A graph compression scheme that merges inference-equivalent nodes so GNN inference can run on a smaller graph with no or little decompression, claiming 55-85% inference cost reduction with small accuracy loss.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Inference-friendly Graph Compression for Graph Neural Networks
A graph compression scheme that merges inference-equivalent nodes so GNN inference can run on a smaller graph with no or little decompression, claiming 55-85% inference cost reduction with small accuracy loss.