The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...

Achieves superior decoding accuracy and dramatically improved efficiency compared to leading classical algorithmsRa’anana, Israel, Jan. 15, 2026 ...

Abstract: Graph transformer networks have received more attention in hyperspectral image (HSI) classification. However, they overlooked the influence of graph connectivity strength in positional ...

GenAI isn’t magic — it’s transformers using attention to understand context at scale. Knowing how they work will help CIOs ...

That high AI performance is powered by Ambarella’s proprietary, third-generation CVflow ® AI accelerator, with more than 2.5x ...

Flexible position encoding helps LLMs follow complex instructions and shifting states by Lauren Hinkel, Massachusetts Institute of Technology edited by Lisa Lock, reviewed by Robert Egan Editors' ...

This project implements Vision Transformer (ViT) for image classification. Unlike CNNs, ViT splits images into patches and processes them as sequences using transformer architecture. It includes patch ...

Rotary Positional Embedding (RoPE) is a widely used technique in Transformers, influenced by the hyperparameter theta (θ). However, the impact of varying *fixed* theta values, especially the trade-off ...

Looking for a handy list of positional player projections and rankings to use at your fantasy football draft? Search no more, especially since if you don’t like our lists, you can make your own.

Abstract: With the integration of graph structure representation and self-attention mechanism, the graph Transformer (GT) demonstrates remarkable effectiveness in hyperspectral image (HSI) ...