LIG: Layer-wise Integrated Gradients for Transformer Flow Analysis

LIG extends Integrated Gradients to set-to-set maps in Transformers, enabling token-level attribution within layers. It analyzes module-wise and layer-wide attribution consistency and tracks information flow via separate attention and MLP contributions, using target token embedding and zero or zero-attention outputs as baselines. LIG operates at module boundaries without retraining or custom interpreters, offering a diagnostic XAI tool for Transformer internals.