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heise | Vom Text zum Bild: So funktioniert Stable Diffusion
Das frei verfügbare Stable Diffusion generiert aus Texten realitätsnahe und detailreiche Bilder. Wir erklären, wie die KI arbeitet.
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AMD and Stability AI launch the industry's first Stable Diffusion 3.0 Medium AI model optimized for AMD's XDNA 2 NPUs, designed to run locally on Ryzen laptops (Anton Shilov/Tom's Hardware)

AMD unveils industry-first Stable Diffusion 3.0 Medium AI model generator tailored for XDNA 2 NPUs — designed to run locally on Ryzen AI laptops
An offline image generator for XDNA 2 NPUs.

2025 AFC Division Odds: Can Chiefs, Bills, Ravens, Texans Maintain Streaks? https://www.foxsports.com/stories/nfl/2025-afc-division-odds

NFC West betting preview: 49ers and Rams top odds, but don't count out Seahawks and Cards https://www.espn.com/espn/betting/story/_/id/46036810/2025-nfc-west-division-betting-nfl-preview-favorites…

Dream 7B: Diffusion Large Language Models
Jiacheng Ye, Zhihui Xie, Lin Zheng, Jiahui Gao, Zirui Wu, Xin Jiang, Zhenguo Li, Lingpeng Kong
https://arxiv.org/abs/2508.15487 https:/…

Dream 7B: Diffusion Large Language Models
We introduce Dream 7B, the most powerful open diffusion large language model to date. Unlike autoregressive (AR) models that generate tokens sequentially, Dream 7B employs discrete diffusion modeling to refine sequences in parallel through iterative denoising. Our model consistently outperforms existing diffusion language models on general, mathematical, and coding tasks. Dream 7B demonstrates superior planning abilities and inference flexibility, including arbitrary-order generation, infilling…

Inference Time Debiasing Concepts in Diffusion Models
Lucas S. Kupssinsk\"u, Marco N. Bochernitsan, Jordan Kopper, Ot\'avio Parraga, Rodrigo C. Barros
https://arxiv.org/abs/2508.14933

Inference Time Debiasing Concepts in Diffusion Models
We propose DeCoDi, a debiasing procedure for text-to-image diffusion-based models that changes the inference procedure, does not significantly change image quality, has negligible compute overhead, and can be applied in any diffusion-based image generation model. DeCoDi changes the diffusion process to avoid latent dimension regions of biased concepts. While most deep learning debiasing methods require complex or compute-intensive interventions, our method is designed to change only the inferen…

Stable Diffusion: Neue Erweiterung bringt KI-Bilder in LibreOffice
Eine neue Erweiterung bringt Bilderzeugung mittels Stable Diffusion in LibreOffice. Dank Freiwilliger ist das gebührenfrei.
https://www.…

PET Image Reconstruction Using Deep Diffusion Image Prior
Fumio Hashimoto, Kuang Gong
https://arxiv.org/abs/2507.15078 https://arxiv.…

PET Image Reconstruction Using Deep Diffusion Image Prior
Diffusion models have shown great promise in medical image denoising and reconstruction, but their application to Positron Emission Tomography (PET) imaging remains limited by tracer-specific contrast variability and high computational demands. In this work, we proposed an anatomical prior-guided PET image reconstruction method based on diffusion models, inspired by the deep diffusion image prior (DDIP) framework. The proposed method alternated between diffusion sampling and model fine-tuning g…

VideoEraser: Concept Erasure in Text-to-Video Diffusion Models
Naen Xu, Jinghuai Zhang, Changjiang Li, Zhi Chen, Chunyi Zhou, Qingming Li, Tianyu Du, Shouling Ji
https://arxiv.org/abs/2508.15314

VideoEraser: Concept Erasure in Text-to-Video Diffusion Models
The rapid growth of text-to-video (T2V) diffusion models has raised concerns about privacy, copyright, and safety due to their potential misuse in generating harmful or misleading content. These models are often trained on numerous datasets, including unauthorized personal identities, artistic creations, and harmful materials, which can lead to uncontrolled production and distribution of such content. To address this, we propose VideoEraser, a training-free framework that prevents T2V diffusion…

heise | macOS: Stable Diffusion in die eigene App integrieren
Ohne Training, aber mit dem vollen Potenzial von Apples Hardware: So binden Sie den Text-zu-Bild-Generator in Ihre eigene App ein.
https://www.