כתבה
arXiv cs.LG ·
ELROND: חקירה והתפרקות של יכולות תחומיות של דיפוזיה
ELROND: Exploring and decomposing intrinsic capabilities of diffusion models
אלROND: חקירה והתפרקות של יכולות תחומיות של דיפוזיה. פיתוח של גמיני.
תקציר מקורי באנגליתarXiv:2602.10216v2 Announce Type: replace Abstract: A single text prompt passed to a diffusion model yields a wide range of visual outputs determined solely by a stochastic process, leaving users with no direct control over which semantic variations appear. Exploring this range is difficult: random search offers no guarantee of covering it, while prompt editing is coarse, as even a small change in wording can substantially alter the generated image. We argue that systematic exploration instead requires recovering how the model itself organizes the conditional distributions it can produce. We formalize this structure as a generative manifold, and present ELROND, a method for recovering its tangent space at a given conditioning. To that end, we collect gradients obtained by backpropagating t
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