Tootfinder

Approximation Fixpoint Theory as a Unifying Framework for Fuzzy Logic Programming Semantics (Extended Version)
Pascal Kettmann, Jesse Heyninck, Hannes Strass
https://arxiv.org/abs/2507.11961

Approximation Fixpoint Theory as a Unifying Framework for Fuzzy Logic Programming Semantics (Extended Version)
Fuzzy logic programming is an established approach for reasoning under uncertainty. Several semantics from classical, two-valued logic programming have been generalized to the case of fuzzy logic programs. In this paper, we show that two of the most prominent classical semantics, namely the stable model and the well-founded semantics, can be reconstructed within the general framework of approximation fixpoint theory (AFT). This not only widens the scope of AFT from two- to many-valued logics, b…

Evasion Under Blockchain Sanctions
Endong Liu, Mark Ryan, Liyi Zhou, Pascal Berrang
https://arxiv.org/abs/2507.11721 https://arxiv.or…

Evasion Under Blockchain Sanctions
Sanctioning blockchain addresses has become a common regulatory response to malicious activities. However, enforcement on permissionless blockchains remains challenging due to complex transaction flows and sophisticated fund-obfuscation techniques. Using cryptocurrency mixing tool Tornado Cash as a case study, we quantitatively assess the effectiveness of U.S. Office of Foreign Assets Control (OFAC) sanctions over a 957-day period, covering 6.79 million Ethereum blocks and 1.07 billion transact…

GenAI-based test case generation and execution in SDV platform
Denesa Zyberaj, Lukasz Mazur, Nenad Petrovic, Pankhuri Verma, Pascal Hirmer, Dirk Slama, Xiangwei Cheng, Alois Knoll
https://arxiv.org/abs/2509.05112

GenAI-based test case generation and execution in SDV platform
This paper introduces a GenAI-driven approach for automated test case generation, leveraging Large Language Models and Vision-Language Models to translate natural language requirements and system diagrams into structured Gherkin test cases. The methodology integrates Vehicle Signal Specification modeling to standardize vehicle signal definitions, improve compatibility across automotive subsystems, and streamline integration with third-party testing tools. Generated test cases are executed withi…

How can a geothermal storage system be optimally integrated into a local district? A case study
Ueli Schilt, Somesh Vijayananda, Sarah Schneeberger, Manuel Meyer, Santhosh Iyyakkunnel, Pascal Marc Vecsei, Philipp Schuetz
https://arxiv.org/abs/2509.08568

How can a geothermal storage system be optimally integrated into a local district? A case study
Achieving net-zero targets requires the phase-out of fossil-based heating. A major challenge is the seasonal mismatch between renewable heat supply and demand. District heating networks often dispose of excess heat in summer and rely on fossil backups in winter. Large-scale thermal energy storage offers a solution by storing surplus summer heat for use during winter, thus reducing the need for fossil fuels. This study investigates the feasibility of a large-scale thermal storage system at a pow…

Paratransit Optimization with Constraint Programming: A Case Study in Savannah, Georgia
Liam Jagrowski, Kevin Dalmeijer, Tinghan Ye, Pascal Van Hentenryck
https://arxiv.org/abs/2508.00241

Paratransit Optimization with Constraint Programming: A Case Study in Savannah, Georgia
Paratransit services are vital for individuals who cannot use fixed-route public transit, including those with disabilities. Optimizing these services is essential for transit agencies to deliver high-quality service efficiently. This paper introduces a constraint programming model to jointly optimize route planning and shift scheduling for paratransit operations, along with practical guidance for real-world implementation. A case study in Savannah, Georgia, demonstrates that the new approach i…

Empowering Manufacturers with Privacy-Preserving AI Tools: A Case Study in Privacy-Preserving Machine Learning to Solve Real-World Problems
Xiaoyu Ji, Jessica Shorland, Joshua Shank, Pascal Delpe-Brice, Latanya Sweeney, Jan Allebach, Ali Shakouri
https://arxiv.org/abs/2507.01808

Empowering Manufacturers with Privacy-Preserving AI Tools: A Case Study in Privacy-Preserving Machine Learning to Solve Real-World Problems
Small- and medium-sized manufacturers need innovative data tools but, because of competition and privacy concerns, often do not want to share their proprietary data with researchers who might be interested in helping. This paper introduces a privacy-preserving platform by which manufacturers may safely share their data with researchers through secure methods, so that those researchers then create innovative tools to solve the manufacturers' real-world problems, and then provide tools that execu…

Targeted Physical Evasion Attacks in the Near-Infrared Domain
Pascal Zimmer, Simon Lachnit, Alexander Jan Zielinski, Ghassan Karame
https://arxiv.org/abs/2509.02042 https://

Targeted Physical Evasion Attacks in the Near-Infrared Domain
A number of attacks rely on infrared light sources or heat-absorbing material to imperceptibly fool systems into misinterpreting visual input in various image recognition applications. However, almost all existing approaches can only mount untargeted attacks and require heavy optimizations due to the use-case-specific constraints, such as location and shape. In this paper, we propose a novel, stealthy, and cost-effective attack to generate both targeted and untargeted adversarial infrared pertu…