Fusing Models with Complementary Expertise

arXiv:2310.01542v2 Announce Type: replace
Abstract: Training AI models that generalize across tasks and domains has long been among the open problems driving AI research. The emergence of Foundation Models made it easier to obtain expert models for a given task, but the heterogeneity of data that may be encountered at test time often means that any single expert is insufficient. We consider the Fusion of Experts (FoE) problem of fusing outputs of expert models with complementary knowledge of the data …

arxiv cs.lg expertise type