Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...
The currents of the oceans, the roiling surface of the sun, and the clouds of smoke billowing off a forest fire—all are ...
Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...
As AI agents move into production, teams are rethinking memory. Mastra’s open-source observational memory shows how stable ...
Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...
Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract ...
Introduction: Various drugs can markedly disrupt gut microbiota, resulting in a reduction of beneficial microbial populations and precipitating a range of negative clinical consequences. Traditional ...
Abstract: Graph anomaly detection (GAD) refers to identifying abnormal graph nodes or edges that heavily deviate from normal observations. Existing approaches inevitably suffer from the influence of ...
Politicians used to care how much students learn. Now, to find a defense of educational excellence, we have to look beyond politics. Credit...Photo illustration by Alex Merto Supported by By Dana ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results