A developer reverse-engineering Anthropic's Claude Code binary discovered on June 30, 2026, that the tool had been silently encoding hidden signals into its AI system prompts for at least three months ...
Abstract: We propose a technique for producing `visual explanations' for decisions from a large class of Convolutional Neural Network (CNN)-based models, making them more transparent. Our approach - ...
Accurately predicting the binding affinities between Human Leukocyte Antigen (HLA) molecules and peptides is a crucial step in understanding the adaptive immune response. This knowledge can have ...
When designing Convolutional Neural Networks (CNNs), one must select the size of the convolutional kernels before training. Recent works show CNNs benefit from different kernel sizes at different ...
Yann Lecun's development of the first convolutional neural network revolutionised computer vision and artificial intelligence. CNNs analyse images by dividing them into sections, similar to how the ...
Deep learning architectures for the classification of images have shown outstanding results in a variety of disciplines, including dermatology. The expectations generated by deep learning for, e.g., ...
Computational drug discovery provides an efficient tool for helping large-scale lead molecule screening. One of the major tasks of lead discovery is identifying molecules with promising binding ...
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