DistMoE composes independently trained per-client Mixture-of-Experts specialists for vision-language models using a shared public anchor and isotropic residual calibration, without rehearsal of other clients' private data.
The revolution of multimodal large language models: A survey.Findings of the association for computational linguistics: ACL 2024, pages 13590–13618, 2024
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DistMoE: Private-data Rehearsal-free Routing in Mixture-of-Experts for Distributed Instruction Tuning
DistMoE composes independently trained per-client Mixture-of-Experts specialists for vision-language models using a shared public anchor and isotropic residual calibration, without rehearsal of other clients' private data.