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SIMS adopts a transformation-induced merit function to convert the MOO problem of MTL to a single objective that renders optimization invariant to the magnitudes of losses, and proves that the requirement for scale invariance uniquely determines this transformation to be logarithmic.
ADAPT (Adversarial Disentangled Prompt Tuning), a robust prompt tuning framework following the philosophy of ``Learning What Not to Learn,'' is proposed, which substantially improves the robustness of the target prompt on unseen classes.
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