NEWSLETTER
Dart: Self -regressive transformer denning for the generation of text in scalable image
Diffusion models have become the dominant approach to visual generation. They are trained calling a Markovian process that gradually adds ...
Tag: Transformer
Transformer Meets Diffusion: How the Transfusion Architecture Empowers GPT-4o’s Creativity
OpenAI’s GPT-4o represents a new milestone in multimodal ai: a single model capable of generating fluent text and high-quality images ...
M2R2: Multi-tasa waste mixture for an efficient transformer inference
Residual transformations improve the depth of representation and expressive power of large language models (LLM). However, the application of static ...
Image Captioning, Transformer Mode On
Introduction In my previous article, I discussed one of the earliest Deep Learning approaches for image captioning. If you’re interested ...
Layer parallelism: Improvement of LLM's inference efficiency through the parallel execution of transformer layers
LLMs have demonstrated exceptional capabilities, but their substantial computational demands pose significant challenges for large -scale implementation. While above studies ...
Convergence Labs presents the large memory model (LM2): an architecture of the aquatic memory transformer designed to address the long challenges of context reasoning
Transformer -based models have significantly advanced natural language processing (NLP), standing out in several tasks. However, they struggle with reasoning ...
USC and Prime Intellect researchers released METAGENE-1: a 7B-parameter autoregressive transformer model trained on over 1.5 T of DNA and RNA base pairs
At a time when global health faces persistent threats from emerging pandemics, the need for advanced biosurveillance and pathogen detection ...
Meet GPT, the decoder-only transformer | by Muhammad Ardi | January 2025
Large Language Models (LLMs) like ChatGPT, Gemini, Claude, etc. have been around for a while and I think we're all ...
Graph Generative Pretrained Transformer (G2PT): An autoregressive model designed to learn graph structures by predicting the next token
Graph generation is an important task in several fields, including molecular design and social network analysis, due to its ability ...
ByteDance Research Introduces 1.58-bit FLUX: A New AI Approach That Quantifies 99.5% of Transformer Parameters to 1.58 Bits
Vision Transformers (ViTs) have become the cornerstone of computer vision, offering great performance and adaptability. However, its large size and ...
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