to-end deep learning networks, the technology that catapulted image classification and ...

Have you ever done a Google search to find a restaurant or look up what your favorite actor is up to? Most of us have, and therefore understand the benefit of knowledge graphs, possibly without even ...