Tootfinder

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems
Frederik Vandeputte
https://arxiv.org/abs/2508.15411 https://

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems
Generative AI (GenAI) has emerged as a transformative technology, demonstrating remarkable capabilities across diverse application domains. However, GenAI faces several major challenges in developing reliable and efficient GenAI-empowered systems due to its unpredictability and inefficiency. This paper advocates for a paradigm shift: future GenAI-native systems should integrate GenAI's cognitive capabilities with traditional software engineering principles to create robust, adaptive, and effici…

NASA and IBM release Surya, an open-source AI model trained on over a decade's worth of NASA solar data to predict solar flares and winds (Peter Hall/MIT Technology Review)
https://www.technologyreview.com/2025/08/20/1122163/nasa-ibm-ai-predict-solar-…

NASA’s new AI model can predict when a solar storm may strike
Surya, an AI model developed by NASA and IBM, tries to find hidden patterns in solar data to detect solar flares and winds.

Tao-Technology for Teen Mobile Use: Harmonizing Adaptation, Autonomy, and Reflection
Pengyu Zhu, Janghee Cho
https://arxiv.org/abs/2507.12204 https://

Tao-Technology for Teen Mobile Use: Harmonizing Adaptation, Autonomy, and Reflection
Adolescents' mobile technology use is often regulated through rigid control mechanisms that fail to account for their autonomy and natural usage patterns. Drawing on Taoist philosophy, particularly Wu Wei, Yin-Yang, and Zi Ran, this position paper proposes Tao-Technology, a self-organizing, adaptive regulatory framework. Integrating insights from Reflective Informatics and Information Ecologies, we explore how mobile technology can dynamically adjust to context while fostering self-reflection a…

The Ethics of Generative AI in Anonymous Spaces: A Case Study of 4chan's /pol/ Board
Parth Gaba, Emiliano De Cristofaro
https://arxiv.org/abs/2506.14191

The Ethics of Generative AI in Anonymous Spaces: A Case Study of 4chan's /pol/ Board
This paper presents a characterization of AI-generated images shared on 4chan, examining how this anonymous online community is (mis-)using generative image technologies. Through a methodical data collection process, we gathered 900 images from 4chan's /pol/ (Politically Incorrect) board, which included the label "/mwg/" (memetic warfare general), between April and July 2024, identifying 66 unique AI-generated images. The analysis reveals concerning patterns in the use of this technology, with …

Deep Learning in Classical and Quantum Physics
Timothy Heightman, Marcin P{\l}odzie\'n
https://arxiv.org/abs/2508.10666 https://arxiv.org/pdf/2508.1066…

Deep Learning in Classical and Quantum Physics
Scientific progress is tightly coupled to the emergence of new research tools. Today, machine learning (ML)-especially deep learning (DL)-has become a transformative instrument for quantum science and technology. Owing to the intrinsic complexity of quantum systems, DL enables efficient exploration of large parameter spaces, extraction of patterns from experimental data, and data-driven guidance for research directions. These capabilities already support tasks such as refining quantum control p…

Signals and Symptoms: ICS Attack Dataset From Railway Cyber Range
Anis Yusof, Yuancheng Liu, Niklaus Kang, Choon Meng Seah, Zhenkai Liang, Ee-Chien Chang
https://arxiv.org/abs/2507.01768

Signals and Symptoms: ICS Attack Dataset From Railway Cyber Range
The prevalence of cyberattacks on Industrial Control Systems (ICS) has highlighted the necessity for robust security measures and incident response to protect critical infrastructure. This is prominent when Operational Technology (OT) systems undergo digital transformation by integrating with Information Technology (IT) systems to enhance operational efficiency, adaptability, and safety. To support analysts in staying abreast of emerging attack patterns, there is a need for ICS datasets that re…

The Manipulative Power of Voice Characteristics: Investigating Deceptive Patterns in Mandarin Chinese Female Synthetic Speech
Shuning Zhang (Tsinghua University, Beijing, China), Han Chen (Wuhan Institute of Technology, Wuhan, China), Yabo Wang (Tsinghua University, Beijing, China), Yiqun Xu (Tsinghua University, Beijing, China), Jiaqi Bai (Tsinghua University, Beijing, China), Yuanyuan Wu (Shanghai Jiaotong University, Shanghai, China), Shixuan Li (Tsinghua University, Beijing, China)…

The Manipulative Power of Voice Characteristics: Investigating Deceptive Patterns in Mandarin Chinese Female Synthetic Speech
Pervasive voice interaction enables deceptive patterns through subtle voice characteristics, yet empirical investigation into this manipulation lags behind, especially within major non-English language contexts. Addressing this gap, our study presents the first systematic investigation into voice characteristic-based dark patterns employing female synthetic voices in Mandarin Chinese. This focus is crucial given the prevalence of female personas in commercial assistants and the prosodic signifi…

We in Game Workers Unite Ireland stand in solidarity with Animation Workers of Ireland, and the international trade union coalition happening to organise against the threat of AI in the animation industry, and we support their call to acton.
Join them Thursday 12 June at 14:00 at the Pâquier in Annecy!!
#Animation

Mathematical model of blood coagulation during endovenous laser therapy
Anna A. Andreeva (Moscow Institute of Physics and Technology), Konstantin A. Klochkov (Moscow Institute of Physics and Technology), Alexey I. Lobanov (Moscow Institute of Physics and Technology)
https://arxiv.org/abs/2507.20401…

Mathematical model of blood coagulation during endovenous laser therapy
Endovenous laser therapy (ELT) as a minimally invasive procedure for ablation of large superficial veins, nevertheless, can cause complications of thrombotic nature. In this regard, the study of the main patterns of thrombus formation during ELT and modelling of endovenous heat-induced thrombosis (EHIT) is relevant. Based on the assumption of diffusion limiting of biochemical processes occurring during the coagulation of blood, by recalculating the reaction rates according to the Stokes-Einstei…

Data Driven Insights into Composition Property Relationships in FCC High Entropy Alloys
Nicolas Flores, Daniel Salas Mula, Wenle Xu, Sahu Bibhu, Daniel Lewis, Alexandra Eve Salinas, Samantha Mitra, Raj Mahat, Surya R. Kalidindi, Justin Wilkerson, James Paramore, Ankit Srivastiva, George Pharr, Douglas Allaire, Ibrahim Karaman, Brady Butler, Vahid Attari, Raymundo Arroyave

Data Driven Insights into Composition Property Relationships in FCC High Entropy Alloys
Structural High Entropy Alloys (HEAs) are crucial in advancing technology across various sectors, including aerospace, automotive, and defense industries. However, the scarcity of integrated chemistry, process, structure, and property data presents significant challenges for predictive property modeling. Given the vast design space of these alloys, uncovering the underlying patterns is essential yet difficult, requiring advanced methods capable of learning from limited and heterogeneous dataset…

This https://arxiv.org/abs/2503.09257 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

A Global Dataset Mapping the AI Innovation from Academic Research to Industrial Patents
In the rapidly evolving field of artificial intelligence (AI), mapping innovation patterns and understanding effective technology transfer from research to applications are essential for economic growth. However, existing data infrastructures suffer from fragmentation, incomplete coverage, and insufficient evaluative capacity. Here, we present DeepInnovationAI, a comprehensive global dataset containing three structured files. DeepPatentAI.csv: Contains 2,356,204 patent records with 8 field-spec…

Show Me Your Best Side: Characteristics of User-Preferred Perspectives for 3D Graph Drawings
Lucas Joos, Gavin J. Mooney, Maximilian T. Fischer, Daniel A. Keim, Falk Schreiber, Helen C. Purchase, Karsten Klein
https://arxiv.org/abs/2506.09212

Show Me Your Best Side: Characteristics of User-Preferred Perspectives for 3D Graph Drawings
The visual analysis of graphs in 3D has become increasingly popular, accelerated by the rise of immersive technology, such as augmented and virtual reality. Unlike 2D drawings, 3D graph layouts are highly viewpoint-dependent, making perspective selection critical for revealing structural and relational patterns. Despite its importance, there is limited empirical evidence guiding what constitutes an effective or preferred viewpoint from the user's perspective. In this paper, we present a systema…

Mind the Dark: A Gamified Exploration of Deceptive Design Awareness for Children in the Digital Age
Noverah Khan, Hira Eiraj Daud, Suleman Shahid
https://arxiv.org/abs/2506.23017 …

Mind the Dark: A Gamified Exploration of Deceptive Design Awareness for Children in the Digital Age
This paper addresses the critical issue of deceptive design elements prevalent in technology, and their potential impact on children. Recent research highlights the impact of dark patterns on adults and adolescents, while studies involving children are scarce. In an era where children wield greater independence with digital devices, their vulnerability to dark patterns amplifies without early education. Our findings show a significant positive impact of dark pattern education on children's awar…

MeloKids: Multisensory VR System to Enhance Speech and Motor Coordination in Children with Hearing Loss
Yichen Yu, Qiaoran Wang
https://arxiv.org/abs/2507.18619 https://

MeloKids: Multisensory VR System to Enhance Speech and Motor Coordination in Children with Hearing Loss
Children with hearing impairments face ongoing challenges in language and motor development. This study explores how multi-sensory feedback technology based on virtual reality (VR), integrating auditory, visual, and tactile stimuli, can enhance rehabilitation outcomes. Using functional near-infrared spectroscopy (fNIRS) technology, we assessed cortical activation patterns in children during pitch-matching tasks across different interaction modes. Our findings aim to provide evidence for designi…

Mapping Student-AI Interaction Dynamics in Multi-Agent Learning Environments: Supporting Personalised Learning and Reducing Performance Gaps
Zhanxin Hao, Jie Cao, Ruimiao Li, Jifan Yu, Zhiyuan Liu, Yu Zhang
https://arxiv.org/abs/2506.02993

Mapping Student-AI Interaction Dynamics in Multi-Agent Learning Environments: Supporting Personalised Learning and Reducing Performance Gaps
Multi-agent AI systems, which simulate diverse instructional roles such as teachers and peers, offer new possibilities for personalized and interactive learning. Yet, student-AI interaction patterns and their pedagogical implications remain unclear. This study explores how university students engaged with multiple AI agents, and how these interactions influenced cognitive outcomes (learning gains) and non-cognitive factors (motivation, technology acceptance). Based on MAIC, an online learning p…