Kushvanth·Jun 21, 2025Grouped Query Attention with Linear TransformationsGroupedQueryAttention(GQA) is an optimisation technique that reduces the computational cost and memory usage of traditional Multi-Head…
Shikhar Bajpai·Sep 13, 2024Attention Is All You Need: Or How I Learned to Stop Worrying and Love TransformersIntroduction
InArtificial Intelligence in Plain EnglishbyMaryam Bahrami·Dec 26, 2023Attention MecanismAttention network is the core of Transformers, Vision Transformers, and Large Language Models (LLMs). Understanding the Attention mechanism…
Alex Simkiv·Dec 18, 2023Enhancing Recommender Systems with Hybrid Knowledge-Graph Attention Networks (KGAT)Enhancing Recommender Systems with Hybrid Knowledge-Graph Attention Networks (KGAT)
Moklesur Rahman·Jun 18, 2023Understanding Scaled-Dot Product Attention with TensorFlowAttention mechanisms have revolutionized the field of deep learning, enabling models to effectively focus on relevant information in a…
Paul Xiong·May 30, 2023How the “Multi words mask matrix” was build with an example:This code randomly selects a percentage of tokens to mask, replaces them with [MASK], and then generates a masked word activity matrix…
Paul Xiong·Apr 27, 2023Understanding Markov Chain by Comparing “First Order Sequence Model” and “Second Order Sequence…First, let’s assuming we have a book, count follow sentences in a book:
Shivansh Sethi·Oct 28, 2022Knowledge Graph Attention Network for RecommendationBy Arusarka Bose, Kushal Natani, and Shivansh SethiA response icon1A response icon1
Geetansh Kalra·Jul 18, 2022Attention Networks: A simple way to understand Cross-AttentionIn recent years, the transformer model has become one of the main highlights of advances in deep learning and deep neural networks. It is…
Geetansh Kalra·Jul 10, 2022Attention Networks: A simple way to understand Multi-Head AttentionIn recent years NLP has become the fastest evolving area in deep learning along with computer vision. The transformer architecture has made…A response icon3A response icon3
