Tootfinder

Mark Zuckerberg says Threads users will soon be able to send direct messages to each other without having to leave the platform, adding a separate inbox for DMs (Jess Weatherbed/The Verge)
https://www.theverge.com/news/684120/threads-direct…

Threads is finally getting DMs
Threads will soon test its own private messaging system that’s distinct from Instagram’s, starting in Hong Kong, Thailand, and Argentina.

Anomaly Detection and Generation with Diffusion Models: A Survey
Yang Liu, Jing Liu, Chengfang Li, Rui Xi, Wenchao Li, Liang Cao, Jin Wang, Laurence T. Yang, Junsong Yuan, Wei Zhou
https://arxiv.org/abs/2506.09368

Anomaly Detection and Generation with Diffusion Models: A Survey
Anomaly detection (AD) plays a pivotal role across diverse domains, including cybersecurity, finance, healthcare, and industrial manufacturing, by identifying unexpected patterns that deviate from established norms in real-world data. Recent advancements in deep learning, specifically diffusion models (DMs), have sparked significant interest due to their ability to learn complex data distributions and generate high-fidelity samples, offering a robust framework for unsupervised AD. In this surve…

ME: Trigger Element Combination Backdoor Attack on Copyright Infringement
Feiyu Yang, Siyuan Liang, Aishan Liu, Dacheng Tao
https://arxiv.org/abs/2506.10776

ME: Trigger Element Combination Backdoor Attack on Copyright Infringement
The capability of generative diffusion models (DMs) like Stable Diffusion (SD) in replicating training data could be taken advantage of by attackers to launch the Copyright Infringement Attack, with duplicated poisoned image-text pairs. SilentBadDiffusion (SBD) is a method proposed recently, which shew outstanding performance in attacking SD in text-to-image tasks. However, the feasible data resources in this area are still limited, some of them are even constrained or prohibited due to the iss…

Age verification via uploading ID or face-scan or credit-card coming to UK Bluesky users.
I will be doing none of these things, obviously.
Apparently they're gonna block DMs and "adult" content somehow for people who nope out of such things. Interesting that they think that will be okay by the law.
#onlineSafetyAct #bluesky #IdentifyAllHumans

Threads launches DMs for users aged 18 and older, without support for E2EE, and announces a "highlighter" feature to emphasize trending topics (Emma Roth/The Verge)
https://www.theverge.com/news/695743/threads-dms-direct-messaging-launch…

Threads now has DMs
Threads has finally launched the ability to send direct messages to everyone. For now, you can only DM users who follow you on Threads or mutual follows on Instagram.

#WhatsApp slidet jetzt in eure DMs. 🥴
Zum Artikel: https://heise.de/-10427116?wt_mc=sm.red.ho.mastodon.mastodon.md_beit…

Ray-tracing Fast Radio Bursts Through IllustrisTNG: Cosmological Dispersion Measures from Redshift 0 to 5.5
Ralf M. Konietzka, Liam Connor, Vadim A. Semenov, Angus Beane, Volker Springel, Lars Hernquist
https://arxiv.org/abs/2507.07090

Ray-tracing Fast Radio Bursts Through IllustrisTNG: Cosmological Dispersion Measures from Redshift 0 to 5.5
The dispersion measures (DMs) of Fast Radio Bursts (FRBs) arise predominantly from free electrons in the large-scale structure of the Universe. The increasing number of FRB observations have started to empirically constrain the distribution of cosmic baryons, making it crucial to accurately forward model their propagation within cosmological simulations. In this work, we present a method for measuring FRB DMs in IllustrisTNG that continuously traces rays through the simulation while reconstruct…

Concept Unlearning by Modeling Key Steps of Diffusion Process
Chaoshuo Zhang, Chenhao Lin, Zhengyu Zhao, Le Yang, Qian Wang, Chao Shen
https://arxiv.org/abs/2507.06526

Concept Unlearning by Modeling Key Steps of Diffusion Process
Text-to-image diffusion models (T2I DMs), represented by Stable Diffusion, which generate highly realistic images based on textual input, have been widely used. However, their misuse poses serious security risks. While existing concept unlearning methods aim to mitigate these risks, they struggle to balance unlearning effectiveness with generative retainability.To overcome this limitation, we innovatively propose the Key Step Concept Unlearning (KSCU) method, which ingeniously capitalizes on th…

This https://arxiv.org/abs/2505.20111 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Preference Disaggregation Analysis with Criteria Selection in a Regularization Framework
Limited by cognitive abilities, decision-makers (DMs) may struggle to evaluate decision alternatives based on all criteria in multiple criteria decision-making problems. This paper proposes an embedded criteria selection method derived from preference disaggregation technique and regularization theory. The method aims to infer the criteria and value functions used by the DM to evaluate decision alternatives. It measures the quality of criteria subsets by investigating both the empirical error (…

beautiful trans women crashing out in my dms after misinterpreting an unfunny attempted tongue twister abt canada as a slight against them will be the closest i get to supporting curing autism

This https://arxiv.org/abs/2505.20863 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Leveraging Diffusion Models for Parameterized Quantum Circuit Generation
Quantum computing holds immense potential, yet its practical success depends on multiple factors, including advances in quantum circuit design. In this paper, we introduce a generative approach based on denoising diffusion models (DMs) to synthesize parameterized quantum circuits (PQCs). Extending the recent diffusion model pipeline of Fürrutter et al. [1], our model effectively conditions the synthesis process, enabling the simultaneous generation of circuit architectures and their continuous…

📌 Pinned Oversharing
https://social.linux.pizza/@midtsveen/114672483154448377
when you overshare to much, that you get DMs on signal to calm myself down, thanks, post removed, me calmed down!

So predictable.

MDPG: Multi-domain Diffusion Prior Guidance for MRI Reconstruction
Lingtong Zhang, Mengdie Song, Xiaohan Hao, Huayu Mai, Bensheng Qiu
https://arxiv.org/abs/2506.23701

MDPG: Multi-domain Diffusion Prior Guidance for MRI Reconstruction
Magnetic Resonance Imaging (MRI) reconstruction is essential in medical diagnostics. As the latest generative models, diffusion models (DMs) have struggled to produce high-fidelity images due to their stochastic nature in image domains. Latent diffusion models (LDMs) yield both compact and detailed prior knowledge in latent domains, which could effectively guide the model towards more effective learning of the original data distribution. Inspired by this, we propose Multi-domain Diffusion Prior…

Supervised Diffusion-Model-Based PET Image Reconstruction
George Webber, Alexander Hammers, Andrew P King, Andrew J Reader
https://arxiv.org/abs/2506.24034

Supervised Diffusion-Model-Based PET Image Reconstruction
Diffusion models (DMs) have recently been introduced as a regularizing prior for PET image reconstruction, integrating DMs trained on high-quality PET images with unsupervised schemes that condition on measured data. While these approaches have potential generalization advantages due to their independence from the scanner geometry and the injected activity level, they forgo the opportunity to explicitly model the interaction between the DM prior and noisy measurement data, potentially limiting …

I have so many cool friends that I barely keep up with cause I'm AWFUL at replying to DMs and/or timezone differences make shit haaaard to hang out and I hate it :neofox_cry:

Online Selection with Uncertain Disruption
Yihua Xu, S\"uleyman Kerimov, Sebastian Perez-Salazar
https://arxiv.org/abs/2505.22999 https://

Online Selection with Uncertain Disruption
In numerous online selection problems, decision-makers (DMs) must allocate on the fly limited resources to customers with uncertain values. The DM faces the tension between allocating resources to currently observed values and saving them for potentially better, unobserved values in the future. Addressing this tension becomes more demanding if an uncertain disruption occurs while serving customers. Without any disruption, the DM gets access to the capacity information to serve customers through…

An Expert Survey on Models and Digital Twins
Jonathan Reif, Daniel Dittler, Milapji Singh Gill, Tam\'as Farkas, Valentin Stegmaier, Felix Gehlhoff, Tobias Kleinert, Michael Weyrich
https://arxiv.org/abs/2506.17313

An Expert Survey on Models and Digital Twins
Digital Twins (DTs) are becoming increasingly vital for future industrial applications, enhancing monitoring, control, and optimization of physical assets. This enhancement is made possible by integrating various Digital Models (DMs) within DTs, which must interoperate to represent different system aspects and fulfill diverse application purposes. However, industry perspectives on the challenges and research needs for integrating these models are rarely obtained. Thus, this study conducts an ex…

Role of non-thermal processes in the quiescent and active millimeter spectrum of a young M-dwarf
Atul Mohan, Peter H. Hauschildt, Birgit Fuhrmeister, Surajit Mondal, Vladimir Airapetian, Sven Wedemeyer
https://arxiv.org/abs/2506.19779

Role of non-thermal processes in the quiescent and active millimeter spectrum of a young M-dwarf
Millimeter (mm) emission from F - M dwarfs (cool stars) primarily traces chromospheric activity, with thermal emission thought to dominate in quiescence. Despite the high chromospheric activity, the quiescent mm spectral fluence (mm-S($ν$)) of young (< 1 Gyr) M dwarfs (dMs) remain largely unexplored. We present the quiescent mm-S($ν$) of a young dM, ADLeo, observed around 94 GHz using the Northern Extended Millimetre Array (NOEMA). The observed quiescent mm-S($ν$) exceeds the thermal flux de…

A Correlation Between FRB Dispersion Measure and Foreground Large-Scale Structure
Maryam Hussaini, Liam Connor, Ralf M. Konietzka, Vikram Ravi, Jakob Faber, Kritti Sharma, Myles Sherman
https://arxiv.org/abs/2506.04186

A Correlation Between FRB Dispersion Measure and Foreground Large-Scale Structure
The distribution of baryons in the Universe remains a fundamental open question in astronomy, and the dispersion measure (DM) of Fast Radio Bursts (FRBs) serves as a valuable tool for probing this cosmic gas. We investigate the impact of the foreground cosmic web on FRB DMs using 61 localized FRBs and public galaxy catalogs. We test for the large-scale structure's impact on cosmological DM using two methods. First, we searched for a correlation between galaxy number density along the line of si…

Searching for radio pulsars in old open clusters from the Parkes archive
S. B. Zhang, J. J. Wei, X. Yang, S. Dai, J. S. Wang, L. Toomey, S. Q. Wang, G. Hobbs, X. F. Wu, L. Staveley-Smith
https://arxiv.org/abs/2506.19236

Searching for radio pulsars in old open clusters from the Parkes archive
Motivated by the discovery of a pulsar in the direction of the old open cluster NGC 6791, we conducted a search for radio pulsars in archival Parkes observations targeting similar old open clusters. We reprocessed 224 observations totalling 75.02 hours from four clusters: Theia 1661, NGC 6259, Pismis 3, and Trumpler 20. Our analysis identified five known pulsars and three new rotating radio transient (RRAT) candidates. By comparing the measured dispersion measures (DMs) with the expected DM val…

Dynamic Collaborative Material Distribution System for Intelligent Robots In Smart Manufacturing
Ziren Xiao, Ruxin Xiao, Chang Liu, Xinheng Wang
https://arxiv.org/abs/2506.11723

Dynamic Collaborative Material Distribution System for Intelligent Robots In Smart Manufacturing
The collaboration and interaction of multiple robots have become integral aspects of smart manufacturing. Effective planning and management play a crucial role in achieving energy savings and minimising overall costs. This paper addresses the real-time Dynamic Multiple Sources to Single Destination (DMS-SD) navigation problem, particularly with a material distribution case for multiple intelligent robots in smart manufacturing. Enumerated solutions, such as in \cite{xiao2022efficient}, tackle t…

Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks
Manyi Li, Renshuai Tao, Yufan Liu, Chuangchuang Tan, Haotong Qin, Bing Li, Yunchao Wei, Yao Zhao
https://arxiv.org/abs/2506.20548

Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks
With the rapid advancement of deep learning, particularly through generative adversarial networks (GANs) and diffusion models (DMs), AI-generated images, or ``deepfakes", have become nearly indistinguishable from real ones. These images are widely shared across Online Social Networks (OSNs), raising concerns about their misuse. Existing deepfake detection methods overlook the ``block effects" introduced by compression in OSNs, which obscure deepfake artifacts, and primarily focus on raw images,…

Parameterization and benchmarking of the Modified Marrone-Treanor Model for five-species air
Erik Torres, Thomas Gross, Graham V. Candler, Thomas E. Schwartzentruber
https://arxiv.org/abs/2506.20521

Parameterization and benchmarking of the Modified Marrone-Treanor Model for five-species air
We present updated parameters for five-species air to be used with the Modified Marrone-Treanor (MMT) air dissociation model. The vibrational relaxation and chemical reaction rates are derived from quasiclassical trajectory calculation (QCT) and direct molecular simulation (DMS) using ab initio potential energy surfaces (PESs). The resulting model and parameter set enable efficient computational fluid dynamics (CFD) simulations of high-temperature nonequilibrium five-species air (N2, O2, NO, N …

Doctor Approved: Generating Medically Accurate Skin Disease Images through AI-Expert Feedback
Janet Wang, Yunbei Zhang, Zhengming Ding, Jihun Hamm
https://arxiv.org/abs/2506.12323

Doctor Approved: Generating Medically Accurate Skin Disease Images through AI-Expert Feedback
Paucity of medical data severely limits the generalizability of diagnostic ML models, as the full spectrum of disease variability can not be represented by a small clinical dataset. To address this, diffusion models (DMs) have been considered as a promising avenue for synthetic image generation and augmentation. However, they frequently produce medically inaccurate images, deteriorating the model performance. Expert domain knowledge is critical for synthesizing images that correctly encode clin…