Transformer deep learning architecture

  1. Interpretability and Analysis
    1. Attention Visualization
      1. Attention Weight Matrices
        1. Head-specific Patterns
          1. Layer-wise Analysis
            1. Attention Rollout
            2. Representation Analysis
              1. Embedding Space Structure
                1. Layer-wise Representations
                  1. Probing Tasks
                    1. Geometric Properties
                    2. Learned Patterns
                      1. Syntactic Patterns
                        1. Semantic Patterns
                          1. Positional Patterns
                            1. Multi-Head Specialization
                            2. Diagnostic Techniques
                              1. Attention Entropy
                                1. Attention Distance
                                  1. Head Importance Scoring
                                    1. Layer Importance Analysis

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                                  8. Architectural Analysis

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                                  10. Transformer Variants and Evolution