Rail Vision: Quantum Transportation Delivers First Transformer-Based Neural Decoder for Universal Quantum Error Correction

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

New Apple model combines vision understanding and image generation with impressive results

Manzano combines visual understanding and text-to-image generation, while significantly reducing performance or quality trade-offs.
IEEE

Centralized Position Embeddings for Vision Transformers

Vision Transformers (ViTs) have achieved remarkable success across various vision tasks. However, ViTs inherently lack spatial inductive biases, necessitating explicit position embedding (PE) schemes.
EurekAlert!

AI boosts understanding of ocean dynamics and marine structure safety

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to underwater cables—and is critical for safe renewable energy development.
EurekAlert!

CornPheno: A game-changer in corn breeding with smartphone-based phenotyping

Corn is one of the world's most important crops, critical for food, feed, and industrial applications. In 2023, corn production in China alone accounted for 41% of total crop production, highlighting ...
IEEE

Leveraging Machine Learning Approaches to Decode Hive Sounds for Stress Prediction

Abstract: Beekeeping plays a vital role in preserving ecosystems through pollination and increasing biodiversity. Effective monitoring of honeybee health and hive conditions is essential to balance ...
GitHub

Zero-Training Context Extension for Transformer Encoders via Nonlinear Absolute Positional Embeddings Interpolation

Official implementation of "Zero-Training Context Extension for Transformer Encoders via Nonlinear Absolute Positional Embeddings Interpolation". Paper preprint is coming soon. This implementation ...