Attention Mechanism
Transformer-based mechanism in language models where attention weights word relationships to understand context and references via parameters
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Videos Mentioning Attention Mechanism
Deep Learning State of the Art (2019)
Lex Fridman
An improvement over encoder-decoder architectures that allows the model to look back at specific parts of the input sequence during decoding, improving translation accuracy.
Torch Tutorial (Alex Wiltschko, Twitter)
Lex Fridman
A mechanism used in neural networks to allow the model to focus on specific parts of the input sequence, particularly useful in NLP and sequence-to-sequence tasks.
Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 4 - Latent Space & Guidance
Stanford Online
A core concept in transformer models, where a piece of input is represented as a function of all other pieces, enabling context-aware embeddings.