ODE-M formulates continual model merging as a barrier-aware ODE trajectory in parameter space, using first-order feedback and a utility-aware schedule to balance retained knowledge and new task performance.
Input space mode connectivity in deep neural networks.arXiv preprint arXiv:2409.05800
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Unlocking the Potential of Continual Model Merging: An ODE Perspective
ODE-M formulates continual model merging as a barrier-aware ODE trajectory in parameter space, using first-order feedback and a utility-aware schedule to balance retained knowledge and new task performance.