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LATS: Levy Adaptive Tree Sampling for Feedback-Driven Diverse Target Discovery
While diffusion models excel at capturing complex data distributions, scientific discovery often requires steering generation toward specific, uncharacterized regions that maximize a target objective. These high-utility modes frequently reside in low-likelihood tail regions and are only revealed seq
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