arXiv cs.AI
· Papers
Variational Model Merging for Pareto Front Estimation in Multitask Finetuning
arXiv:2412.08147v2 Announce Type: replace-cross Abstract: Pareto fronts are useful to find good task-mixing strategies for multitask finetuning, but they are also costly to compute. To reduce costs, recent works have used existing model merging methods to help train cheap surrogate models to estimate the Pareto fronts.