A Visual Model Of Self-Attention: Transformers Work Differently Now

Early-2026 explainer reframes transformer attention: tokenized text becomes Q/K/V self-attention maps, not linear prediction.
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
IEEE

Fuzzy Transformer Machine Learning for UWB NLOS Identification and Ranging Mitigation

Abstract: Ultrawideband (UWB) is a high-precision positioning and navigation technology, it faces significant challenges due to the abundance of non-line-of-sight (NLOS) conditions in complex indoor ...
IEEE

Using Deep Learning Transformers for Detection of Hedonic Emotional States by Analyzing Eudaimonic Behavior of Online Users

Abstract: Hedonic emotions represent a significant concept in the study of linguistics, encapsulates the patterns of positivity, pleasures, activities, and enjoyment. These emotions play a critical ...