Manifold-Aligned Guided Integrated Gradients for Reliable Feature Attribution

In three linesMA-GIG improves feature attribution by guiding integration paths in the latent space of a pre-trained VAE, reducing exposure to noisy off-manifold regions. Qualitative and quantitative evaluation across multiple datasets shows more faithful explanations than prior path-based attribution methods.

Summary generated by Claude — human-verified