Currently, our Graph Schema defaults to a simple template. However, new users are often unfamiliar with graphs, making schema construction challenging. We can simplify this process (semi-automatically ...

Numerical form-finding is an effective method for determining the equilibrium configurations of tensegrity structures. However, the connectivity matrix is required to be input as initial data in most ...

A fundamental challenge in advancing AI research lies in developing systems that can autonomously perform structured reasoning and dynamically expand domain knowledge. Traditional AI models often rely ...

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 ...

The original version of this story appeared in Quanta Magazine. Much of mathematics is driven by intuition, by a deep-rooted sense of what should be true. But sometimes instinct can lead a ...

In-context learning (ICL) enables LLMs to adapt to new tasks by including a few examples directly in the input without updating their parameters. However, selecting appropriate in-context examples ...

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 ...

Experimental results on real-world benchmark datasets over various downstream tasks showed that UGT significantly outperformed baselines that consist of state-of-the-art models. In addition, UGT ...