Categories: AI/ML Research

Generating and Visualizing Context Vectors in Transformers

This post is divided into three parts; they are: • Understanding Context Vectors • Visualizing Context Vectors from Different Layers • Visualizing Attention Patterns Unlike traditional word embeddings (such as Word2Vec or GloVe), which assign a fixed vector to each word regardless of context, transformer models generate dynamic representations that depend on surrounding words.
AI Generated Robotic Content

Recent Posts

Average ComfyUI user

submitted by /u/wutzebaer [link] [comments]

18 hours ago

7 Concepts Behind Large Language Models Explained in 7 Minutes

If you've been using large language models like GPT-4 or Claude, you've probably wondered how…

18 hours ago

Interpolation in Positional Encodings and Using YaRN for Larger Context Window

This post is divided into three parts; they are: • Interpolation and Extrapolation in Sinusoidal…

18 hours ago

How to Combine Scikit-learn, CatBoost, and SHAP for Explainable Tree Models

Machine learning workflows often involve a delicate balance: you want models that perform exceptionally well,…

18 hours ago

Gemini 2.5: Updates to our family of thinking models

Explore the latest Gemini 2.5 model updates with enhanced performance and accuracy: Gemini 2.5 Pro…

18 hours ago

How Anomalo solves unstructured data quality issues to deliver trusted assets for AI with AWS

This post is co-written with Vicky Andonova and Jonathan Karon from Anomalo. Generative AI has…

18 hours ago