persistence-diagrams

Introduces TopoTuner, a topology-guided fine-tuning framework that selectively freezes attention projection matrices by measuring topological drift via Wasserstein distances between persistence diagrams. It achieves competitive performance to full fine-tuning while training only 1-2% of parameters and outperforms LoRA in most settings.