Tootfinder

Campus AI vs. Commercial AI: How Customizations Shape Trust and Usage of LLM as-a-Service Chatbots
Leon Hannig (University of Duisburg-Essen, Germany), Annika Bush (TU Dortmund University, Germany), Meltem Aksoy (TU Dortmund University, Germany), Steffen Becker (Ruhr University Bochum, Germany), Greta Ontrup (University of Duisburg-Essen, Germany)
https://

Campus AI vs. Commercial AI: How Customizations Shape Trust and Usage of LLM as-a-Service Chatbots
As the use of LLM chatbots by students and researchers becomes more prevalent, universities are pressed to develop AI strategies. One strategy that many universities pursue is to customize pre-trained LLM as-a-service (LLMaaS). While most studies on LLMaaS chatbots prioritize technical adaptations, we focus on psychological effects of user-salient customizations, such as interface changes. We assume that such customizations influence users' perception of the system and are therefore important i…

From Data to Diagnosis: A Large, Comprehensive Bone Marrow Dataset and AI Methods for Childhood Leukemia Prediction
Henning H\"ofener (Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany), Farina Kock (Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany), Martina Pontones (Department of Pediatrics and Adolescent Medicine, University Hospital Erlangen, Erlangen, Germany), Tabita Ghete (Department of Pediatrics and Adolescent Medicine, University Hospital E…

From Data to Diagnosis: A Large, Comprehensive Bone Marrow Dataset and AI Methods for Childhood Leukemia Prediction
Leukemia diagnosis primarily relies on manual microscopic analysis of bone marrow morphology supported by additional laboratory parameters, making it complex and time consuming. While artificial intelligence (AI) solutions have been proposed, most utilize private datasets and only cover parts of the diagnostic pipeline. Therefore, we present a large, high-quality, publicly available leukemia bone marrow dataset spanning the entire diagnostic process, from cell detection to diagnosis. Using this…

Right-Side-Out: Learning Zero-Shot Sim-to-Real Garment Reversal
Chang Yu, Siyu Ma, Wenxin Du, Zeshun Zong, Han Xue, Wendi Chen, Cewu Lu, Yin Yang, Xuchen Han, Joseph Masterjohn, Alejandro Castro, Chenfanfu Jiang
https://arxiv.org/abs/2509.15953

Right-Side-Out: Learning Zero-Shot Sim-to-Real Garment Reversal
Turning garments right-side out is a challenging manipulation task: it is highly dynamic, entails rapid contact changes, and is subject to severe visual occlusion. We introduce Right-Side-Out, a zero-shot sim-to-real framework that effectively solves this challenge by exploiting task structures. We decompose the task into Drag/Fling to create and stabilize an access opening, followed by Insert&Pull to invert the garment. Each step uses a depth-inferred, keypoint-parameterized bimanual primitive…

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 …

PoliTok-DE: A Multimodal Dataset of Political TikToks and Deletions From Germany
Tomas Ruiz, Andreas Nanz, Ursula Kristin Schmid, Carsten Schwemmer, Yannis Theocharis, Diana Rieger
https://arxiv.org/abs/2509.15860

PoliTok-DE: A Multimodal Dataset of Political TikToks and Deletions From Germany
We present PoliTok-DE, a large-scale multimodal dataset (video, audio, images, text) of TikTok posts related to the 2024 Saxony state election in Germany. The corpus contains over 195,000 posts published between 01.07.2024 and 30.11.2024, of which over 18,000 (17.3%) were subsequently deleted from the platform. Posts were identified via the TikTok research API and complemented with web scraping to retrieve full multimodal media and metadata. PoliTok-DE supports computational social science acro…

Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram
Xiaogang Yang (NSLS-II, Brookhaven National Laboratory, Upton, USA), Dawit Hailu (Institute of Materials Physics, Helmholtz-Zentrum Hereon, Geesthacht, Germany), Vojt\v{e}ch Kulvait (Institute of Materials Physics, Helmholtz-Zentrum Hereon, Geesthacht, Germany), Thomas Jentschke (Institute of Materials Physics, Helmholtz-Zentrum Hereon, Geesthacht, Germany), Silja Flenner (Institute of…

Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram
X-ray phase contrast imaging significantly improves the visualization of structures with weak or uniform absorption, broadening its applications across a wide range of scientific disciplines. Propagation-based phase contrast is particularly suitable for time- or dose-critical in vivo/in situ/operando (tomography) experiments because it requires only a single intensity measurement. However, the phase information of the wave field is lost during the measurement and must be recovered. Conventional…

Precise Predictions for Event Shapes in Hadronic Higgs Decays
Elliot Fox, Aude Gehrmann-De Ridder, Thomas Gehrmann, Nigel Glover, Matteo Marcoli, Christian T. Preuss
https://arxiv.org/abs/2508.14282

Precise Predictions for Event Shapes in Hadronic Higgs Decays
We present NNLO QCD predictions for a wide range of event-shape observables in hadronic Higgs decays, taking into account the two dominant decay modes $H\to gg$ and $H\to b\bar{b}$. Specifically, we consider the six classical event shapes thrust, heavy jet mass, $C$-parameter, total and wide jet broadening, and the three-jet resolution $y_{23}$ in the Durham algorithm.We also present results for the soft-drop variant of thrust. Decays of the Higgs boson to two gluons are treated in the heavy-to…

Response and Prompt Evaluation to Prevent Parasocial Relationships with Chatbots
Emma Rath, Stuart Armstrong, Rebecca Gorman
https://arxiv.org/abs/2508.15748 https://

Response and Prompt Evaluation to Prevent Parasocial Relationships with Chatbots
The development of parasocial relationships with AI agents has severe, and in some cases, tragic effects for human well-being. Yet preventing such dynamics is challenging: parasocial cues often emerge gradually in private conversations, and not all forms of emotional engagement are inherently harmful. We address this challenge by introducing a simple response evaluation framework, created by repurposing a state-of-the-art language model, that evaluates ongoing conversations for parasocial cues …

Principle Methods of Rendering Non-equivalent Words from Uzbek and Dari to Russian and English
Mohammad Ibrahim Qani
https://arxiv.org/abs/2508.15453 https://

Principle Methods of Rendering Non-equivalent Words from Uzbek and Dari to Russian and English
These pure languages understanding directly relates to translation knowledge where linguists and translators need to work and research to eradicate misunderstanding. Misunderstandings mostly appear in non-equivalent words because there are different local and internal words like food, garment, cultural and traditional words and others in every notion. Truly, most of these words do not have equivalent in the target language and these words need to be worked and find their equivalent in the targe…

XAI-Driven Spectral Analysis of Cough Sounds for Respiratory Disease Characterization
Patricia Amado-Caballero, Luis Miguel San-Jos\'e-Revuelta, Mar\'ia Dolores Aguilar-Garc\'ia, Jos\'e Ram\'on Garmendia-Leiza, Carlos Alberola-L\'opez, Pablo Casaseca-de-la-Higuera
https://arxiv.org/abs/2508.14949

XAI-Driven Spectral Analysis of Cough Sounds for Respiratory Disease Characterization
This paper proposes an eXplainable Artificial Intelligence (XAI)-driven methodology to enhance the understanding of cough sound analysis for respiratory disease management. We employ occlusion maps to highlight relevant spectral regions in cough spectrograms processed by a Convolutional Neural Network (CNN). Subsequently, spectral analysis of spectrograms weighted by these occlusion maps reveals significant differences between disease groups, particularly in patients with COPD, where cough patt…