Tootfinder

ReVeal: Self-Evolving Code Agents via Iterative Generation-Verification
Yiyang Jin, Kunzhao Xu, Hang Li, Xueting Han, Yanmin Zhou, Cheng Li, Jing Bai
https://arxiv.org/abs/2506.11442

ReVeal: Self-Evolving Code Agents via Iterative Generation-Verification
Recent advances in reinforcement learning (RL) with verifiable outcome rewards have significantly improved the reasoning capabilities of large language models (LLMs), especially when combined with multi-turn tool interactions. However, existing methods lack both meaningful verification signals from realistic environments and explicit optimization for verification, leading to unreliable self-verification. To address these limitations, we propose ReVeal, a multi-turn reinforcement learning framew…

The CAISAR Platform: Extending the Reach of Machine Learning Specification and Verification
Michele Alberti (LSL), Fran\c{c}ois Bobot (LSL), Julien Girard-Satabin (LSL), Alban Grastien (LSL), Aymeric Varasse (LSL), Zakaria Chihani (LSL)
https://arxiv.org/abs/2506.12084

The CAISAR Platform: Extending the Reach of Machine Learning Specification and Verification
The formal specification and verification of machine learning programs saw remarkable progress in less than a decade, leading to a profusion of tools. However, diversity may lead to fragmentation, resulting in tools that are difficult to compare, except for very specific benchmarks. Furthermore, this progress is heavily geared towards the specification and verification of a certain class of property, that is, local robustness properties. But while provers are becoming more and more efficient at…

VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
Hao Peng, Yunjia Qi, Xiaozhi Wang, Bin Xu, Lei Hou, Juanzi Li
https://arxiv.org/abs/2506.09942 …

VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
Reinforcement learning with verifiable rewards (RLVR) has become a key technique for enhancing large language models (LLMs), with verification engineering playing a central role. However, best practices for RL in instruction following remain underexplored. In this work, we explore the verification challenge in RL for instruction following and propose VerIF, a verification method that combines rule-based code verification with LLM-based verification from a large reasoning model (e.g., QwQ-32B). …

Lakers, an implementation of #EDHOC, i.e., lightweight security for #IoT, now uses formal verification to continuously check a first small part of its code using #hax and F*, proving our buffers won't reach out of the…

Experimental Verification of Entangled States in the Adversarial Scenario
Wen-Hao Zhang, Zihao Li, Gong-Chu Li, Xu-Song Hong, Huangjun Zhu, Geng Chen, Chuan-Feng Li, Guang-Can Guo
https://arxiv.org/abs/2506.10655

Experimental Verification of Entangled States in the Adversarial Scenario
Efficient verification of entangled states is crucial to many applications in quantum information processing. However, the effectiveness of standard quantum state verification (QSV) is based on the condition of independent and identical distribution (IID), which impedes its applications in many practical scenarios. Here we demonstrate a defensive QSV protocol, which is effective in all kinds of non-IID scenarios, including the extremely challenging adversarial scenario. To this end, we build a …

Abstraction-Based Proof Production in Formal Verification of Neural Networks
Yizhak Yisrael Elboher, Omri Isac, Guy Katz, Tobias Ladner, Haoze Wu
https://arxiv.org/abs/2506.09455 …

Abstraction-Based Proof Production in Formal Verification of Neural Networks
Modern verification tools for deep neural networks (DNNs) increasingly rely on abstraction to scale to realistic architectures. In parallel, proof production is becoming a critical requirement for increasing the reliability of DNN verification results. However, current proofproducing verifiers do not support abstraction-based reasoning, creating a gap between scalability and provable guarantees. We address this gap by introducing a novel framework for proof-producing abstraction-based DNN verif…

The Limits of Tractable Marginalization
Oliver Broadrick, Sanyam Agarwal, Guy Van den Broeck, Markus Bl\"aser
https://arxiv.org/abs/2506.12020 https:/…

The Limits of Tractable Marginalization
Marginalization -- summing a function over all assignments to a subset of its inputs -- is a fundamental computational problem with applications from probabilistic inference to formal verification. Despite its computational hardness in general, there exist many classes of functions (e.g., probabilistic models) for which marginalization remains tractable, and they can be commonly expressed by polynomial size arithmetic circuits computing multilinear polynomials. This raises the question, can all…

Infinitely many solutions for nonlinear superposition operators of mixed fractional order involving critical exponent
Souvik Bhowmick, Sekhar Ghosh, Vishvesh Kumar
https://arxiv.org/abs/2506.11832

Infinitely many solutions for nonlinear superposition operators of mixed fractional order involving critical exponent
This paper addresses elliptic problems involving the superposition of nonlinear fractional operators with the critical Sobolev exponent in sublinear regimes. We establish the existence of infinitely many nontrivial weak solutions using a variational framework that combines a truncation argument with the notion of genus. A central part of our analysis is the verification of the Palais--Smale $(\mathrm{PS})_c$ condition for every $q \in (1, p_{s_\sharp}^*)$, despite the challenges posed by the la…

Verification of the Release-Acquire Semantics
Parosh Abdulla, Elli Anastasiadi, Mohamed Faouzi Atig, Samuel Grahn
https://arxiv.org/abs/2506.08238 https://…

Verification of the Release-Acquire Semantics
The Release-Acquire (RA) semantics and its variants are some of the most fundamental models of concurrent semantics for architectures, programming languages, and distributed systems. Several steps have been taken in the direction of testing such semantics, where one is interested in whether a single program execution is consistent with a memory model. The more general verification problem, i.e., checking whether all allowed program runs are consistent with a memory model, has still not been stu…

StepProof: Step-by-step verification of natural language mathematical proofs
Xiaolin Hu, Qinghua Zhou, Bogdan Grechuk, Ivan Y. Tyukin
https://arxiv.org/abs/2506.10558

StepProof: Step-by-step verification of natural language mathematical proofs
Interactive theorem provers (ITPs) are powerful tools for the formal verification of mathematical proofs down to the axiom level. However, their lack of a natural language interface remains a significant limitation. Recent advancements in large language models (LLMs) have enhanced the understanding of natural language inputs, paving the way for autoformalization - the process of translating natural language proofs into formal proofs that can be verified. Despite these advancements, existing aut…

QualitEye: Public and Privacy-preserving Gaze Data Quality Verification
Mayar Elfares, Pascal Reisert, Ralf K\"usters, Andreas Bulling
https://arxiv.org/abs/2506.05908

QualitEye: Public and Privacy-preserving Gaze Data Quality Verification
Gaze-based applications are increasingly advancing with the availability of large datasets but ensuring data quality presents a substantial challenge when collecting data at scale. It further requires different parties to collaborate, therefore, privacy concerns arise. We propose QualitEye--the first method for verifying image-based gaze data quality. QualitEye employs a new semantic representation of eye images that contains the information required for verification while excluding irrelevant …

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Simin Sun, Yuchuan Jin, Miroslaw Staron
https://arxiv.org/abs/2506.11659

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Developing autonomous driving systems (ADSs) involves generating and storing extensive log data from test drives, which is essential for verification, research, and simulation. However, these high-frequency logs, recorded over varying durations, pose challenges for developers attempting to locate specific driving scenarios. This difficulty arises due to the wide range of signals representing various vehicle components and driving conditions, as well as unfamiliarity of some developers' with the…

An Efficient Candidate-Free R-S Set Similarity Join Algorithm with the Filter-and-Verification Tree and MapReduce
Yuhong Feng, Fangcao Jian, Yixuan Cao, Xiaobin Jian, Jia Wang, Haiyue Feng, Chunyan Miao
https://arxiv.org/abs/2506.03893

An Efficient Candidate-Free R-S Set Similarity Join Algorithm with the Filter-and-Verification Tree and MapReduce
Given two different collections of sets, the exact set similarity R-S Join finds all set pairs with similarity no less than a given threshold, which has widespread applications. While existing algorithms accelerate large-scale R-S Joins using a two-stage filter-and-verification framework along with the parallel and distributed MapReduce framework, they suffer from excessive candidate set pairs, leading to significant I/O, data transfer, and verification overhead, and ultimately degrading the pe…

If you want to see the iPhone identity verification flow, it's demoed in this WWDC25 session.
https://youtu.be/R3EgtCX1r-E?feature=shared&t=222

This https://arxiv.org/abs/2505.11963 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

MARVEL: Multi-Agent RTL Vulnerability Extraction using Large Language Models
Hardware security verification is a challenging and time-consuming task. For this purpose, design engineers may utilize tools such as formal verification, linters, and functional simulation tests, coupled with analysis and a deep understanding of the hardware design being inspected. Large Language Models (LLMs) have been used to assist during this task, either directly or in conjunction with existing tools. We improve the state of the art by proposing MARVEL, a multi-agent LLM framework for a u…

Digital badges have come to the Fediverse! Courtesy of @… .
Each badge comes with a verification link. Here's the link for my "code contributor" badge: https://

Pornhub is making bullshit claims regarding the privacy issues of the French gov age verification requirements. There are very real and significant problems with the French gov approach, but Pornhub's approach is significantly worse.
Pornhub wants to put the burden of age verification and enforcement on user devices. They even name the actors that should have to bear that burden: Google, Apple and Microsoft.
First off, this creates an artificial monopoly: three American compa…

If you are like me, then you might have installed the #GoogleAuthenticator app, back in the days when it was the only solution out there for #TOTP #2FA.
But that is long ago. Since …

Texas Governor Signs Age Verification Bill Despite Heavy Pushback From Apple (PCMag, 27 May 2025)
https://www.pcmag.com/news/despite-heavy-pushback-from-apple-texas-gov-signs-age-verification-bill

A Short Survey on Formalising Software Requirements using Large Language Models
Arshad Beg, Diarmuid O'Donoghue, Rosemary Monahan
https://arxiv.org/abs/2506.11874

A Short Survey on Formalising Software Requirements using Large Language Models
This paper presents a focused literature survey on the use of large language models (LLM) to assist in writing formal specifications for software. A summary of thirty-five key papers is presented, including examples for specifying programs written in Dafny, C and Java. This paper arose from the project VERIFAI - Traceability and verification of natural language requirements that addresses the challenges in writing formal specifications from requirements that are expressed in natural language. O…

EditInspector: A Benchmark for Evaluation of Text-Guided Image Edits
Ron Yosef, Moran Yanuka, Yonatan Bitton, Dani Lischinski
https://arxiv.org/abs/2506.09988

EditInspector: A Benchmark for Evaluation of Text-Guided Image Edits
Text-guided image editing, fueled by recent advancements in generative AI, is becoming increasingly widespread. This trend highlights the need for a comprehensive framework to verify text-guided edits and assess their quality. To address this need, we introduce EditInspector, a novel benchmark for evaluation of text-guided image edits, based on human annotations collected using an extensive template for edit verification. We leverage EditInspector to evaluate the performance of state-of-the-art…

The Folly of AI for Age Verification
Reid McIlroy-Young
https://arxiv.org/abs/2506.00038 https://arxiv.org/pdf/2506.00038

The Folly of AI for Age Verification
In the near future a governmental body will be asked to allow companies to use AI for age verification. If they allow it the resulting system will both be easily circumvented and disproportionately misclassify minorities and low socioeconomic status users. This is predictable by showing that other very similar systems (facial recognition and remote proctoring software) have similar issues despite years of efforts to mitigate their biases. These biases are due to technical limitations both of th…

Bayesian Learning for Domain-Invariant Speaker Verification and Anti-Spoofing
Jin Li, Man-Wai Mak, Johan Rohdin, Kong Aik Lee, Hynek Hermansky
https://arxiv.org/abs/2506.07536

Bayesian Learning for Domain-Invariant Speaker Verification and Anti-Spoofing
The performance of automatic speaker verification (ASV) and anti-spoofing drops seriously under real-world domain mismatch conditions. The relaxed instance frequency-wise normalization (RFN), which normalizes the frequency components based on the feature statistics along the time and channel axes, is a promising approach to reducing the domain dependence in the feature maps of a speaker embedding network. We advocate that the different frequencies should receive different weights and that the w…

Chance and Mass Interpretations of Probabilities in Markov Decision Processes (Extended Version)
Yun Chen Tsai, Kittiphon Phalakarn, S. Akshay, Ichiro Hasuo
https://arxiv.org/abs/2506.10377

Chance and Mass Interpretations of Probabilities in Markov Decision Processes (Extended Version)
Markov decision processes (MDPs) are a popular model for decision-making in the presence of uncertainty. The conventional view of MDPs in verification treats them as state transformers with probabilities defined over sequences of states and with schedulers making random choices. An alternative view, especially well-suited for modeling dynamical systems, defines MDPs as distribution transformers with schedulers distributing probability masses. Our main contribution is a unified semantical framew…

CellTypeAgent: Trustworthy cell type annotation with Large Language Models
Jiawen Chen, Jianghao Zhang, Huaxiu Yao, Yun Li
https://arxiv.org/abs/2505.08844

CellTypeAgent: Trustworthy cell type annotation with Large Language Models
Cell type annotation is a critical yet laborious step in single-cell RNA sequencing analysis. We present a trustworthy large language model (LLM)-agent, CellTypeAgent, which integrates LLMs with verification from relevant databases. CellTypeAgent achieves higher accuracy than existing methods while mitigating hallucinations. We evaluated CellTypeAgent across nine real datasets involving 303 cell types from 36 tissues. This combined approach holds promise for more efficient and reliable cell typ…

Completion of scientific balloon flight BS25-02 - Preliminary experiment (III-1) - toward a precise verification of #GeneralRelativity based on laser frequency transfer: https://www.isas.jaxa.jp/en/topics/004025.html

Verification of Quantum Circuits through Barrier Certificates using a Scenario Approach
Siwei Hu, Victor Lopata, Sadegh Soudjani, Paolo Zuliani
https://arxiv.org/abs/2506.07635

Verification of Quantum Circuits through Barrier Certificates using a Scenario Approach
In recent years, various techniques have been explored for the verification of quantum circuits, including the use of barrier certificates, mathematical tools capable of demonstrating the correctness of such systems. These certificates ensure that, starting from initial states and applying the system's dynamics, the system will never reach undesired states. In this paper, we propose a methodology for synthesizing such certificates for quantum circuits using a scenario-based approach, for both f…

Es ist schön zu sehen, dass @… schon hier ist.
Treibe ruhig mal in deiner Künstler*innen/Autor*innen Bubble die Fediverse Werbetrommel rühren.
Bring sie alle her.
Und verifiziere ruhig mal deinen account:

Verifizierung
Erfahre, wie du dich auf Mastodon verifizieren kannst

This https://arxiv.org/abs/2505.20302 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification
This paper introduces VeriThoughts, a novel dataset designed for reasoning-based Verilog code generation. We establish a new benchmark framework grounded in formal verification methods to evaluate the quality and correctness of generated hardware descriptions. Additionally, we present a suite of specialized small-scale models optimized specifically for Verilog generation. Our work addresses the growing need for automated hardware design tools that can produce verifiably correct implementations …

Formalising Software Requirements using Large Language Models
Arshad Beg, Diarmuid O'Donoghue, Rosemary Monahan
https://arxiv.org/abs/2506.10704 https:…

Formalising Software Requirements using Large Language Models
This paper is a brief introduction to our recently initiated project named VERIFAI: Traceability and verification of natural language requirements. The project addresses the challenges in the traceability and verification of formal specifications through providing support for the automatic generation of the formal specifications and the traceability of the requirements from the initial software design stage through the systems implementation and verification. Approaches explored in this project…

Rust's Stable MIR project is being slept on. It's pitched as a tool for formal verification, but it's more general than that. Once stabilized, it will almost be a stable compiler plugin API!
It doesn't just include what you get from `--emit=mir` (IR for each function), but also has full type and trait information, and will likely even support interactive queries like "does type implement trait”.
In short, it'll be perfect for metaprogramming!
[1/2]…

HEC: Equivalence Verification Checking for Code Transformation via Equality Saturation
Jiaqi Yin, Zhan Song, Nicolas Bohm Agostini, Antonino Tumeo, Cunxi Yu
https://arxiv.org/abs/2506.02290

HEC: Equivalence Verification Checking for Code Transformation via Equality Saturation
In modern computing systems, compilation employs numerous optimization techniques to enhance code performance. Source-to-source code transformations, which include control flow and datapath transformations, have been widely used in High-Level Synthesis (HLS) and compiler optimization. While researchers actively investigate methods to improve performance with source-to-source code transformations, they often overlook the significance of verifying their correctness. Current tools cannot provide…

SPBA: Utilizing Speech Large Language Model for Backdoor Attacks on Speech Classification Models
Wenhan Yao, Fen Xiao, Xiarun Chen, Jia Liu, YongQiang He, Weiping Wen
https://arxiv.org/abs/2506.08346

SPBA: Utilizing Speech Large Language Model for Backdoor Attacks on Speech Classification Models
Deep speech classification tasks, including keyword spotting and speaker verification, are vital in speech-based human-computer interaction. Recently, the security of these technologies has been revealed to be susceptible to backdoor attacks. Specifically, attackers use noisy disruption triggers and speech element triggers to produce poisoned speech samples that train models to become vulnerable. However, these methods typically create only a limited number of backdoors due to the inherent cons…

This https://arxiv.org/abs/2407.20624 has been replaced.
initial toot: https://mastoxiv.page/@arXi…

Spatial verification of global precipitation forecasts
Verification of global high-resolution precipitation forecasts is challenging. Spatial verification techniques address some shortcomings of traditional verification. However most existing methods do not account for the non-planar geometry of a global domain, or their computational complexity is too large for global assessments. We present an adaptation of the recently developed Precipitation Attribution Distance (PAD) metric, designed for verifying precipitation, enabling its use on the Earth's…

English Version too! :ai_yay:
Remember that if you have a link in your profile and this is your website, you can verify the link by putting a <link rel=“me” href=“the link to your fedi account”/> so that the field appears as verified.
More info: on the official mastodon website. https://joinmastodon.org/en/verificati…

SDSS-V Milky Way Mapper (MWM): ASPCAP Stellar Parameters and Abundances in SDSS-V Data Release 19
Szabolcs M\'esz\'aros, Paula Jofr\'e, Jennifer A. Johnson, Jonathan C. Bird, Andrew R. Casey, Katia Cunha, Nathan De Lee, Peter Frinchaboy, Guillaume Guiglion, Viola Heged\H{u}s, Alex P. Ji, Juna A. Kollmeier, Melissa K. Ness, Jonah Otto, Marc H. Pinsonneault, Alexandre Roman-Lopes, Amaya Sinha, Ying-Yi Song, Guy S. Stringfellow, Keivan G. Stassun, Jamie Tayar, Andrew Tkachenko…

SDSS-V Milky Way Mapper (MWM): ASPCAP Stellar Parameters and Abundances in SDSS-V Data Release 19
The goal of this paper is to describe the science verification of Milky Way Mapper (MWM) ASPCAP data products published in Data Release 19 (DR19) of the fifth phase of the Sloan Digital Sky Survey (SDSS-V). We compare MWM ASPCAP atmospheric parameters T$_{\rm eff}$, log g, 24 abundances of 21 elements (carbon, nitrogen, and oxygen have multiple sources for deriving their abundance values) and their uncertainties determined from APOGEE spectrograph spectra with those of the literature and evalua…

This https://arxiv.org/abs/2405.00295 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Proof of Sampling: A Nash Equilibrium-Based Verification Protocol for Decentralized Systems
This paper introduces the Proof of Sampling (PoSP) protocol, a Nash Equilibrium-based verification mechanism, and its application to decentralized machine learning inference through spML. Our protocol has a pure strategy Nash Equilibrium, compelling rational participants to act honestly. It economically disincentivizes dishonest behavior, making it costly for participants to compromise the network's integrity. In our spML protocol, we apply PoSP to decentralized inference for AI applications vi…

Model Checking as Program Verification by Abstract Interpretation (Extended Version)
Paolo Baldan, Roberto Bruni, Francesco Ranzato, Diletta Rigo
https://arxiv.org/abs/2506.05525 …

Model Checking as Program Verification by Abstract Interpretation (Extended Version)
Abstract interpretation offers a powerful toolset for static analysis, tackling precision, complexity and state-explosion issues. In the literature, state partitioning abstractions based on (bi)simulation and property-preserving state relations have been successfully applied to abstract model checking. Here, we pursue a different track in which model checking is seen as an instance of program verification. To this purpose, we introduce a suitable language-called MOKA (for MOdel checking as abst…

It notes (para 37) that under this push for Age verification “the occurrence of security breaches should be expected”

CHIP: Chameleon Hash-based Irreversible Passport for Robust Deep Model Ownership Verification and Active Usage Control
Chaohui Xu, Qi Cui, Chip-Hong Chang
https://arxiv.org/abs/2505.24536

CHIP: Chameleon Hash-based Irreversible Passport for Robust Deep Model Ownership Verification and Active Usage Control
The pervasion of large-scale Deep Neural Networks (DNNs) and their enormous training costs make their intellectual property (IP) protection of paramount importance. Recently introduced passport-based methods attempt to steer DNN watermarking towards strengthening ownership verification against ambiguity attacks by modulating the affine parameters of normalization layers. Unfortunately, neither watermarking nor passport-based methods provide a holistic protection with robust ownership proof, hig…

This https://arxiv.org/abs/2504.07732 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Efficient Formal Verification of Quantum Error Correcting Programs
Quantum error correction (QEC) is fundamental for suppressing noise in quantum hardware and enabling fault-tolerant quantum computation. In this paper, we propose an efficient verification framework for QEC programs. We define an assertion logic and a program logic specifically crafted for QEC programs and establish a sound proof system. We then develop an efficient method for handling verification conditions (VCs) of QEC programs: for Pauli errors, the VCs are reduced to classical assertions t…

CNFs and DNFs with Exactly $k$ Solutions
L. Sunil Chandran, Rishikesh Gajjala, Kuldeep S. Meel
https://arxiv.org/abs/2506.07268 https://

CNFs and DNFs with Exactly $k$ Solutions
Model counting is a fundamental problem that consists of determining the number of satisfying assignments for a given Boolean formula. The weighted variant, which computes the weighted sum of satisfying assignments, has extensive applications in probabilistic reasoning, network reliability, statistical physics, and formal verification. A common approach for solving weighted model counting is to reduce it to unweighted model counting, which raises an important question: {\em What is the minimum …

Companies House have just sent me an email telling me that because of new laws, I need to verify my identity. So I leapt into action. There follows an open letter.
Dear Companies House.
The questions "Do you have a passport?" and "Do you have your passport on you in the office right now?" are different fucking questions and you should clarify which you mean before you direct me down an irreversible cul-de-sac in your application's verification logic.

Reward Models Enable Scalable Code Verification by Trading Accuracy for Throughput
Gabriel Orlanski, Nicholas Roberts, Aws Albarghouthi, Frederic Sala
https://arxiv.org/abs/2506.10056

Reward Models Enable Scalable Code Verification by Trading Accuracy for Throughput
The standard paradigm for solving coding tasks via large language models (LLMs) is to generate-then-rank programs, where the latter step uses a verifier in the ranking process. The growing consensus is that a comprehensive verifier (e.g., a full test suite) should be prioritized over an outcome reward model (ORM) whenever possible, with little consideration given to the trade-offs involved. We aim to challenge this assumption by systematically exploring the tradeoff between speed and accuracy. …

This https://arxiv.org/abs/2505.18492 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Enumerate-Conjecture-Prove: Formally Solving Answer-Construction Problems in Math Competitions
Mathematical reasoning lies at the heart of artificial intelligence, underpinning applications in education, program verification, and research-level mathematical discovery. Mathematical competitions, in particular, present two challenging problem types: theorem-proving, requiring rigorous proofs of stated conclusions, and answer-construction, involving hypothesizing and formally verifying mathematical objects. Large Language Models (LLMs) effectively generate creative candidate answers but str…

Thermodynamic Constraints in DRAM cells: Experimental Verification of Energy Efficiency Limits in Information Erasure
Takase Shimizu, Kensaku Chida, Gento Yamahata, Katsuhiko Nishiguchi
https://arxiv.org/abs/2505.23087

Thermodynamic Constraints in DRAM cells: Experimental Verification of Energy Efficiency Limits in Information Erasure
We measured the energy efficiency of information erasure using silicon DRAM cells capable of counting charges on capacitors at the single-electron level. Our measurements revealed that the efficiency decreased as the erasure error rate decreased, and notably, the Landauer limit was not achieved even under effectively infinite-time operation. By comparing the measured efficiency with the Landauer limit, we identified a thermodynamic constraint that prevents DRAM from reaching this limit: the ina…

This https://arxiv.org/abs/2305.03748 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Certifying the activation of Bell nonlocality with finite data
The activation of Bell nonlocality is a protocol that enables the violation of a Bell inequality from a system that initially did not allow for any such violation because the state of the system was Bell-local. This activation of hidden Bell nonlocality has been demonstrated in experiments; however, while the certification of Bell nonlocality is conceptional straightforward, a statistically rigorous verification that the initial state is Bell-local has not yet been achieved. This is due to two …

RE-oriented Model Development with LLM Support and Deduction-based Verification
Radoslaw Klimek
https://arxiv.org/abs/2506.08606 https://

RE-oriented Model Development with LLM Support and Deduction-based Verification
The requirements engineering (RE) phase is pivotal in developing high-quality software. Integrating advanced modelling techniques with large language models (LLMs) and formal verification in a logical style can significantly enhance this process. We propose a comprehensive framework that focuses on specific Unified Modelling Language (UML) diagrams for preliminary system development. This framework offers visualisations at various modelling stages and seamlessly integrates large language models…

On the influence of language similarity in non-target speaker verification trials
Paul M. Reuter, Michael Jessen
https://arxiv.org/abs/2506.02777 https://

On the influence of language similarity in non-target speaker verification trials
In this paper, we investigate the influence of language similarity in cross-lingual non-target speaker verification trials using a state-of-the-art speaker verification system, ECAPA-TDNN, trained on multilingual and monolingual variants of the VoxCeleb dataset. Our analysis of the score distribution patterns on multilingual Globalphone and LDC CTS reveals a clustering effect in speaker comparisons involving a training language, whereby the choice of comparison language only minimally impacts s…

STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving
Christian Fruhwirth-Reisinger, Du\v{s}an Mali\'c, Wei Lin, David Schinagl, Samuel Schulter, Horst Possegger
https://arxiv.org/abs/2506.06218

STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving
We introduce STSBench, a scenario-based framework to benchmark the holistic understanding of vision-language models (VLMs) for autonomous driving. The framework automatically mines pre-defined traffic scenarios from any dataset using ground-truth annotations, provides an intuitive user interface for efficient human verification, and generates multiple-choice questions for model evaluation. Applied to the NuScenes dataset, we present STSnu, the first benchmark that evaluates the spatio-temporal …

Radionuclide Production for Dose Verification in VHEE FLASH Radiotherapy
Francesco Urso, Federica Baffigi, Esther Ciarrocchi, Leonida Antonio Gizzi, Petra Koester, Luca Labate, Matteo Morrocchi, Simona Piccinini, Martina Salvadori, Maria Giuseppina Bisogni
https://arxiv.org/abs/2505.21183

Radionuclide Production for Dose Verification in VHEE FLASH Radiotherapy
This study explores the production of radionuclides in a PMMA (Polymethylmethacrylate) phantom irradiated with Very High Energy Electrons (VHEE) beams as a novel method for dose verification. In this work, Monte Carlo simulation studies using the Geant4 toolkit and experimental measurements with a VHEE beam produced by a laser-plasma accelerator were conducted. Specifically, the photonuclear production of 11C, 15O and 13N is examined, with a detailed analysis of their spatial distribution, prod…

This https://arxiv.org/abs/2410.16428 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Neural Scoring: A Refreshed End-to-End Approach for Speaker Recognition in Complex Conditions
Modern speaker verification systems primarily rely on speaker embeddings and cosine similarity. While effective, these methods struggle with multi-talker speech due to the unidentifiability of embedding vectors. We propose Neural Scoring (NS), a novel end-to-end framework that directly estimates verification posterior probabilities without relying on test-side embeddings, making it more powerful and robust to complex conditions, e.g., with multiple talkers. To address the challenge of training …

On-The-Fly Symbolic Algorithm for Timed ATL with Abstractions
Nicolaj {\O}. Jensen, Kim G. Larsen, Didier Lime, Ji\v{r}\'i Srba
https://arxiv.org/abs/2506.07802

On-The-Fly Symbolic Algorithm for Timed ATL with Abstractions
Verification of real-time systems with multiple components controlled by multiple parties is a challenging task due to its computational complexity. We present an on-the-fly algorithm for verifying timed alternating-time temporal logic (TATL), a branching-time logic with quantifiers over outcomes that results from coalitions of players in such systems. We combine existing work on games and timed CTL verification in the abstract dependency graph (ADG) framework, which allows for easy creation of…

Verification of the Timing System for the X-ray Imaging and Spectroscopy Mission in the GPS Unsynchronized Mode
Megumi Shidatsu, Yukikatsu Terada, Takashi Kominato, So Kato, Ryohei Sato, Minami Sakama, Takumi Shioiri, Yugo Motogami, Yuuki Niida, Chulsoo Kang, Toshihiro Takagi, Taichi Nakamoto, Chikara Natsukari, Makoto S. Tashiro, Kenichi Toda, Hironori Maejima, Shin Watanabe, Ryo Iizuka, Rie Sato, Chris Baluta, Katsuhiro Hayashi, Tessei Yoshida, Shoji Ogawa, Yoshiaki Kanemaru, Kotaro Fukushima, Akio Hoshino, Hiromitsu Takahashi, Masayoshi Nobukawa, Tsunefumi Mizuno, Kazuhiro Nakazawa, Shinichiro Uno, Ken Ebisawa, Satoshi Eguchi, Satoru Katsuda, Aya Kubota, Naomi Ota, Atsushi Tanimoto, Yuichi Terashima, Yohko Tsuboi, Yuusuke Uchida, Hideki Uchiyama, Shigeo Yamauchi, Tomokage Yoneyama, Satoshi Yamada, Nagomi Uchida, Matt Holland, Michael Loewenstein, Tahir Yaqoob, Eric D. Miller, Robert S. Hill, Efrain C. Perez-Solis, Morgan D. Waddy, Mark Mekosh, Joseph B. Fox, Isabella S. Brewer, Emily Aldoretta, Koji Mukai, Kenji Hamaguchi, Francois Mernier, Anna Ogorzalek, Katja Pottschmidt, Mihoko Yukita
#toXiv_bot_toot

This https://arxiv.org/abs/2502.18560 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Quantum decoherence of gravitational waves
The quantum nature of gravity remains an open question in fundamental physics, lacking experimental verification. Gravitational waves (GWs) provide a potential avenue for detecting gravitons, the hypothetical quantum carriers of gravity. However, by analogy with quantum optics, distinguishing gravitons from classical GWs requires the preservation of quantum coherence, which may be lost due to interactions with the cosmic environment causing decoherence. We investigate whether GWs retain their q…

This https://arxiv.org/abs/2007.07190 has been replaced.
link: https://scholar.google.com/scholar?q=a

Anomalous dimensions for $ϕ^n$ in scale invariant $d=3$ theory
Recently it was shown that the scaling dimension of the operator $ϕ^n$ in scale-invariant $d=3$ theory may be computed semiclassically, and this was verified to leading order (two loops) in perturbation theory at leading and subleading $n$. Here we extend this verification to six loops, once again at leading and subleading $n$. We then perform a similar exercise for a theory with a multiplet of real scalars and an $O(N)$ invariant hexic interaction. We also investigate the strong-coupling regi…

WGLE:Backdoor-free and Multi-bit Black-box Watermarking for Graph Neural Networks
Tingzhi Li, Xuefeng Liu
https://arxiv.org/abs/2506.08602 https://

WGLE:Backdoor-free and Multi-bit Black-box Watermarking for Graph Neural Networks
Graph Neural Networks (GNNs) are increasingly deployed in graph-related applications, making ownership verification critical to protect their intellectual property against model theft. Fingerprinting and black-box watermarking are two main methods. However, the former relies on determining model similarity, which is computationally expensive and prone to ownership collisions after model post-processing such as model pruning or fine-tuning. The latter embeds backdoors, exposing watermarked model…

A Retrieval-Augmented Multi-Agent Framework for Psychiatry Diagnosis
Mengxi Xiao, Mang Ye, Ben Liu, Xiaofen Zong, He Li, Jimin Huang, Qianqian Xie, Min Peng
https://arxiv.org/abs/2506.03750

A Retrieval-Augmented Multi-Agent Framework for Psychiatry Diagnosis
The application of AI in psychiatric diagnosis faces significant challenges, including the subjective nature of mental health assessments, symptom overlap across disorders, and privacy constraints limiting data availability. To address these issues, we present MoodAngels, the first specialized multi-agent framework for mood disorder diagnosis. Our approach combines granular-scale analysis of clinical assessments with a structured verification process, enabling more accurate interpretation of co…

Rigorous theory of coupled resonators
E. A. Muljarov
https://arxiv.org/abs/2506.04413 https://arxiv.org/pdf/2506.04413

Rigorous theory of coupled resonators
We demonstrate the general failure of the famous concept of tight binding and mode hybridization underlying modern theories of coupled open resonators. In spite of sophisticated examples in the literature, successfully illustrating these theories, the latter fail to describe any planar systems. This includes the simplest possible case of two dielectric slabs placed next to each other or separated by a distance, which is straightforward for verification, due to its analytical solvability. We pre…

The EU intends to introduce a universal app for online age verification, for adults and children alike.
Done ahead of the implementation of a broader Digital wallet.
See page 11 of their recently launched guidelines (which are open for feedback);

This https://arxiv.org/abs/2403.13457 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSC_…

OSVAuto: automatic proofs about functional specifications in OS verification
We present OSVAuto for automatic proofs about functional specifications that commonly arise when verifying operating system kernels. The algorithm behind OSVAuto is designed to support natively those data types that commonly occur in OS verification, including sequences, maps, structures and enumerations. Propositions about these data are encoded into a form that is suitable for SMT solving. For quantifier instantiation, we propose an extension of recent work for automatic proofs about sequence…

A generating set of Reidemeister moves of oriented virtual knots
Danish Ali
https://arxiv.org/abs/2505.24094 https://arxiv.org/pdf/25…

A generating set of Reidemeister moves of oriented virtual knots
In oriented knot theory, verifying a quantity is an invariant involves checking its invariance under all oriented Reidemeister moves, a process that can be intricate and time-consuming. A generating set of oriented moves simplifies this by requiring verification for only a minimal subset from which all other moves can be derived. While generating sets for classical oriented Reidemeister moves are well-established, their virtual counterparts are less explored. In this study, we enumerate the ori…

Monitorability for the Modal mu-Calculus over Systems with Data: From Practice to Theory
Luca Aceto, Antonis Achilleos, Duncan Paul Attard, L\'eo Exibard, Adrian Francalanza, Anna Ing\'olfsd\'ottir, Karoliina Lehtinen
https://arxiv.org/abs/2506.06172

Monitorability for the Modal mu-Calculus over Systems with Data: From Practice to Theory
Runtime verification, also known as runtime monitoring, consists of checking whether a system satisfies a given specification by observing the trace it produces during its execution. It is used as a lightweight verification technique to complement or substitute costlier methods such as model-checking. In the regular setting, Hennessy-Milner logic with recursion, a variant of the modal mu-calculus, provides a versatile formalism for expressing linear- and branching-time specifications of the c…

Logic Mining from Process Logs: Towards Automated Specification and Verification
Radoslaw Klimek, Julia Witek
https://arxiv.org/abs/2506.08628 https://

Logic Mining from Process Logs: Towards Automated Specification and Verification
Logical specifications play a key role in the formal analysis of behavioural models. Automating the derivation of such specifications is particularly valuable in complex systems, where manual construction is time-consuming and error-prone. This article presents an approach for generating logical specifications from process models discovered via workflow mining, combining pattern-based translation with automated reasoning techniques. In contrast to earlier work, we evaluate the method on both ge…

Automated Formal Verification of Area-Optimized Safety Registers in Automotive SoCs
Shuhang Zhang, Bryan Olmos
https://arxiv.org/abs/2505.17990 https://

Automated Formal Verification of Area-Optimized Safety Registers in Automotive SoCs
Registers are primary storage elements in System-on-chip~(SoC) designs and play an important role in maintaining state information and processing data in digital systems. With respect to the ISO26262 standard, these registers require high levels of reliability and fault tolerance. For this reason, safety-critical applications require that normal registers are equipped with additional safety components to construct safety registers, which ensure system stability and fault tolerance. However, the…

VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification
Patrick Yubeaton, Andre Nakkab, Weihua Xiao, Luca Collini, Ramesh Karri, Chinmay Hegde, Siddharth Garg
https://arxiv.org/abs/2505.20302

VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification
This paper introduces VeriThoughts, a novel dataset designed for reasoning-based Verilog code generation. We establish a new benchmark framework grounded in formal verification methods to evaluate the quality and correctness of generated hardware descriptions. Additionally, we present a suite of specialized small-scale models optimized specifically for Verilog generation. Our work addresses the growing need for automated hardware design tools that can produce verifiably correct implementations …

Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning
Fangyu Lei, Jinxiang Meng, Yiming Huang, Tinghong Chen, Yun Zhang, Shizhu He, Jun Zhao, Kang Liu
https://arxiv.org/abs/2506.01710

Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning
Table reasoning, encompassing tasks such as table question answering, fact verification, and text-to-SQL, requires precise understanding of structured tabular data, coupled with numerical computation and code manipulation for effective inference. Supervised fine-tuning (SFT) approaches have achieved notable success but often struggle with generalization and robustness due to biases inherent in imitative learning. We introduce Reasoning-Table, the first application of reinforcement learning (RL)…

This https://arxiv.org/abs/2505.10328 has been replaced.
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A Comparative Study of SMT and MILP for the Nurse Rostering Problem
The effects of personnel scheduling on the quality of care and working conditions for healthcare personnel have been thoroughly documented. However, the ever-present demand and large variation of constraints make healthcare scheduling particularly challenging. This problem has been studied for decades, with limited research aimed at applying Satisfiability Modulo Theories (SMT). SMT has gained momentum within the formal verification community in the last decades, leading to the advancement of S…

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
Saif E. Nouma, Attila A. Yavuz
https://arxiv.org/abs/2506.08781

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
The growing deployment of resource-limited Internet of Things (IoT) devices and their expanding attack surfaces demand efficient and scalable security mechanisms. System logs are vital for the trust and auditability of IoT, and offloading their maintenance to a Cold Storage-as-a-Service (Cold-STaaS) enhances cost-effectiveness and reliability. However, existing cryptographic logging solutions either burden low-end IoT devices with heavy computation or create verification delays and storage inef…

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Rolf Drechsler
https://arxiv.org/abs/2505.23311 https://

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Verification is one of the central tasks in circuit and system design. While simulation and emulation are widely used, complete correctness can only be ensured based on formal proof techniques. But these approaches often have very high run time and memory requirements. Recently, Polynomial Formal Verification (PFV) has been introduced showing that for many instances of practical relevance upper bounds on needed resources can be given. But proofs have to be provided that are human-readable. He…

ROSGuard: A Bandwidth Regulation Mechanism for ROS2-based Applications
Jon Altonaga Puente, Enrico Mezzetti, Irune Agirre Troncoso, Jaume Abella Ferrer, Francisco J. Cazorla Almeida
https://arxiv.org/abs/2506.04640

ROSGuard: A Bandwidth Regulation Mechanism for ROS2-based Applications
Multicore timing interference, arising when multiple requests contend for the same shared hardware resources, is a primary concern for timing verification and validation of time-critical applications. Bandwidth control and regulation approaches have been proposed in the literature as an effective method to monitor and limit the impact of timing interference at run time. These approaches seek for fine-grained control of the bandwidth consumption (at the microsecond level) to meet stringent timin…

The European Data Protection Board made its policy statement on Age Verification technologies its very first of 2025:
https://www.edpb.europa.eu/system/files/2025-04/edpb_statement_20250211ageassurance_v1-2_en.pdf

Modal Verification Patterns for Systems
Ismail Kuru, Colin S. Gordon
https://arxiv.org/abs/2506.01719 https://arxiv.org/pdf/2506.0171…

Modal Verification Patterns for Systems
Although they differ in the functionality they offer, low-level systems exhibit certain patterns of design and utilization of computing resources. In this paper, we argue the position that modalities, in the sense of modal logic, should be a go-to approach when specifying and verifying low-level systems code. We explain how the concept of a resource context helps guide the design of new modalities for verification of systems code, and we justify our perspective by discussing prior systems that …

This https://arxiv.org/abs/2501.14478 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Alignment and optical verification of DESHIMA 2.0 at ASTE
We developed, characterized, and verified an alignment procedure for the DESHIMA 2.0 instrument, an ultra wide-band spectrometer operating between 200--400 GHz, at the ASTE telescope. To this end, we mounted the warm optics, consisting of a modified Dragonian dual reflector system, on a motor controlled hexapod. Crucial in the alignment procedure is our sky chopper, which allows fast beam switching. It has a small entrance and exit aperture coupling to (cold) sky, which creates a measurable sig…

You Are What You Say: Exploiting Linguistic Content for VoicePrivacy Attacks
\"Unal Ege Gaznepoglu, Anna Leschanowsky, Ahmad Aloradi, Prachi Singh, Daniel Tenbrinck, Emanu\"el A. P. Habets, Nils Peters
https://arxiv.org/abs/2506.09521

You Are What You Say: Exploiting Linguistic Content for VoicePrivacy Attacks
Speaker anonymization systems hide the identity of speakers while preserving other information such as linguistic content and emotions. To evaluate their privacy benefits, attacks in the form of automatic speaker verification (ASV) systems are employed. In this study, we assess the impact of intra-speaker linguistic content similarity in the attacker training and evaluation datasets, by adapting BERT, a language model, as an ASV system. On the VoicePrivacy Attacker Challenge datasets, our metho…

Stochastically Dominant Peer Prediction
Yichi Zhang, Shengwei Xu, David Pennock, Grant Schoenebeck
https://arxiv.org/abs/2506.02259 https://

Stochastically Dominant Peer Prediction
Eliciting reliable human feedback is essential for many machine learning tasks, such as learning from noisy labels and aligning AI systems with human preferences. Peer prediction mechanisms incentivize truthful reporting without ground truth verification by scoring agents based on correlations with peers. Traditional mechanisms, which ensure that truth-telling maximizes the expected scores in equilibrium, can elicit honest information while assuming agents' utilities are linear functions of the…

BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
Surya Jasper, Minh Luu, Evan Pan, Aakash Tyagi, Michael Quinn, Jiang Hu, David Kebo Houngninou
https://arxiv.org/abs/2506.10501

BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
Hardware complexity continues to strain verification resources, motivating the adoption of machine learning (ML) methods to improve debug efficiency. However, ML-assisted debugging critically depends on diverse and scalable bug datasets, which existing manual or automated bug insertion methods fail to reliably produce. We introduce BugGen, a first of its kind, fully autonomous, multi-agent pipeline leveraging Large Language Models (LLMs) to systematically generate, insert, and validate realisti…

This https://arxiv.org/abs/2501.08249 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Verifying Device Drivers with Pancake
Device driver bugs are the leading cause of OS compromises, and their formal verification is therefore highly desirable. To the best of our knowledge, no realistic and performant driver has been verified for a non-trivial device. We propose Pancake, an imperative language for systems programming that features a well-defined and verification-friendly semantics. Leveraging the verified compiler backend of the CakeML functional language, we develop a compiler for Pancake that guarantees that the b…

Dyna-Think: Synergizing Reasoning, Acting, and World Model Simulation in AI Agents
Xiao Yu, Baolin Peng, Ruize Xu, Michel Galley, Hao Cheng, Suman Nath, Jianfeng Gao, Zhou Yu
https://arxiv.org/abs/2506.00320

Dyna-Think: Synergizing Reasoning, Acting, and World Model Simulation in AI Agents
Recent progress in reasoning with large language models (LLMs), such as DeepSeek-R1, demonstrates impressive capabilities in domains like mathematics and coding, by exhibiting complex cognitive behaviors such as verification, goal decomposition, and self-reflection. However, it is unclear what behavior is effective and what behavior is missing for long-horizon AI agents tasks. In this work, we propose Dyna-Think, a thinking framework that integrates planning with an internal world model with re…

Next Generation Authentication for Data Spaces: An Authentication Flow Based On Grant Negotiation And Authorization Protocol For Verifiable Presentations (GNAP4VP)
Rodrigo Men\'endez, Andres Munoz-Arcentales, Joaqu\'in Salvach\'ua, Carlos Aparicio, Irene Plaza, Gabriel Huecas
https://arxiv.org/abs/2505.24698

Next Generation Authentication for Data Spaces: An Authentication Flow Based On Grant Negotiation And Authorization Protocol For Verifiable Presentations (GNAP4VP)
Identity verification in Data Spaces is a fundamental aspect of ensuring security and privacy in digital environments. This paper presents an identity verification protocol tailored for shared data environments within Data Spaces. This protocol extends the Grant Negotiation and Authorization Protocol (GNAP) and integrates OpenID Connect for Verifiable Presentations (OIDC4VP) along with support for Linked Verifiable Presentations (LVP), providing a robust foundation for secure and privacy-preser…

Generating Automotive Code: Large Language Models for Software Development and Verification in Safety-Critical Systems
Sven Kirchner, Alois C. Knoll
https://arxiv.org/abs/2506.04038

Generating Automotive Code: Large Language Models for Software Development and Verification in Safety-Critical Systems
Developing safety-critical automotive software presents significant challenges due to increasing system complexity and strict regulatory demands. This paper proposes a novel framework integrating Generative Artificial Intelligence (GenAI) into the Software Development Lifecycle (SDLC). The framework uses Large Language Models (LLMs) to automate code generation in languages such as C++, incorporating safety-focused practices such as static verification, test-driven development and iterative refi…

And, for context, here’s Ireland’s head of Internet regulation, describing his ideas for how age verification ought to work.
Note the plan involves legislating for children to send selfies to access porn sites.

Backward Responsibility in Transition Systems Beyond Safety
Christel Baier, Rio Klatt, Sascha Kl\"uppelholz, Johannes Lehmann
https://arxiv.org/abs/2506.05192

Backward Responsibility in Transition Systems Beyond Safety
As the complexity of software systems rises, methods for explaining their behaviour are becoming ever-more important. When a system fails, it is critical to determine which of its components are responsible for this failure. Within the verification community, one approach uses graph games and the Shapley value to ascribe a responsibility value to every state of a transition system. As this is done with respect to a specific failure, it is called backward responsibility. This paper provides ti…

MultiCoSim: A Python-based Multi-Fidelity Co-Simulation Framework
Quinn Thibeault, Giulia Pedrielli
https://arxiv.org/abs/2506.10869 https://

MultiCoSim: A Python-based Multi-Fidelity Co-Simulation Framework
Simulation is a foundational tool for the analysis and testing of cyber-physical systems (CPS), underpinning activities such as algorithm development, runtime monitoring, and system verification. As CPS grow in complexity and scale, particularly in safety-critical and learning-enabled settings, accurate analysis and synthesis increasingly rely on the rapid use of simulation experiments. Because CPS inherently integrate hardware, software, and physical processes, simulation platforms must suppor…

This https://arxiv.org/abs/2301.06136 has been replaced.
link: https://scholar.google.com/scholar?q=a

Quantitative Verification with Neural Networks
We present a data-driven approach to the quantitative verification of probabilistic programs and stochastic dynamical models. Our approach leverages neural networks to compute tight and sound bounds for the probability that a stochastic process hits a target condition within finite time. This problem subsumes a variety of quantitative verification questions, from the reachability and safety analysis of discrete-time stochastic dynamical models, to the study of assertion-violation and terminatio…

This https://arxiv.org/abs/2410.10946 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Equivalence checking of quantum circuits via intermediary matrix product operator
As quantum computing advances, the complexity of quantum circuits is rapidly increasing, driving the need for robust methods to aid in their design. Equivalence checking plays a vital role in identifying errors that may arise during compilation and optimization of these circuits and is a critical step in quantum circuit verification. In this work, we introduce a novel method based on Matrix Product Operators (MPOs) for determining the equivalence of quantum circuits. Our approach contracts tens…

There's Waldo: PCB Tamper Forensic Analysis using Explainable AI on Impedance Signatures
Maryam Saadat Safa, Seyedmohammad Nouraniboosjin, Fatemeh Ganji, Shahin Tajik
https://arxiv.org/abs/2506.05734

There's Waldo: PCB Tamper Forensic Analysis using Explainable AI on Impedance Signatures
The security of printed circuit boards (PCBs) has become increasingly vital as supply chain vulnerabilities, including tampering, present significant risks to electronic systems. While detecting tampering on a PCB is the first step for verification, forensics is also needed to identify the modified component. One non-invasive and reliable PCB tamper detection technique with global coverage is the impedance characterization of a PCB's power delivery network (PDN). However, it is an open question…

BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies
Kourosh Shahnazari, Seyed Moein Ayyoubzadeh, Mohammadali Keshtparvar
https://arxiv.org/abs/2506.00328

BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies
The quest for interpretable reinforcement learning is a grand challenge for the deployment of autonomous decision-making systems in safety-critical applications. Modern deep reinforcement learning approaches, while powerful, tend to produce opaque policies that compromise verification, reduce transparency, and impede human oversight. To address this, we introduce BASIL (Best-Action Symbolic Interpretable Learning), a systematic approach for generating symbolic, rule-based policies via online ev…

Veritas: Deterministic Verilog Code Synthesis from LLM-Generated Conjunctive Normal Form
Prithwish Basu Roy, Akashdeep Saha, Manaar Alam, Johann Knechtel, Michail Maniatakos, Ozgur Sinanoglu, Ramesh Karri
https://arxiv.org/abs/2506.00005

Veritas: Deterministic Verilog Code Synthesis from LLM-Generated Conjunctive Normal Form
Automated Verilog code synthesis poses significant challenges and typically demands expert oversight. Traditional high-level synthesis (HLS) methods often fail to scale for real-world designs. While large language models (LLMs) have enhanced scalability, they often introduce syntactical and logical errors requiring extensive post-generation verification. Here, we introduce a novel conjunctive normal form (CNF)-guided synthesis methodology. The idea is to have an LLM generate CNF clauses, a form…

Compositional Reasoning for Parametric Probabilistic Automata
Hannah Mertens, Tim Quatmann, Joost-Pieter Katoen
https://arxiv.org/abs/2506.08525 https://…

Compositional Reasoning for Parametric Probabilistic Automata
We establish an assume-guarantee (AG) framework for compositional reasoning about multi-objective queries in parametric probabilistic automata (pPA) - an extension to probabilistic automata (PA), where transition probabilities are functions over a finite set of parameters. We lift an existing framework for PA to the pPA setting, incorporating asymmetric, circular, and interleaving proof rules. Our approach enables the verification of a broad spectrum of multi-objective queries for pPA, encompas…

This https://arxiv.org/abs/2502.12267 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

NeuroStrata: Harnessing Neurosymbolic Paradigms for Improved Design, Testability, and Verifiability of Autonomous CPS
Autonomous cyber-physical systems (CPSs) leverage AI for perception, planning, and control but face trust and safety certification challenges due to inherent uncertainties. The neurosymbolic paradigm replaces stochastic layers with interpretable symbolic AI, enabling determinism. While promising, challenges like multisensor fusion, adaptability, and verification remain. This paper introduces NeuroStrata, a neurosymbolic framework to enhance the testing and verification of autonomous CPS. We out…

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
Kai Li, Conggai Li, Xin Yuan, Shenghong Li, Sai Zou, Syed Sohail Ahmed, Wei Ni, Dusit Niyato, Abbas Jamalipour, Falko Dressler, Ozgur B. Akan
https://arxiv.org/abs/2505.23792

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
This paper focuses on Zero-Trust Foundation Models (ZTFMs), a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models (FMs) for Internet of Things (IoT) systems. By integrating core tenets, such as continuous verification, least privilege access (LPA), data confidentiality, and behavioral analytics into the design, training, and deployment of FMs, ZTFMs can enable secure, privacy-preserving AI across distributed, heterogeneous, and potentially adversari…

This https://arxiv.org/abs/2504.03517 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

A framework for computing upper bounds in passive learning settings
The task of inferring logical formulas from examples has garnered significant attention as a means to assist engineers in creating formal specifications used in the design, synthesis, and verification of computing systems. Among various approaches, enumeration algorithms have emerged as some of the most effective techniques for this task. These algorithms employ advanced strategies to systematically enumerate candidate formulas while minimizing redundancies by avoiding the generation of syntact…

The Vampire Diary
Filip B\'artek, Ahmed Bhayat, Robin Coutelier, M\'arton Hajdu, Matthias Hetzenberger, Petra Hozzov\'a, Laura Kov\'acs, Jakob Rath, Michael Rawson, Giles Reger, Martin Suda, Johannes Schoisswohl, Andrei Voronkov
https://arxiv.org/abs/2506.03030

The Vampire Diary
During the past decade of continuous development, the theorem prover Vampire has become an automated solver for the combined theories of commonly-used data structures. Vampire now supports arithmetic, induction, and higher-order logic. These advances have been made to meet the demands of software verification, enabling Vampire to effectively complement SAT/SMT solvers and aid proof assistants. We explain how best to use Vampire in practice and review the main changes Vampire has undergone since…

Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization
Zhiwei Zhang, Samy Wu Fung, Anastasios Kyrillidis, Stanley Osher, Moshe Y. Vardi
https://arxiv.org/abs/2506.00674

Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization
The Boolean satisfiability (SAT) problem lies at the core of many applications in combinatorial optimization, software verification, cryptography, and machine learning. While state-of-the-art solvers have demonstrated high efficiency in handling conjunctive normal form (CNF) formulas, numerous applications require non-CNF (hybrid) constraints, such as XOR, cardinality, and Not-All-Equal constraints. Recent work leverages polynomial representations to represent such hybrid constraints, but it re…

This https://arxiv.org/abs/2405.17492 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

StatWhy: Formal Verification Tool for Statistical Hypothesis Testing Programs
Statistical methods have been widely misused and misinterpreted in various scientific fields, raising significant concerns about the integrity of scientific research. To mitigate this problem, we propose a tool-assisted method for formally specifying and automatically verifying the correctness of statistical programs. In this method, programmers are required to annotate the source code of the statistical programs with the requirements for these methods. Through this annotation, they are reminde…

This https://arxiv.org/abs/2504.03517 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

A framework for computing upper bounds in passive learning settings
The task of inferring logical formulas from examples has garnered significant attention as a means to assist engineers in creating formal specifications used in the design, synthesis, and verification of computing systems. Among various approaches, enumeration algorithms have emerged as some of the most effective techniques for this task. These algorithms employ advanced strategies to systematically enumerate candidate formulas while minimizing redundancies by avoiding the generation of syntact…

Boosting Open-Source LLMs for Program Repair via Reasoning Transfer and LLM-Guided Reinforcement Learning
Xunzhu Tang, Jacques Klein, Tegawend\'e F. Bissyand\'e
https://arxiv.org/abs/2506.03921

Boosting Open-Source LLMs for Program Repair via Reasoning Transfer and LLM-Guided Reinforcement Learning
Several closed-source LLMs have consistently outperformed open-source alternatives in program repair tasks, primarily due to their superior reasoning capabilities and extensive pre-training. This paper introduces Repairity, a novel three-stage methodology that significantly narrows this performance gap through reasoning extraction and reinforcement learning. Our approach: (1) systematically filters high-quality reasoning traces from closed-source models using correctness verification, (2) trans…

Legal Compliance Evaluation of Smart Contracts Generated By Large Language Models
Chanuka Wijayakoon, Hai Dong, H. M. N. Dilum Bandara, Zahir Tari, Anurag Soin
https://arxiv.org/abs/2506.00943

Legal Compliance Evaluation of Smart Contracts Generated By Large Language Models
Smart contracts can implement and automate parts of legal contracts, but ensuring their legal compliance remains challenging. Existing approaches such as formal specification, verification, and model-based development require expertise in both legal and software development domains, as well as extensive manual effort. Given the recent advances of Large Language Models (LLMs) in code generation, we investigate their ability to generate legally compliant smart contracts directly from natural lang…

This https://arxiv.org/abs/2504.06592 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

On Coalgebraic Product Constructions for Markov Chains and Automata
Verifying traces of systems is a central topic in formal verification. We study model checking of Markov chains (MCs) against temporal properties represented as (finite) automata. For instance, given an MC and a deterministic finite automaton (DFA), a simple but practically useful model checking problem asks for the probability of traces on the MC that are accepted by the DFA. A standard approach to solving this problem constructs a product MC of the given MC and DFA, reducing the task to a sim…