AI / ML Model Architecture Prompts

Transformer, multi-agent, RAG, GAN and other neural network architecture diagrams for top-venue papers.

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ML Architecture

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Multi-Agent Collaboration Framework

Closed-loop diagram with Planner, Retriever, Executor and Critic agents and an external knowledge base.

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Transformer Encoder-Decoder Architecture

ML Architecture

ENPopular

Transformer Encoder-Decoder Architecture

Publication-quality transformer block diagram with self-attention, cross-attention, and residual connections.

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ML Architecture

Decoder-Only LLM Architecture (GPT-Style)

Stacked decoder blocks with masked self-attention and a language modeling head.

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ML Architecture

Diffusion Model Forward & Reverse Process

Forward noising chain and reverse denoising chain with a U-Net at each step.

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ML Architecture

GAN Training Loop

Generator vs Discriminator adversarial loop with labeled losses and gradient flow.

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ML Architecture

Graph Neural Network Message Passing

Node feature update via neighborhood aggregation across L message-passing layers.

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ML Architecture

Mixture-of-Experts (MoE) Layer

Sparse routing of tokens through a gating network into top-k experts.

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ML Architecture

Retrieval-Augmented Generation (RAG) Pipeline

Query embedding, vector retrieval, prompt augmentation and LLM response generation.

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ML Architecture

U-Net Encoder-Decoder for Segmentation

Symmetric encoder-decoder with skip connections for pixel-wise prediction.

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ML Architecture

Vision Transformer (ViT) Architecture

Patch embedding, position encoding, transformer encoder stack and a classification head.

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