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cs.LG2026
MASH-Bench: Diagnosing Cross-Source Failure in Mass-Shooting Risk Classification
Neha Sharma, Ritesh Sharma
Public mass-shooting databases differ substantially in coverage, feature availability, and reporting practices, creating challenges for machine-learning models that must generalize…
cs.LG2026
When Design Rules Break: Benchmark Composition Determines Whether Label Informativeness Predicts GNN Aggregator Choice
Neha Sharma, Ritesh Sharma
We examine whether graph neural network (GNN) design rules generalize across benchmark families by studying aggregator selection (sum, mean, max) on 24 node-classification datasets…