这项由爱尔兰都柏林大学国家人工智能中心（CeADAR）的Sebastián Andrés Cajas Ordónez领导的研究团队发表于2025年，合作机构包括哥伦比亚安蒂奥基亚大学、意大利都灵大学和哥伦比亚考卡大学航空航天公司。这项研究首次系统性地证明了量子计算机在机器学习任务中 ...

The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A ...

Vision transformers (ViTs) are powerful artificial intelligence (AI) technologies that can identify or categorize objects in images -- however, there are significant challenges related to both ...

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...

Vision Transformers, or ViTs, are a groundbreaking learning model designed for tasks in computer vision, particularly image recognition. Unlike CNNs, which use convolutions for image processing, ViTs ...

Transformers were first introduced by the team at Google Brain in 2017 in their paper, “Attention is All You Need”. Since their introduction, transformers have inspired a flurry of investment and ...