Tootfinder

Privacy-Preserving On-chain Permissioning for KYC-Compliant Decentralized Applications
Fabian Piper, Karl Wolf, Jonathan Heiss
https://arxiv.org/abs/2510.05807 https://

Privacy-Preserving On-chain Permissioning for KYC-Compliant Decentralized Applications
Decentralized applications (dApps) in Decentralized Finance (DeFi) face a fundamental tension between regulatory compliance requirements like Know Your Customer (KYC) and maintaining decentralization and privacy. Existing permissioned DeFi solutions often fail to adequately protect private attributes of dApp users and introduce implicit trust assumptions, undermining the blockchain's decentralization. Addressing these limitations, this paper presents a novel synthesis of Self-Sovereign Identity…

pyspect: An Extensible Toolbox for Automatic Construction of Temporal Logic Trees via Reachability Analysis
Kaj Munhoz Arfvidsson, Loizos Hadjiloizou, Frank J. Jiang, Karl H. Johansson, Jonas M{\aa}rtensson
https://arxiv.org/abs/2510.11316

pyspect: An Extensible Toolbox for Automatic Construction of Temporal Logic Trees via Reachability Analysis
In this paper, we present pyspect, a Python toolbox that simplifies the use of reachability analysis for temporal logic problems. Currently, satisfying complex requirements in cyber-physical systems requires significant manual effort and domain expertise to develop the underlying reachability programs. This high development effort limits the broader adoption of reachability analysis for complex verification problems. To address this, pyspect provides a method-agnostic approach to performing rea…

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants
Oskar Kviman, Kirill Tamogashev, Nicola Branchini, V\'ictor Elvira, Jens Lagergren, Nikolay Malkin
https://arxiv.org/abs/2510.01159

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants
Learning the dynamics of a process given sampled observations at several time points is an important but difficult task in many scientific applications. When no ground-truth trajectories are available, but one has only snapshots of data taken at discrete time steps, the problem of modelling the dynamics, and thus inferring the underlying trajectories, can be solved by multi-marginal generalisations of flow matching algorithms. This paper proposes a novel flow matching method that overcomes the …

ARUQULA -- An LLM based Text2SPARQL Approach using ReAct and Knowledge Graph Exploration Utilities
Felix Brei, Lorenz B\"uhmann, Johannes Frey, Daniel Gerber, Lars-Peter Meyer, Claus Stadler, Kirill Bulert
https://arxiv.org/abs/2510.02200

ARUQULA -- An LLM based Text2SPARQL Approach using ReAct and Knowledge Graph Exploration Utilities
Interacting with knowledge graphs can be a daunting task for people without a background in computer science since the query language that is used (SPARQL) has a high barrier of entry. Large language models (LLMs) can lower that barrier by providing support in the form of Text2SPARQL translation. In this paper we introduce a generalized method based on SPINACH, an LLM backed agent that translates natural language questions to SPARQL queries not in a single shot, but as an iterative process of e…

Speeding up SQL subqueries via decoupling of non-correlated predicate (extended version)
Dmitrii Radivonchik, Yakov Kuzin, Anton Chizhov, Dmitriy Shcheka, Mikhail Firsov, Kirill Smirnov, George Chernishev
https://arxiv.org/abs/2510.05907

Speeding up SQL subqueries via decoupling of non-correlated predicate (extended version)
In this paper, we discuss a novel technique for processing correlated subqueries in SQL. The core idea is to isolate the non-correlated part of the predicate and use it to reduce the number of evaluations of the correlated part. We begin by providing an overview of several classes of queries that may benefit from this technique. For each class, we propose a potential rewrite and discuss the conditions under which it is advantageous. Next, we address the evaluation aspects of the proposed rewrit…

Audio Forensics Evaluation (SAFE) Challenge
Kirill Trapeznikov, Paul Cummer, Pranay Pherwani, Jai Aslam, Michael S. Davinroy, Peter Bautista, Laura Cassani, Matthew Stamm, Jill Crisman
https://arxiv.org/abs/2510.03387

Audio Forensics Evaluation (SAFE) Challenge
The increasing realism of synthetic speech generated by advanced text-to-speech (TTS) models, coupled with post-processing and laundering techniques, presents a significant challenge for audio forensic detection. In this paper, we introduce the SAFE (Synthetic Audio Forensics Evaluation) Challenge, a fully blind evaluation framework designed to benchmark detection models across progressively harder scenarios: raw synthetic speech, processed audio (e.g., compression, resampling), and laundered a…

Supporting Creative Ownership through Deep Learning-Based Music Variation
Stephen James Krol, Maria Teresa Llano, Jon McCormack
https://arxiv.org/abs/2509.25834 https://

Supporting Creative Ownership through Deep Learning-Based Music Variation
This paper investigates the importance of personal ownership in musical AI design, examining how practising musicians can maintain creative control over the compositional process. Through a four-week ecological evaluation, we examined how a music variation tool, reliant on the skill of musicians, functioned within a composition setting. Our findings demonstrate that the dependence of the tool on the musician's ability, to provide a strong initial musical input and to turn moments into complete …

A note on the $k$-defect number: Vertex Coloring with a Fixed Number of Monochromatic Edges
Eunice Mphako-Banda, Christo Kriel, Alex Alochukwu
https://arxiv.org/abs/2510.00712 h…

A note on the $k$-defect number: Vertex Coloring with a Fixed Number of Monochromatic Edges
In this paper, we introduce and study a novel graph parameter called the $k$-defect number, denoted $ϕ_{k}(G)$, for a graph $G$ and an integer $0\leq k\leq |E(G)|$. Unlike traditional defective colorings that bound the local degree within monochromatic components, the $k$-defect number represents the smallest number of colors required to achieve a vertex coloring of $G$ having exactly \emph{$k$ monochromatic edges (also termed ``bad edges")}. This parameter generalizes the well-known…

General Order Virtual Element Approximation for the Smagorinsky turbulence model
Stefano Berrone, Karol L. Cascavita, Enrique Delgado \'Avila, Samuele Rubino, Maria Strazzullo, Fabio Vicini
https://arxiv.org/abs/2510.03563

General Order Virtual Element Approximation for the Smagorinsky turbulence model
In this paper, we investigate a Smagorinsky model in a virtual element framework to simulate convection-dominated Navier-Stokes equations. We conduct a two-dimensional numerical investigation to assess the performance of the general order virtual element approximation in this context. First, we examine numerically the convergence of the method with respect to the meshsize to certify the novel virtual element numerical discretization, which includes, for the first time, a discretization of the S…

Detection and Identification of Sensor Attacks Using Data
Takumi Shinohara, Karl H. Johansson, Henrik Sandberg
https://arxiv.org/abs/2510.02183 https://arx…

Detection and Identification of Sensor Attacks Using Data
In this paper, we investigate data-driven attack detection and identification in a model-free setting. Unlike existing studies, we consider the case where the available output data include malicious false-data injections. We aim to detect and identify such attacks solely from the compromised data. We address this problem in two scenarios: (1) when the system operator is aware of the system's sparse observability condition, and (2) when the data are partially clean (i.e., attack-free). In both s…