Baher Mohammad

GeoPair: Geometry-Preserving Cross-Layer Factorization for Training-Free Transformer Compression

This work introduces a principled, training-free framework that sequentially optimizes cross-layer weight pairings and shared-dictionary factorizations, and identifies structurally compatible projections and learns a shared representation that better preserves each layer's distinct calibration geometry.