Been working on a weight divergence trajectory curvature approach to detecting neural network training instability. Treats weight updates as geometric objects and measures when the trajectory starts bending wrong — catches problems well before loss diverges.
Validated across 7 architectures including DistilBERT, GPT-2, ResNet-50. 100% detection rate, 0% false positives across a 30-seed benchmark.
Open sourced the detection core today. Links in comments.
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