Tootfinder

Public Evaluation on Potential Social Impacts of Fully Autonomous Cybernetic Avatars for Physical Support in Daily-Life Environments: Large-Scale Demonstration and Survey at Avatar Land
Lotfi El Hafi, Kazuma Onishi, Shoichi Hasegawa, Akira Oyama, Tomochika Ishikawa, Masashi Osada, Carl Tornberg, Ryoma Kado, Kento Murata, Saki Hashimoto, Sebastian Carrera Villalobos, Akira Taniguchi, Gustavo Alfonso Garcia Ricardez, Yoshinobu Hagiwara, Tatsuya Aoki, Kensuke Iwata, Takato Horii, Yukiko H…

Public Evaluation on Potential Social Impacts of Fully Autonomous Cybernetic Avatars for Physical Support in Daily-Life Environments: Large-Scale Demonstration and Survey at Avatar Land
Cybernetic avatars (CAs) are key components of an avatar-symbiotic society, enabling individuals to overcome physical limitations through virtual agents and robotic assistants. While semi-autonomous CAs intermittently require human teleoperation and supervision, the deployment of fully autonomous CAs remains a challenge. This study evaluates public perception and potential social impacts of fully autonomous CAs for physical support in daily life. To this end, we conducted a large-scale demonstr…

A spherical hydrodynamical model of cosmic voids in {\Lambda}CDM and beyond
Tommaso Moretti, Giovanni Verza, Noemi Frusciante, Franceso Pace
https://arxiv.org/abs/2507.14120

A spherical hydrodynamical model of cosmic voids in ΛCDM and beyond
Cosmic voids have emerged as powerful probes for cosmology, providing complementary information on the large-scale structure of the universe. We present the first application of a hydrodynamical framework to model the evolution of cosmic voids. This approach offers a physically intuitive characterization of void dynamics and can naturally be applied to non-standard cosmologies. We derive the cosmology-dependent mapping that relates the linear (Lagrangian) and fully non-linear (Eulerian) evoluti…

Rethinking the Embodied Gap in Vision-and-Language Navigation: A Holistic Study of Physical and Visual Disparities
Liuyi Wang, Xinyuan Xia, Hui Zhao, Hanqing Wang, Tai Wang, Yilun Chen, Chengju Liu, Qijun Chen, Jiangmiao Pang
https://arxiv.org/abs/2507.13019

Rethinking the Embodied Gap in Vision-and-Language Navigation: A Holistic Study of Physical and Visual Disparities
Recent Vision-and-Language Navigation (VLN) advancements are promising, but their idealized assumptions about robot movement and control fail to reflect physically embodied deployment challenges. To bridge this gap, we introduce VLN-PE, a physically realistic VLN platform supporting humanoid, quadruped, and wheeled robots. For the first time, we systematically evaluate several ego-centric VLN methods in physical robotic settings across different technical pipelines, including classification mod…

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates
Carlos De La Vega Martin, Rodrigo Diaz Fernandez, Mark Sandler
https://arxiv.org/abs/2507.12563

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates
Physical modelling synthesis aims to generate audio from physical simulations of vibrating structures. Thin elastic plates are a common model for drum membranes. Traditional numerical methods like finite differences and finite elements offer high accuracy but are computationally demanding, limiting their use in real-time audio applications. This paper presents a comparative analysis of neural network-based approaches for solving the vibration of nonlinear elastic plates. We evaluate several sta…

A Hidden Pulse: Uncovering a New Timing Signal in Cygnus X-1 with AstroSat
Sandeep K. Rout, Federico Garcia, Mariano Mendez, Abhay Kumar, Santosh Vadawale, David M. Russell, Pei Jin
https://arxiv.org/abs/2507.13884

A Hidden Pulse: Uncovering a New Timing Signal in Cygnus X-1 with AstroSat
The study of fast variability properties in X-ray binaries advances our understanding of the physical processes and geometric properties of the accretion flow around the compact object. In this work, we study the evolution of the timing properties of Cygnus X-1 with AstroSat/LAXPC, during the transition of the source from the hard to soft state in 2017. We use a novel frequency-segmented technique to fit simultaneously the cross spectra and part of the power spectra and coherence function with …

H-NeiFi: Non-Invasive and Consensus-Efficient Multi-Agent Opinion Guidance
Shijun Guo, Haoran Xu, Yaming Yang, Ziyu Guan, Wei Zhao, Xinyi Zhang, Yishan Song, Jiwei Chen
https://arxiv.org/abs/2507.13370

H-NeiFi: Non-Invasive and Consensus-Efficient Multi-Agent Opinion Guidance
The openness of social media enables the free exchange of opinions, but it also presents challenges in guiding opinion evolution towards global consensus. Existing methods often directly modify user views or enforce cross-group connections. These intrusive interventions undermine user autonomy, provoke psychological resistance, and reduce the efficiency of global consensus. Additionally, due to the lack of a long-term perspective, promoting local consensus often exacerbates divisions at the mac…

Variations in Volatile-Driven Activity of Comet C/2017 K2 (PanSTARRS) Revealed by Long-Term Multi-Wavelength Observations
S. Hmiddouch, E. Jehin, M. Lippi, M. Vander Donckt, K. Aravind, D. Hutsem\'ekers, J. Manfroid, A. Jabiri, Y. Moulane, Z. Benkhaldoun
https://arxiv.org/abs/2507.13451

Variations in Volatile-Driven Activity of Comet C/2017 K2 (PanSTARRS) Revealed by Long-Term Multi-Wavelength Observations
Context. A comprehensive study of comets over a wide heliocentric distance range helps us understand the physical processes driving their activity and reveals compositional differences across dynamical groups. C/2017 K2 (PANSTARRS) is a Dynamically New Oort Cloud comet (DNC) that showed activity as far as 23.75 au and displayed a CO-rich coma at 6.72 au, making it a key object to investigate pre- and post-perihelion behavior. Aims. We aim to study the long-term activity evolution and chemical…

Challenges in the nonlinear evolution of unequal mass binaries in sGB gravity
Llibert Arest\'e Sal\'o, Daniela D. Doneva, Katy Clough, Pau Figueras, Stoytcho S. Yazadjiev
https://arxiv.org/abs/2507.13046

Challenges in the nonlinear evolution of unequal mass binaries in sGB gravity
It has only recently become possible to simulate the full nonlinear dynamics of binary black holes in scalar-Gauss-Bonnet theories of gravity. The simulations remain technically challenging and evolutions of unequal mass binaries in particular have been difficult to follow through the merger. Even when the merger is successful, accurately quantifying the physical dephasing, as opposed to contributions from transients in the initial data and gauge adjustments, remains difficult. We show the firs…

Simulation of parametrized cardiac electrophysiology in three dimensions using physics-informed neural networks
Roshan Antony Gomez, Julien St\"ocker, Bar{\i}\c{s} Cans{\i}z, Michael Kaliske
https://arxiv.org/abs/2506.15405

Simulation of parametrized cardiac electrophysiology in three dimensions using physics-informed neural networks
Physics-informed neural networks (PINNs) are extensively used to represent various physical systems across multiple scientific domains. The same can be said for cardiac electrophysiology, wherein fully-connected neural networks (FCNNs) have been employed to predict the evolution of an action potential in a 2D space following the two-parameter phenomenological Aliev-Panfilov (AP) model. In this paper, the training behaviour of PINNs is investigated to determine optimal hyperparameters to predict…

Humans are more gullible than LLMs in believing common psychological myths
Bevan Koopman, Guido Zuccon
https://arxiv.org/abs/2507.12296 https://

Humans are more gullible than LLMs in believing common psychological myths
Despite widespread debunking, many psychological myths remain deeply entrenched. This paper investigates whether Large Language Models (LLMs) mimic human behaviour of myth belief and explores methods to mitigate such tendencies. Using 50 popular psychological myths, we evaluate myth belief across multiple LLMs under different prompting strategies, including retrieval-augmented generation and swaying prompts. Results show that LLMs exhibit significantly lower myth belief rates than humans, thoug…