Tootfinder

BASFuzz: Towards Robustness Evaluation of LLM-based NLP Software via Automated Fuzz Testing
Mingxuan Xiao, Yan Xiao, Shunhui Ji, Jiahe Tu, Pengcheng Zhang
https://arxiv.org/abs/2509.17335

BASFuzz: Towards Robustness Evaluation of LLM-based NLP Software via Automated Fuzz Testing
Fuzzing has shown great success in evaluating the robustness of intelligent natural language processing (NLP) software. As large language model (LLM)-based NLP software is widely deployed in critical industries, existing methods still face two main challenges: 1 testing methods are insufficiently coupled with the behavioral patterns of LLM-based NLP software; 2 fuzzing capability for the testing scenario of natural language generation (NLG) generally degrades. To address these issues, we propos…

House Finch, collecting cactus fuzz for nesting. Huntington Library, San Marino, California, USA. June, 2025. #huntingtonlibrary #finch #housefinch

Hardness and Structural Properties of Fuzzy Edge Contraction
Shanookha Ali
https://arxiv.org/abs/2509.16185 https://arxiv.org/pdf/2509.16185

Hardness and Structural Properties of Fuzzy Edge Contraction
We investigate the computational complexity of edge-deletion and edge-contraction problems in fuzzy graphs. For any graph property Π that is hereditary under contractions (or deletions) and determined by 3-connected components, the corresponding fuzzy edge-deletion (FPED) and fuzzy edge-contraction (FPEC) problems are NP- hard. Our results hold under both fixed-threshold (α_0) and all-threshold (\forall α) semantics, and apply even to restricted classes of fuzzy graphs such as fuzzy 3-connec…

STAFF: Stateful Taint-Assisted Full-system Firmware Fuzzing
Alessio Izzillo, Riccardo Lazzeretti, Emilio Coppa
https://arxiv.org/abs/2509.18039 https://arx…

STAFF: Stateful Taint-Assisted Full-system Firmware Fuzzing
Modern embedded Linux devices, such as routers, IP cameras, and IoT gateways, rely on complex software stacks where numerous daemons interact to provide services. Testing these devices is crucial from a security perspective since vendors often use custom closed- or open-source software without documenting releases and patches. Recent coverage-guided fuzzing solutions primarily test individual processes, ignoring deep dependencies between daemons and their persistent internal state. This article…

Quantum Metric Spaces: Replacing Fuzzy Metrics with the Hilbert Space Structure of Quantum States
Nicola Fabiano
https://arxiv.org/abs/2509.15945 https://a…

Quantum Metric Spaces: Replacing Fuzzy Metrics with the Hilbert Space Structure of Quantum States
Fuzzy metric spaces, grounded in t-norms and membership functions, have been widely proposed to model uncertainty in machine learning, decision systems, and artificial intelligence. Yet these frameworks treat uncertainty as an external layer of imprecision imposed upon classical, point-like entities - a conceptual mismatch for domains where indeterminacy is intrinsic, such as quantum systems or cognitive representations. We argue that fuzzy metrics are unnecessary for modeling such uncertainty:…

Was very tired, so went to bed early...but suddenly here I am on Masto again 😄

Transformer-Gather, Fuzzy-Reconsider: A Scalable Hybrid Framework for Entity Resolution
Mohammadreza Sharifi, Danial Ahmadzadeh
https://arxiv.org/abs/2509.17470 https://

Transformer-Gather, Fuzzy-Reconsider: A Scalable Hybrid Framework for Entity Resolution
Entity resolution plays a significant role in enterprise systems where data integrity must be rigorously maintained. Traditional methods often struggle with handling noisy data or semantic understanding, while modern methods suffer from computational costs or the excessive need for parallel computation. In this study, we introduce a scalable hybrid framework, which is designed to address several important problems, including scalability, noise robustness, and reliable results. We utilized a pre…

Linear Equations in the Ring of $\mathcal{S}\left(\mathcal{A}\right)$-Linearly Correlated Fuzzy Numbers
Beatriz Laiate, Peter Sussner
https://arxiv.org/abs/2508.14900 https://…

Linear Equations in the Ring of $\mathcal{S}\left(\mathcal{A}\right)$-Linearly Correlated Fuzzy Numbers
This paper investigates the solutions of a family of certain linear fuzzy arithmetic equations that involve fuzzy numbers belonging to certain finite-dimensional vector spaces of $\mathbb{R}_{\mathcal{F}}$, called $\mathcal{S}\left(\mathcal{A}\right)$-linearly correlated fuzzy numbers. Here, $\A$ stands for a strongly linearly independent (SLI) set of fuzzy numbers. The arithmetic operations in the aforementioned linear equations are the sum in the vector space $\Sc(\A)$ and the so-called $ψ$-…

Technology has evolved over the years!
Main image: 6T SRAM bitcells from PIC12F683 (2007, Microchip 160K 350 nm). Bitcells are 5.73 x 8.23 μm or 47.15 μm^2.
Inset: 6T SRAM from STM32L431 (2016, TSMC 90nm). Bitcells are 1.486 x 0.68 μm or 1.01 μm^2.

Causal Fuzzing for Verifying Machine Unlearning
Anna Mazhar, Sainyam Galhotra
https://arxiv.org/abs/2509.16525 https://arxiv.org/pdf/2509.16525

Causal Fuzzing for Verifying Machine Unlearning
As machine learning models become increasingly embedded in decision-making systems, the ability to "unlearn" targeted data or features is crucial for enhancing model adaptability, fairness, and privacy in models which involves expensive training. To effectively guide machine unlearning, a thorough testing is essential. Existing methods for verification of machine unlearning provide limited insights, often failing in scenarios where the influence is indirect. In this work, we propose CAFÉ, a ne…