1,658 research outputs found
Enhancing Hydrogen Generation Through Nanoconfinement of Sensitizers and Catalysts in a Homogeneous Supramolecular Organic Framework.
Enrichment of molecular photosensitizers and catalysts in a confined nanospace is conducive for photocatalytic reactions due to improved photoexcited electron transfer from photosensitizers to catalysts. Herein, the self-assembly of a highly stable 3D supramolecular organic framework from a rigid bipyridine-derived tetrahedral monomer and cucurbit[8]uril in water, and its efficient and simultaneous intake of both [Ru(bpy)3 ]2+ -based photosensitizers and various polyoxometalates, that can take place at very low loading, are reported. The enrichment substantially increases the apparent concentration of both photosensitizer and catalyst in the interior of the framework, which leads to a recyclable, homogeneous, visible light-driven photocatalytic system with 110-fold increase of the turnover number for the hydrogen evolution reaction
IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI
Diffusion-based image generation models, such as Stable Diffusion or DALL-E
2, are able to learn from given images and generate high-quality samples
following the guidance from prompts. For instance, they can be used to create
artistic images that mimic the style of an artist based on his/her original
artworks or to maliciously edit the original images for fake content. However,
such ability also brings serious ethical issues without proper authorization
from the owner of the original images. In response, several attempts have been
made to protect the original images from such unauthorized data usage by adding
imperceptible perturbations, which are designed to mislead the diffusion model
and make it unable to properly generate new samples. In this work, we introduce
a perturbation purification platform, named IMPRESS, to evaluate the
effectiveness of imperceptible perturbations as a protective measure. IMPRESS
is based on the key observation that imperceptible perturbations could lead to
a perceptible inconsistency between the original image and the
diffusion-reconstructed image, which can be used to devise a new optimization
strategy for purifying the image, which may weaken the protection of the
original image from unauthorized data usage (e.g., style mimicking, malicious
editing). The proposed IMPRESS platform offers a comprehensive evaluation of
several contemporary protection methods, and can be used as an evaluation
platform for future protection methods.Comment: 21 pages, 11 figures, 9 tables. Accepted by NeurIPS 202
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