Tootfinder

A short note on the Massicot-Wagner method
Arturo Rodr\'iguez Fanlo
https://arxiv.org/abs/2509.17904 https://arxiv.org/pdf/2509.17904

A short note on the Massicot-Wagner method
We provide a general abstract statement of the Massicot-Wagner method: our main result is an assymetric version (i.e. a version for group actions) of the recursive Massicot-Wagner argument.

FlyTrap: Physical Distance-Pulling Attack Towards Camera-based Autonomous Target Tracking Systems
Shaoyuan Xie, Mohamad Habib Fakih, Junchi Lu, Fayzah Alshammari, Ningfei Wang, Takami Sato, Halima Bouzidi, Mohammad Abdullah Al Faruque, Qi Alfred Chen
https://arxiv.org/abs/2509.20362

FlyTrap: Physical Distance-Pulling Attack Towards Camera-based Autonomous Target Tracking Systems
Autonomous Target Tracking (ATT) systems, especially ATT drones, are widely used in applications such as surveillance, border control, and law enforcement, while also being misused in stalking and destructive actions. Thus, the security of ATT is highly critical for real-world applications. Under the scope, we present a new type of attack: distance-pulling attacks (DPA) and a systematic study of it, which exploits vulnerabilities in ATT systems to dangerously reduce tracking distances, leading …

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Emergence of Fair Leaders via Mediators in Multi-Agent Reinforcement Learning
Akshay Dodwadmath, Setareh Maghsudi
https://arxiv.org/abs/2508.02421 https://…

Emergence of Fair Leaders via Mediators in Multi-Agent Reinforcement Learning
Stackelberg games and their resulting equilibria have received increasing attention in the multi-agent reinforcement learning literature. Each stage of a traditional Stackelberg game involves a leader(s) acting first, followed by the followers. In situations where the roles of leader(s) and followers can be interchanged, the designated role can have considerable advantages, for example, in first-mover advantage settings. Then the question arises: Who should be the leader and when? A bias in the…