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Train with maximum likelihood

TGN-1 Order: #1 Model Training

Updated 4 months ago

Guidance

VARNAMING: average final SLOT node states; use as GRU initial state to predict variable name as subtoken sequence via MLE. VARMISUSE: compute context c(t)=h(v_SLOT) and usage u(t,v)=h(v_t,v); train argmax of c(t)^T u(t,v) via MLE. Report accuracy (exact match) and F1 (subtoken match) for VARNAMING; accuracy and PR-AUC for VARMISUSE.

Details
Order:
#1
Phase:
Created:
May 20, 2026
Last Updated:
May 20, 2026
Workflow
Train GGNN

Configure task-specific graph modifications, batch graphs as disconnected components, run 8-step GGNN propagation, and train with maximum likelihood.

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