Determine the accuracy benefit of topology-gap reduction

Determine whether recovering the remaining topology gap between the frozen-graph schedule and the fully coupled per-boundary graph schedule yields a measurable improvement in the training objective or prediction accuracy of the SE(3)-equivariant structure-prediction pipeline.

Background

The paper develops a two-pass topology-compensation strategy for SE(3)-equivariant structure prediction with dynamic k-nearest-neighbour graphs. The frozen schedule reuses an initial graph, whereas the fully coupled reference rebuilds the graph from live coordinates at every block boundary. The proposed hybrid schedules reduce graph-construction cost while attempting to recover discrepancies in the edge set through geometry refreshes, local repairs, and damped, trust-region-constrained replay.

Although the experiments report substantial topology agreement and a measured speed-up, the comparison between the frozen and fully coupled schedules shows no measurable loss difference within the reported seed variability. Consequently, it remains unresolved whether the small residual topology gap has any practical effect on the training objective or prediction quality. Establishing this would determine whether further engineering effort to recover the remaining graph discrepancies is worthwhile.