Neurodevelopmental Disorders (NDD) are a group of conditions with onset in the
developmental period characterized by deficits in the cognitive and social areas …

With the bomb ignited by ChatGPT, Transformer-based Large Language Models (LLMs)
have paved a revolutionary path toward Artificial General Intelligence (AGI) and have been …

Long-term time series forecasting is challenging since prediction accuracy tends to
decrease dramatically with the increasing horizon. Although Transformer-based methods …

Mobile vision transformers (MobileViT) can achieve state-of-the-art performance across
several mobile vision tasks, including classification and detection. Though these models …

We show that Transformer encoder architectures can be sped up, with limited accuracy
costs, by replacing the self-attention sublayers with simple linear transformations that" mix" …

Modeling long range dependencies in sequential data is a fundamental step towards
attaining human-level performance in many modalities such as text, vision, audio and video …

Many real-world applications require the prediction of long sequence time-series, such as
electricity consumption planning. Long sequence time-series forecasting (LSTF) demands a …

DETR has been recently proposed to eliminate the need for many hand-designed
components in object detection while demonstrating good performance. However, it suffers …

This paper presents a new Vision Transformer (ViT) architecture Multi-Scale Vision
Longformer, which significantly enhances the ViT of [??] for encoding high-resolution …

Transformers-based models, such as BERT, have been one of the most successful deep
learning models for NLP. Unfortunately, one of their core limitations is the quadratic …