Tootfinder

Scaling Truth: The Confidence Paradox in AI Fact-Checking
Ihsan A. Qazi, Zohaib Khan, Abdullah Ghani, Agha A. Raza, Zafar A. Qazi, Wassay Sajjad, Ayesha Ali, Asher Javaid, Muhammad Abdullah Sohail, Abdul H. Azeemi
https://arxiv.org/abs/2509.08803

Scaling Truth: The Confidence Paradox in AI Fact-Checking
The rise of misinformation underscores the need for scalable and reliable fact-checking solutions. Large language models (LLMs) hold promise in automating fact verification, yet their effectiveness across global contexts remains uncertain. We systematically evaluate nine established LLMs across multiple categories (open/closed-source, multiple sizes, diverse architectures, reasoning-based) using 5,000 claims previously assessed by 174 professional fact-checking organizations across 47 languages…

Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
Sajad Ahmadi, Hossein Nejatbakhsh Esfahani, Javad Mohammadpour Velni
https://arxiv.org/abs/2509.06687

Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
Deploying self-navigating surface vessels in inland waterways offers a sustainable alternative to reduce road traffic congestion and emissions. However, navigating confined waterways presents unique challenges, including narrow channels, higher traffic density, and hydrodynamic disturbances. Existing methods for autonomous vessel navigation often lack the robustness or precision required for such environments. This paper presents a new motion planning approach for Automated Surface Vessels (ASV…

Long-period variable stars in NGC 147 and NGC 185-II. Their dust production
Hamidreza Mahani, Atefeh Javadi, Jacco van Loon, Francisca Kemper, Roya Hamedani Golshan, Iain McDonald, Habib Khosroshahi, Hedieh Abdollahi, Sajjad Mahdizadeh
https://arxiv.org/abs/2508.05596

Long-period variable stars in NGC 147 and NGC 185-II. Their dust production
This study presents a comparative analysis of mass-loss and dust-production rates in the dwarf galaxies NGC 147 and NGC 185, focusing on long-period variables (LPVs) and pulsating asymptotic giant branch (AGB) stars as primary indicators of dust feedback into the interstellar medium. For NGC 147, the total mass-loss rate is calculated as $(9.44 \pm 3.78) \times 10^{-4} M_{sun} yr^{-1}$, with LPV luminosities ranging from $(6.20 \pm 0.25) \times 10^{2} L_\odot$ to $( 7.87 \pm 0.32) \times 10^{3}…

An Adaptive Coverage Control Approach for Multiple Autonomous Off-road Vehicles in Dynamic Agricultural Fields
Sajad Ahmadi, Mohammadreza Davoodi, Javad Mohammadpour Velni
https://arxiv.org/abs/2509.06682

An Adaptive Coverage Control Approach for Multiple Autonomous Off-road Vehicles in Dynamic Agricultural Fields
This paper presents an adaptive coverage control method for a fleet of off-road and Unmanned Ground Vehicles (UGVs) operating in dynamic (time-varying) agricultural environments. Traditional coverage control approaches often assume static conditions, making them unsuitable for real-world farming scenarios where obstacles, such as moving machinery and uneven terrains, create continuous challenges. To address this, we propose a real-time path planning framework that integrates Unmanned Aerial Veh…

From Tiny Machine Learning to Tiny Deep Learning: A Survey
Shriyank Somvanshi, Md Monzurul Islam, Gaurab Chhetri, Rohit Chakraborty, Mahmuda Sultana Mimi, Swagat Ahmed Shuvo, Kazi Sifatul Islam, Syed Aaqib Javed, Sharif Ahmed Rafat, Anandi Dutta, Subasish Das
https://arxiv.org/abs/2506.18927…

From Tiny Machine Learning to Tiny Deep Learning: A Survey
The rapid growth of edge devices has driven the demand for deploying artificial intelligence (AI) at the edge, giving rise to Tiny Machine Learning (TinyML) and its evolving counterpart, Tiny Deep Learning (TinyDL). While TinyML initially focused on enabling simple inference tasks on microcontrollers, the emergence of TinyDL marks a paradigm shift toward deploying deep learning models on severely resource-constrained hardware. This survey presents a comprehensive overview of the transition from…

Max-Min Fairness-Oriented Beamforming Design in HAPS-Enabled ISAC for 6G Networks
Parisa Kanani, Mohammad Javad Omidi, Mahmoud Modarres-Hashemi, Halim Yanikomeroglu
https://arxiv.org/abs/2507.18764

Max-Min Fairness-Oriented Beamforming Design in HAPS-Enabled ISAC for 6G Networks
This paper presents a high-altitude platform station (HAPS)-enabled integrated sensing and communication (ISAC) system designed for sixth-generation (6G) networks. Positioned in the stratosphere, HAPS serves as a super-macro base station, leveraging advanced beamforming techniques to enable communication and sensing simultaneously. This research addresses the need for equitable service distribution in 6G networks by focusing on fairness within the HAPS-ISAC system. It tackles a non-convex optim…

Engaging young people for a more inclusive national energy transition: A participatory modelling framework
Muhammad Shahzad Javed, Karin Fossheim, Maximilian Roithner, Matylda N. Guzik, James Price, Beate Seibt, Marianne Zeyringer
https://arxiv.org/abs/2508.12352

Engaging young people for a more inclusive national energy transition: A participatory modelling framework
Participatory research in energy system modelling can generate bottom-up knowledge to explore co-designed future net-zero energy system scenarios. However, it often fails to facilitate collective learning, explore explicitly informed perspectives, and frequently ignores underrepresented groups like youth, among whom distrust about the energy transformation process is growing. By modifying a national electricity system model to reflect young people's socio-techno-environmental insights gathered …