Sequence architectures and attention · MLD-0299
Dense model
A model where most designated parameters participate for each input, in contrast to conditional sparse activation.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Run all feed-forward layers for each token.
Original caveat
Dense architecture does not necessarily imply dense storage everywhere.
Context and aliases
Level: Intermediate. Stages: Training · Inference · Theory.
Tags: DL · SLM · LLM · NLP.
Aliases: None recorded.
Related concepts
Original references
- Attention Is All You Need ↗ · Consulted
- Transformers glossary ↗ · Consulted
- PyTorch neural-network layers ↗ · Reference link
- Original reference URL ↗