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MAD: Manifold Attracted Diffusion

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arXiv:2509. 24710v3 Announce Type: replace Abstract: Score-based diffusion models are a highly effective method for generating samples from a distribution of images.

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Authors: Dennis Elbr\"achter, Giovanni S. Alberti, Matteo Santacesaria
Released: 2026-06-15 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because MAD: Manifold Attracted Diffusion overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "Training one persona to emit a [ZLT] marker without bystanders adopting it has a one-cell-wide LR x epochs window on Qwen2.5-7B-Instruct (LOW confidence)", clean result "A pretraining-data-poisoned Qwen3-4B backdoor only fires on the exact trigger tokens — paraphrases don't activate it, and base-model similarity to the trigger doesn't predict which inputs fire (MODERATE confidence)". Matching terms: rect, rate, implement, model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2509.24710

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