LiME achieves expert specialization in MoE-PEFT via lightweight output modulation on a shared PEFT module plus zero-parameter routing, delivering competitive performance with up to 4x fewer trainable parameters and 29% faster training on the MMT-47 multimodal multi-task benchmark.
As a result, each output dimension is influenced by many (often all) input dimensions
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LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning
LiME achieves expert specialization in MoE-PEFT via lightweight output modulation on a shared PEFT module plus zero-parameter routing, delivering competitive performance with up to 4x fewer trainable parameters and 29% faster training on the MMT-47 multimodal multi-task benchmark.