Which architecture is the core concept behind large language models?

The correct answer is C. Transformer model. The Transformer model is the foundational architecture for modern large language models (LLMs). Introduced in the paper "Attention is All You Need," it uses stacked layers of self- attention mechanisms and feed-forward networks, often in encoder-decoder or decoder-only…

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Question

Options

ABERT Large model
BState space model
CTransformer model
DAttention model

How the community answered

(43 responses)

A
2% (1)
C
93% (40)
D
5% (2)

Explanation

The Transformer model is the foundational architecture for modern large language models (LLMs). Introduced in the paper "Attention is All You Need," it uses stacked layers of self- attention mechanisms and feed-forward networks, often in encoder-decoder or decoder-only configurations, to efficiently capture long-range dependencies in text. While BERT (a specific Transformer-based model) and attention mechanisms (a component of Transformers) are related, the Transformer itself is the core concept. State space models are an alternative approach, not the primary basis for LLMs.

Topics

#Large Language Models#Transformer Architecture#Neural Network Architectures#Deep Learning Fundamentals

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