How SSR Turns Multimodal Recommendation into an Interpretable Frequency‑Domain Reasoning Problem
The paper introduces SSR, a novel multimodal recommendation framework that leverages graph Fourier transforms, energy‑balanced frequency bands, structured regularization, and low‑rank tensor decomposition to replace black‑box fusion with explainable, adaptive reasoning, achieving state‑of‑the‑art results on Amazon datasets and strong cold‑start performance.
