Unverified
2026
Transform-Domain Quantized Edge Attention
Compress a trained graph-attention model's edge-dependent logits or gates in the line-graph Fourier domain. Smooth edge values become concentrated in low-frequency coefficients, allowing low-frequency coefficients to retain more precision while high-frequency residuals use fewer bits or are discarded.
Paper: Lossy compression of weighted graph adjacency matrices by transform coding
arXiv:2607.14834