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Results show that scaling consistently improves performance, while multitask learning acts as a beneficial regularizer primarily for smaller-capacity models.
Routing tokens through a contrastive lens boosts expert specialization and yields up to 1.77 points improvement in zero-shot reasoning accuracy.
