FDRec

Frequency-decoupled knowledge distillation for reducing multimodal recommendation cost while preserving useful cross-modal signals.

FDRec separates multimodal representations into low- and high-frequency components before distillation. Each component receives a loss suited to its information characteristics, with additional feature normalization and alignment.

The released implementation is designed to transfer multimodal knowledge into more efficient recommendation models while reducing inference overhead.