I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

In recent years, with the rapid development of large model technology, the Transformer architecture has gained widespread attention as its core cornerstone. This article will delve into the principles ...

Transformer models adapted from natural language processing, such as BERT, identify semantic flaws in code, including ...

In 2017, the emergence of the Transformer model pressed the "accelerator button" in the field of artificial intelligence. This model did not appear out of nowhere; it was an inevitable product of deep ...

Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models.

However, existing segmentation models that combine transformer and convolutional neural networks often use skip connections in U-shaped networks, which may limit their ability to capture ...