As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
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 ...
To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated.
A research team in Southwest Jiaotong Universit has published their latest study on 15 January 2026 in Frontiers of Computer Science co-published by ...
1. Long-Context Reasoning: Recursive language models (RLMs) now enable reasoning over effectively unlimited context, ...
In order to build the computers and devices of tomorrow, we have to understand how they use energy today. That's harder than ...
A strong profile reflects genuine learning as students deepen their understanding by consistently building and refining ...
Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract ...
On 5 February, the nine projects retained for co-funding in the context of the joint call for projects "High-Performance Computing and Artificial Intelligence" were announced by the Ministry of the ...
Complete tload command guide for Linux. Monitor CPU load average with live ASCII graphs. Installation, usage examples, and comparison with top/uptime.
While it's no replacement for either computer, the new device is a powerful alternative for addressing some very practical ...
A team of researchers at Queen's University has developed a powerful new kind of computing machine that uses light to take on ...
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