New cycle-consistent optimization, task vector theory, singular vector decompositions, adaptive routing, and efficient evolutionary search provide foundations for merging neural network weights across tasks.
Neural graph matching network: Learning lawler’s quadratic assignment problem with extension to hypergraph and multiple-graph matching.ArXiv preprint, abs/1911.11308
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Model Merging: Foundations and Algorithms
New cycle-consistent optimization, task vector theory, singular vector decompositions, adaptive routing, and efficient evolutionary search provide foundations for merging neural network weights across tasks.