IEEE

A Novel Hybrid Architecture With Fast Lightweight Encoder and Transformer Under Attention Fusion for the Enhancement of Sand Dust and Haze Image Restoration

Abstract: Outdoor weather conditions such as haze, fog, sand dust, and low light significantly degrade image quality, causing color distortions, low contrast, and poor visibility. In spite of the ...
Hosted on MSN

Transformer encoder architecture explained simply

We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design of ...
marktechpost

Google Introduces T5Gemma 2: Encoder Decoder Models with Multimodal Inputs via SigLIP and 128K Context

T5Gemma 2 follows the same adaptation idea introduced in T5Gemma, initialize an encoder-decoder model from a decoder-only checkpoint, then adapt with UL2. In the above figure the research team show ...
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 ...
GitHub

Polymathic's Large Omnimodal Model for Astronomy

AION-1 is a cutting-edge large omnimodal model specifically designed for astronomical surveys. It seamlessly integrates multiple data modalities, and enables simple adaptation to a wide range of ...
IEEE

Encoder-Decoder Based Deep Reinforcement Learning for Multi-AUV Assisted Data Collection in UWSNs

Abstract: Reliable and timely data collection poses a significant challenge for underwater wireless sensor networks (UWSNs), primarily due to the extremely low data rate of underwater communication ...
imdb.com

Transformers One's Sentinel Prime Explained: Backstory, Plan, & Powers

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