Tootfinder

We are thrilled to take part in this year's Ars Electronica Festival with multiple arts installations and interventions, conveying what digital identity is and why everybody should care: https://ars.electronica.art/panic/en/view/digital-shadows-22a38…

Digital Shadows | Ars Electronica Festival 2025: Panic
Digital Shadows confronts visitors with their digital self—copied, measured, analyzed. An experiment on data power, visibility, and control in the digital age.

"The Bib Record in the Age of Digital Reproduction" https://journal.radicallibrarianship.org/index.php/journal/article/view/135
"Taking both structural and thematic inspiration from Walter Benjamin’s “The Work of Art in the Age of Mechanic…

RiverEcho: Real-Time Interactive Digital System for Ancient Yellow River Culture
Haofeng Wang, Yilin Guo, Zehao Li, Tong Yue, Yizong Wang, Enci Zhang, Rongqun Lin, Feng Gao, Shiqi Wang, Siwei Ma
https://arxiv.org/abs/2506.21865

RiverEcho: Real-Time Interactive Digital System for Ancient Yellow River Culture
The Yellow River is China's mother river and a cradle of human civilization. The ancient Yellow River culture is, moreover, an indispensable part of human art history. To conserve and inherit the ancient Yellow River culture, we designed RiverEcho, a real-time interactive system that responds to voice queries using a large language model and a cultural knowledge dataset, delivering explanations through a talking-head digital human. Specifically, we built a knowledge database focused on the anci…

Equally entangled multiqubit states
Francisco Albarr\'an-Arriagada, Guillermo Romero, Juan Carlos Retamal
https://arxiv.org/abs/2508.20770 https://arxi…

Equally entangled multiqubit states
We present a protocol for generating multiqubit quantum states with translationally invariant pairwise entanglement. Our approach is tailored for digital quantum computers with restricted qubit connectivity, a common limitation in state-of-the-art hardware platforms. We examine two configurations: star connectivity, which enables rotationally invariant entanglement, and linear connectivity, which achieves translationally invariant entanglement. For the linear configuration, we use a variant of …

Layered Interactions: Exploring Non-Intrusive Digital Craftsmanship Design Through Lacquer Art Interfaces
Yan Dong, Hanjie Yu, Yanran Chen, Zipeng Zhang, Qiong Wu
https://arxiv.org/abs/2507.17430

Layered Interactions: Exploring Non-Intrusive Digital Craftsmanship Design Through Lacquer Art Interfaces
Integrating technology with the distinctive characteristics of craftsmanship has become a key issue in the field of digital craftsmanship. This paper introduces Layered Interactions, a design approach that seamlessly merges Human-Computer Interaction (HCI) technologies with traditional lacquerware craftsmanship. By leveraging the multi-layer structure and material properties of lacquerware, we embed interactive circuits and integrate programmable hardware within the layers, creating tangible in…

If you get an invite to this generative art software engineering call, note that if you submit something and it gets accepted, as far as I can tell it would cost you $3000 in open access fees... unless you want it to languish behind a paywall (you'd then only be allowed to share an unedited draft, and even then would have to advertise the paywall on it). They don't seem to want to make this clear in their call.

💡 Wie werden die Querverbindungen zwischen kulturellen Ressourcen in @… hergestellt?
🚀 Bei der #DH2025 in Lissabon zeigen unsere 4Culture-Kolleginnen @… und Linnaea Sö…

TONUS: Neuromorphic human pose estimation for artistic sound co-creation
Jules Lecomte (Fortiss GmbH, Munich, Germany), Konrad Zinner (Hochschule f\"ur Musik und Theater Munich, Germany), Michael Neumeier (Fortiss GmbH, Munich, Germany), Axel von Arnim (Fortiss GmbH, Munich, Germany)
https://arxiv.org/abs/2507.15734

TONUS: Neuromorphic human pose estimation for artistic sound co-creation
Human machine interaction is a huge source of inspiration in today's media art and digital design, as machines and humans merge together more and more. Its place in art reflects its growing applications in industry, such as robotics. However, those interactions often remains too technical and machine-driven for people to really engage into. On the artistic side, new technologies are often not explored in their full potential and lag a bit behind, so that state-of-the-art research does not make …

The Rhythm of Tai Chi: Revitalizing Cultural Heritage in Virtual Reality through Interactive Visuals
Xianghan Wang
https://arxiv.org/abs/2508.16605 https://

The Rhythm of Tai Chi: Revitalizing Cultural Heritage in Virtual Reality through Interactive Visuals
The Rhythm of Tai Chi reinterprets the ancient Chinese martial art as a dynamic, interactive virtual reality (VR) experience. By leveraging computer vision and multimedia technologies, the project transforms Tai Chi's philosophy and movements into an immersive digital form. Real-time motion tracking captures user gestures, while visual feedback systems simulate the flow of Qi, enabling an intuitive and engaging practice environment. Beyond technological innovation, this work bridges traditional…

Oh wow I just found the Web page of a photographer focusing on flowers.
This style is adorable!
#photography

LUCY KETCHUM
Fine art floral photography by Lucy Ketchum. I offer private mentoring sessions to photographers of all levels. In my shop you can find my floral prints for sale as well as greeting cards and a few digital products to download like wallpapers for your computer and phone.

wip #art

Approaching the Source of Symbol Grounding with Confluent Reductions of Abstract Meaning Representation Directed Graphs
Nicolas Goulet, Alexandre Blondin Mass\'e, Moussa Abdendi
https://arxiv.org/abs/2508.11068

Approaching the Source of Symbol Grounding with Confluent Reductions of Abstract Meaning Representation Directed Graphs
Abstract meaning representation (AMR) is a semantic formalism used to represent the meaning of sentences as directed acyclic graphs. In this paper, we describe how real digital dictionaries can be embedded into AMR directed graphs (digraphs), using state-of-the-art pre-trained large language models. Then, we reduce those graphs in a confluent manner, i.e. with transformations that preserve their circuit space. Finally, the properties of these reduces digraphs are analyzed and discussed in relat…

Making Effective Decisions: Machine Learning and the Ecogame in 1970
Catherine Mason
https://arxiv.org/abs/2508.07027 https://arxiv.org/pdf/2508.07027

Making Effective Decisions: Machine Learning and the Ecogame in 1970
This paper considers Ecogame, an innovative art project of 1970, whose creators believed in a positive vision of a technological future; an understanding, posited on cybernetics, of a future that could be participatory via digital means, and therefore more democratised. Using simulation and early machine learning techniques over a live network, Ecogame combined the power of visual art with cybernetic concepts of adaptation, feedback, and control to propose that behaviour had implications for th…

MUTE-DSS: A Digital-Twin-Based Decision Support System for Minimizing Underwater Radiated Noise in Ship Voyage Planning
Akash Venkateshwaran, Indu Kant Deo, Rajeev K. Jaiman
https://arxiv.org/abs/2508.01907

MUTE-DSS: A Digital-Twin-Based Decision Support System for Minimizing Underwater Radiated Noise in Ship Voyage Planning
We present a novel MUTE-DSS, a digital-twin-based decision support system for minimizing underwater radiated noise (URN) during ship voyage planning. It is a ROS2-centric framework that integrates state-of-the-art acoustic models combining a semi-empirical reference spectrum for near-field modeling with 3D ray tracing for propagation losses for far-field modeling, offering real-time computation of the ship noise signature, alongside a data-driven Southern resident killer whale distribution mode…

Kibble-Zurek dynamical scaling hypothesis in the Google analog-digital quantum simulator of the $XX$ model
Yintai Zhang, Francis A. Bayocboc Jr., Jacek Dziarmaga
https://arxiv.org/abs/2506.10771

Kibble-Zurek dynamical scaling hypothesis in the Google analog-digital quantum simulator of the $XX$ model
The state-of-the-art tensor networks are employed to simulate the Hamiltonian ramp in the analog-digital quantum simulation of the quantum phase transition to the quasi-long-range ordered phase of the 2D square-lattice $XX$ model [Nature 638, 79 (2025)]. We focus on the quantum Kibble-Zurek (KZ) mechanism near the quantum critical point. Using the infinite projected entangled pair state (iPEPS), we simulate an infinite lattice and demonstrate the KZ scaling hypothesis for the $XX$ correlations …

Plant-Centric Metaverse: A Biocentric-Creation Framework for Ecological Art and Digital Symbiosis
Ze Gao, Mengyao Guo, Zheng Wang, Xiaolin Zhang, Sihuang Man
https://arxiv.org/abs/2508.04391

Plant-Centric Metaverse: A Biocentric-Creation Framework for Ecological Art and Digital Symbiosis
Digital ecological art represents an emergent frontier where biological media converge with virtual environments. This study examines the paradigm shift from anthropocentric to plant-centered artistic narratives within the metaverse, contextualizing how digital platforms transform ecological expression. However, current frameworks fail to systematically guide artists in leveraging plant agency for digital symbiosis that transcends human-centered creation. We propose the Biocentric-Creation Tran…

This https://arxiv.org/abs/2504.16571 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

LaSDVS : A Post-Quantum Secure Compact Strong-Designated Verifier Signature
Digital signatures are fundamental cryptographic primitives that ensure the authenticity and integrity of digital communication. However, in scenarios involving sensitive interactions -- such as e-voting or e-cash -- there is a growing need for more controlled signing mechanisms. Strong-Designated Verifier Signature (SDVS) offers such control by allowing the signer to specify and restrict the verifier of a signature. The existing state-of-the-art SDVS are mostly based on number-theoretic hardne…

Learning to cluster neuronal function
Nina S. Nellen, Polina Turishcheva, Michaela Vystr\v{c}ilov\'a, Shashwat Sridhar, Tim Gollisch, Andreas S. Tolias, Alexander S. Ecker
https://arxiv.org/abs/2506.03293

Learning to cluster neuronal function
Deep neural networks trained to predict neural activity from visual input and behaviour have shown great potential to serve as digital twins of the visual cortex. Per-neuron embeddings derived from these models could potentially be used to map the functional landscape or identify cell types. However, state-of-the-art predictive models of mouse V1 do not generate functional embeddings that exhibit clear clustering patterns which would correspond to cell types. This raises the question whether th…

A Fast Unsupervised Scheme for Polygonal Approximation
Bimal Kumar Ray
https://arxiv.org/abs/2506.04664 https://arxiv.org/pdf/2506.04…

A Fast Unsupervised Scheme for Polygonal Approximation
This paper proposes a fast and unsupervised scheme for a polygonal approximation of a closed digital curve. It is demonstrated that the approximation scheme is faster than state-of-the-art approximation and is competitive with the same in Rosin's measure and in its aesthetic aspect. The scheme comprises of three phases: initial segmentation, iterative vertex insertion, and iterative merging, followed by vertex adjustment. The initial segmentation is used to detect sharp turnings - the vertices …

Verified Language Processing with Hybrid Explainability: A Technical Report
Oliver Robert Fox, Giacomo Bergami, Graham Morgan
https://arxiv.org/abs/2507.05017

Verified Language Processing with Hybrid Explainability: A Technical Report
The volume and diversity of digital information have led to a growing reliance on Machine Learning techniques, such as Natural Language Processing, for interpreting and accessing appropriate data. While vector and graph embeddings represent data for similarity tasks, current state-of-the-art pipelines lack guaranteed explainability, failing to determine similarity for given full texts accurately. These considerations can also be applied to classifiers exploiting generative language models with …

Hate in Plain Sight: On the Risks of Moderating AI-Generated Hateful Illusions
Yiting Qu, Ziqing Yang, Yihan Ma, Michael Backes, Savvas Zannettou, Yang Zhang
https://arxiv.org/abs/2507.22617

Hate in Plain Sight: On the Risks of Moderating AI-Generated Hateful Illusions
Recent advances in text-to-image diffusion models have enabled the creation of a new form of digital art: optical illusions--visual tricks that create different perceptions of reality. However, adversaries may misuse such techniques to generate hateful illusions, which embed specific hate messages into harmless scenes and disseminate them across web communities. In this work, we take the first step toward investigating the risks of scalable hateful illusion generation and the potential for bypa…

Modeling Interactive Narrative Systems: A Formal Approach
Jules Clerc, Domitile Lourdeaux, Mohamed Sallak, Johann Barbier, Marc Ravaine
https://arxiv.org/abs/2508.05653 https://…

Modeling Interactive Narrative Systems: A Formal Approach
Interactive Narrative Systems (INS) have revolutionized digital experiences by empowering users to actively shape their stories, diverging from traditional passive storytelling. However, the field faces challenges due to fragmented research efforts and diverse system representations. This paper introduces a formal representation framework for INS, inspired by diverse approaches from the state of the art. By providing a consistent vocabulary and modeling structure, the framework facilitates the …