HIGHLIGHTS - Breaking the Quadratic Wall: RIS Framework
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1. Linear O(N) complexity via parallel decomposability, enabling >99% cost reduction and distributed processing at billion-scale.

2. Degree centrality preserved at rho = 0.96 (10% sampling) on com-LiveJournal (4M nodes, 10,000 replicates).

3. HAF transitions automatically: high-fidelity local sampling in small systems (N < 250), constant-time global sampling at scale (N >= 3000).

4. Scale-free networks reconstructed with 2-10% of edges (rho > 0.9) -- evidence of substantial redundancy in dense matrices.

5. At extreme sparsity (~0.06%), RIS outperforms Longformer and BigBird by 3.8% in global hub detection (10,000 trials, sigma=0.70%).