Tootfinder

Jaguar Land Rover says cyberattack shutdown to last 'at least' another week https://therecord.media/jaguar-land-rover-another-week-shutdown-cyberattack

Douro Valley hiking day 2. #hiking #portugal

Towards Trustworthy Agentic IoEV: AI Agents for Explainable Cyberthreat Mitigation and State Analytics
Meryem Malak Dif, Mouhamed Amine Bouchiha, Abdelaziz Amara Korba, Yacine Ghamri-Doudane
https://arxiv.org/abs/2509.12233

Towards Trustworthy Agentic IoEV: AI Agents for Explainable Cyberthreat Mitigation and State Analytics
The Internet of Electric Vehicles (IoEV) envisions a tightly coupled ecosystem of electric vehicles (EVs), charging infrastructure, and grid services, yet it remains vulnerable to cyberattacks, unreliable battery-state predictions, and opaque decision processes that erode trust and performance. To address these challenges, we introduce a novel Agentic Artificial Intelligence (AAI) framework tailored for IoEV, where specialized agents collaborate to deliver autonomous threat mitigation, robust a…

Empowering Multi-Robot Cooperation via Sequential World Models
Zijie Zhao, Honglei Guo, Shengqian Chen, Kaixuan Xu, Bo Jiang, Yuanheng Zhu, Dongbin Zhao
https://arxiv.org/abs/2509.13095

Empowering Multi-Robot Cooperation via Sequential World Models
Model-based reinforcement learning (MBRL) has shown significant potential in robotics due to its high sample efficiency and planning capability. However, extending MBRL to multi-robot cooperation remains challenging due to the complexity of joint dynamics. To address this, we propose the Sequential World Model (SeqWM), a novel framework that integrates the sequential paradigm into model-based multi-agent reinforcement learning. SeqWM employs independent, sequentially structured agent-wise world…

Optimal Treatment Rules under Missing Predictive Covariates: A Covariate-Balancing Doubly Robust Approach
Yue Zhang, Shanshan Luo, Zhi Geng, Yangbo He
https://arxiv.org/abs/2510.12321

Optimal Treatment Rules under Missing Predictive Covariates: A Covariate-Balancing Doubly Robust Approach
In precision medicine, one of the most important problems is estimating the optimal individualized treatment rules (ITR), which typically involves recommending treatment decisions based on fully observed individual characteristics of patients to maximize overall clinical benefit. In practice, however, there may be missing covariates that are not necessarily confounders, and it remains uncertain whether these missing covariates should be included for learning optimal ITRs. In this paper, we prop…

CAMNet: Leveraging Cooperative Awareness Messages for Vehicle Trajectory Prediction
Mattia Grasselli, Angelo Porrello, Carlo Augusto Grazia
https://arxiv.org/abs/2510.12703 http…

CAMNet: Leveraging Cooperative Awareness Messages for Vehicle Trajectory Prediction
Autonomous driving remains a challenging task, particularly due to safety concerns. Modern vehicles are typically equipped with expensive sensors such as LiDAR, cameras, and radars to reduce the risk of accidents. However, these sensors face inherent limitations: their field of view and line of sight can be obstructed by other vehicles, thereby reducing situational awareness. In this context, vehicle-to-vehicle communication plays a crucial role, as it enables cars to share information and rema…

Pooling Probabilistic Forecasts for Cooperative Wind Power Offering
Honglin Wen, Pierre Pinson
https://arxiv.org/abs/2510.12382 https://arxiv.org/pdf/2510.…

Pooling Probabilistic Forecasts for Cooperative Wind Power Offering
Wind power producers can benefit from forming coalitions to participate cooperatively in electricity markets. To support such collaboration, various profit allocation rules rooted in cooperative game theory have been proposed. However, existing approaches overlook the lack of coherence among producers regarding forecast information, which may lead to ambiguity in offering and allocations. In this paper, we introduce a ``reconcile-then-optimize'' framework for cooperative market offerings. This …

The Adaptation Paradox: Agency vs. Mimicry in Companion Chatbots
T. James Brandt, Cecilia Xi Wang
https://arxiv.org/abs/2509.12525 https://arxiv.org/pdf/25…

The Adaptation Paradox: Agency vs. Mimicry in Companion Chatbots
Generative AI powers a growing wave of companion chatbots, yet principles for fostering genuine connection remain unsettled. We test two routes: visible user authorship versus covert language-style mimicry. In a preregistered 3x2 experiment (N = 162), we manipulated user-controlled avatar generation (none, premade, user-generated) and Language Style Matching (LSM) (static vs. adaptive). Generating an avatar boosted rapport ($ω^2$ = .040, p = .013), whereas adaptive LSM underperformed static st…

Cooperative Face Liveness Detection from Optical Flow
Artem Sokolov, Mikhail Nikitin, Anton Konushin
https://arxiv.org/abs/2508.10786 https://arxiv.org/pdf…

Cooperative Face Liveness Detection from Optical Flow
In this work, we proposed a novel cooperative video-based face liveness detection method based on a new user interaction scenario where participants are instructed to slowly move their frontal-oriented face closer to the camera. This controlled approaching face protocol, combined with optical flow analysis, represents the core innovation of our approach. By designing a system where users follow this specific movement pattern, we enable robust extraction of facial volume information through neur…

An Unsupervised Learning Approach For A Reliable Profiling Of Cyber Threat Actors Reported Globally Based On Complete Contextual Information Of Cyber Attacks
Sawera Shahid, Umara Noor, Zahid Rashid
https://arxiv.org/abs/2509.11683

An Unsupervised Learning Approach For A Reliable Profiling Of Cyber Threat Actors Reported Globally Based On Complete Contextual Information Of Cyber Attacks
Cyber attacks are rapidly increasing with the advancement of technology and there is no protection for our information. To prevent future cyberattacks it is critical to promptly recognize cyberattacks and establish strong defense mechanisms against them. To respond to cybersecurity threats immediately, it is essential to examine the attackers skills, knowledge, and behaviors with the goal of evaluating their impact on the system and comprehending the traits associated with these attacks. Creati…