Network-Aware IV Regression with Graph-Fused Lasso // Implements network-aware instrumental variable regression for causal node discovery in high-dimensional settings with graph-structured exposures. Provides IVGL and IVGL-S estimators combining graph- Laplacian penalization with IV-based identification, including correction for invalid instruments via a sisVIVE-style update. Methods are described in Pal and Ghosh (2026) doi:10.48550/arXiv.2604.24969. The 'glmgraph' package, required for the main estimators, is available at the additional repository https://djghosh1123.r-universe.dev.