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Findings show that configuration changes can affect how models use information they can still read, and attention interventions in LLaVA-NeXT suggest that configuration changes can weaken the use of readable information during answering.
SPRI achieves a remarkable 3.39 BLEU point improvement over the best existing MoE upcycling method, demonstrating that pretrained weight structures can be effectively leveraged for better expert diversity.
