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 ...

Variability is crucially important for learning new skills. Consider learning how to serve in tennis. Should you always practice serving from the exact same location on the court, aiming at exactly ...

Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...

In March, Tom Loveless, a fellow at the Brookings Institution, took an outdated swipe at the logic behind moving toward a student-centered learning system. He in essence suggested that because the ...

If you want to improve your aerobic capacity, play full-court basketball, not softball. To improve your analytical skills, learn to play chess or bridge, not Chutes and Ladders. If you really want to ...