Tootfinder

🏘️ To spur the construction of affordable, resilient homes, the future is concrete
https://theconversation.com/to-spur-the-construction-of-affordable-resilient-homes-the-future-is-concrete-254561

To spur the construction of affordable, resilient homes, the future is concrete
When most Americans imagine a home, they picture a wood-framed house. But in an era of high housing costs and extreme weather events, precast concrete offers a mix of durability and efficiency.

A Bayesian Incentive Mechanism for Poison-Resilient Federated Learning
Daniel Commey, Rebecca A. Sarpong, Griffith S. Klogo, Winful Bagyl-Bac, Garth V. Crosby
https://arxiv.org/abs/2507.12439

A Bayesian Incentive Mechanism for Poison-Resilient Federated Learning
Federated learning (FL) enables collaborative model training across decentralized clients while preserving data privacy. However, its open-participation nature exposes it to data-poisoning attacks, in which malicious actors submit corrupted model updates to degrade the global model. Existing defenses are often reactive, relying on statistical aggregation rules that can be computationally expensive and that typically assume an honest majority. This paper introduces a proactive, economic defense:…

Distributed Resilient State Estimation and Control with Strategically Implemented Security Measures
Takumi Shinohara, Karl H. Johansson, Henrik Sandberg
https://arxiv.org/abs/2507.12052

Distributed Resilient State Estimation and Control with Strategically Implemented Security Measures
This paper addresses the problem of distributed resilient state estimation and control for linear time-invariant systems in the presence of malicious false data injection sensor attacks and bounded noise. We consider a system operator (defender) capable of deploying cybersecurity measures to counteract the sensor compromises. Although such measures enhance resilience against adversarial attacks, they may incur substantial costs; hence, it is crucial to select countermeasures to balance resilien…

Resilient-native and Intelligent NextG Systems
Mehdi Bennis
https://arxiv.org/abs/2506.12795 https://arxiv.org/pdf/2506.12795

Resilient-native and Intelligent NextG Systems
Just like power, water and transportation systems, wireless networks are a crucial societal infrastructure. As natural and human-induced disruptions continue to grow, wireless networks must be resilient to unforeseen events, able to withstand and recover from unexpected adverse conditions, shocks, unmodeled disturbances and cascading failures. Despite its critical importance, resilience remains an elusive concept, with its mathematical foundations still underdeveloped. Unlike robustness and rel…

Leakage-Resilient Extractors against Number-on-Forehead Protocols
Eshan Chattopadhyay, Jesse Goodman
https://arxiv.org/abs/2506.12595 https://

Leakage-Resilient Extractors against Number-on-Forehead Protocols
Given a sequence of $N$ independent sources $\mathbf{X}_1,\mathbf{X}_2,\dots,\mathbf{X}_N\sim\{0,1\}^n$, how many of them must be good (i.e., contain some min-entropy) in order to extract a uniformly random string? This question was first raised by Chattopadhyay, Goodman, Goyal and Li (STOC '20), motivated by applications in cryptography, distributed computing, and the unreliable nature of real-world sources of randomness. In their paper, they showed how to construct explicit low-error extracto…

Ultra-Resilient Superimposed Codes: Near-Optimal Construction and Applications
Gianluca De Marco, Dariusz R. Kowalski
https://arxiv.org/abs/2506.13489 http…

Ultra-Resilient Superimposed Codes: Near-Optimal Construction and Applications
A superimposed code is a collection of binary vectors (codewords) with the property that no vector is contained in the Boolean sum of any $k$ others, enabling unique identification of codewords within any group of $k$. Superimposed codes are foundational combinatorial tools with applications in areas ranging from distributed computing and data retrieval to fault-tolerant communication. However, classical superimposed codes rely on strict alignment assumptions, limiting their effectiveness in as…

A Machine Learning Framework for Climate-Resilient Insurance and Real Estate Decisions
Lang Qin, Yuejin Xie, Daili Hua, Xuhui Meng
https://arxiv.org/abs/2506.14638

A Machine Learning Framework for Climate-Resilient Insurance and Real Estate Decisions
Extreme weather events increasingly threaten the insurance and real estate industries, creating conflicts between profitability and homeowner burdens. To address this, we propose the SSC-Insurance Model, which integrates SMOTE, SVM, and C-D-C algorithms to evaluate weather impacts on policies and investments. Our model achieves 88.3% accuracy in Zhejiang and 79.6% in Ireland, identifying a critical threshold (43% weather increase) for insurance viability. Additionally, we develop the TOA-Preser…

QSpark: Towards Reliable Qiskit Code Generation
Kiana Kheiri, Aamna Aamir, Andriy Miranskyy, Chen Ding
https://arxiv.org/abs/2507.12642 https://

QSpark: Towards Reliable Qiskit Code Generation
Quantum circuits must be error-resilient, yet LLMs like Granite-20B-Code and StarCoder often output flawed Qiskit code. We fine-tuned a 32 B model with two RL methods, Group Relative Policy Optimization (GRPO) and Odds-Ratio Preference Optimization (ORPO), using a richly annotated synthetic dataset. On the Qiskit HumanEval benchmark, ORPO reaches 56.29\% Pass@1 ($\approx+10$ pp over Granite-8B-QK) and GRPO hits 49\%, both beating all general-purpose baselines; on the original HumanEval they sco…

My dad knew about bugs.
He taught us to be curious about the mundane, to be adaptable and resilient, to be confident in the might of the small.
On this Father's Day, I think I may have located the first of his academic articles from 1962. 🤍
https://www.sciencedirect.com…

Resilient Time-Sensitive Networking for Industrial IoT: Configuration and Fault-Tolerance Evaluation
Mohamed Seliem, Dirk Pesch, Utz Roedig, Cormac Sreenan
https://arxiv.org/abs/2507.11250

Resilient Time-Sensitive Networking for Industrial IoT: Configuration and Fault-Tolerance Evaluation
Time-Sensitive Networking (TSN) is increasingly adopted in industrial systems to meet strict latency, jitter, and reliability requirements. However, evaluating TSN's fault tolerance under realistic failure conditions remains challenging. This paper presents IN2C, a modular OMNeT++/INET-based simulation framework that models two synchronized production cells connected to centralized infrastructure. IN2C integrates core TSN features, including time synchronization, traffic shaping, per-stream fil…

Digitaltag 2025: resilient, demokratisch, Teilhabe-orientiert
Der Digitaltag wirbt für eine digital-affine und resiliente Gesellschaft. Die destruktiven Seiten des Internets sollen bekämpft, die guten gefördert werden.

Towards Robust Sensor-Fusion Ground SLAM: A Comprehensive Benchmark and A Resilient Framework
Deteng Zhang, Junjie Zhang, Yan Sun, Tao Li, Hao Yin, Hongzhao Xie, Jie Yin
https://arxiv.org/abs/2507.08364

Towards Robust Sensor-Fusion Ground SLAM: A Comprehensive Benchmark and A Resilient Framework
Considerable advancements have been achieved in SLAM methods tailored for structured environments, yet their robustness under challenging corner cases remains a critical limitation. Although multi-sensor fusion approaches integrating diverse sensors have shown promising performance improvements, the research community faces two key barriers: On one hand, the lack of standardized and configurable benchmarks that systematically evaluate SLAM algorithms under diverse degradation scenarios hinders …

The Building Resilient Kids Podcast
Great Australian Pods Podcast Directory: #GreatAusPods

Obfuscation-Resilient Binary Code Similarity Analysis using Dominance Enhanced Semantic Graph
Yufeng Wang, Yuhong Feng, Yixuan Cao, Haoran Li, Haiyue Feng, Yifeng Wang
https://arxiv.org/abs/2506.06161

Obfuscation-Resilient Binary Code Similarity Analysis using Dominance Enhanced Semantic Graph
Binary code similarity analysis (BCSA) serves as a core technique for binary analysis tasks such as vulnerability detection. While current graph-based BCSA approaches capture substantial semantics and show strong performance, their performance suffers under code obfuscation due to the unstable control flow. To address this issue, we develop ORCAS, an Obfuscation-Resilient BCSA model based on Dominance Enhanced Semantic Graph (DESG). The DESG is an original binary code representation, capturing …

FPGA-Based Multiplier with a New Approximate Full Adder for Error-Resilient Applications
Ali Ranjbar, Elham Esmaeili, Roghayeh Rafieisangari, Nabiollah Shiri
https://arxiv.org/abs/2506.09596

FPGA-Based Multiplier with a New Approximate Full Adder for Error-Resilient Applications
Electronic devices primarily aim to offer low power consumption, high speed, and a compact area. The performance of very large-scale integration (VLSI) devices is influenced by arithmetic operations, where multiplication is a crucial operation. Therefore, a high-speed multiplier is essential for developing any signal-processing module. Numerous multipliers have been reviewed in existing literature, and their speed is largely determined by how partial products (PPs) are accumulated. To enhance t…

Multi-Level Damage-Aware Graph Learning for Resilient UAV Swarm Networks
Huan Lin, Chenguang Zhu, Lianghui Ding, Feng Yang
https://arxiv.org/abs/2506.09703

Multi-Level Damage-Aware Graph Learning for Resilient UAV Swarm Networks
Unmanned aerial vehicle (UAV) swarm networks leverage resilient algorithms to address communication network split issues and restore connectivity. However, existing graph learning-based resilient algorithms face over-aggregation and non-convergence problems caused by uneven and sparse topology under massive damage scenarios. To alleviate these problems, we propose a novel Multi-Level Damage-Aware Graph Learning (ML-DAGL) algorithm, which generates recovery trajectories by mining information fro…

Fully-Distributed Construction of Byzantine-Resilient Dynamic Peer-to-Peer Networks
Aayush Gupta, Gopal Pandurangan
https://arxiv.org/abs/2506.04368 https:…

Fully-Distributed Construction of Byzantine-Resilient Dynamic Peer-to-Peer Networks
We address a fundamental problem in Peer-to-Peer (P2P) networks, namely, constructing and maintaining dynamic P2P overlay network topologies with essential properties such as connectivity, low diameter, and high expansion, that are resilient to continuous high churn and the presence of a large number of malicious (Byzantine) nodes. Our main goal is to construct and maintain a sparse (bounded degree) expander topology despite high churn and a large number of Byzantine nodes. Such an expander top…

Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity
Haoxiang Ye, Tao Sun, Qing Ling
https://arxiv.org/abs/2506.09438

Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity
Decentralized learning, which facilitates joint model training across geographically scattered agents, has gained significant attention in the field of signal and information processing in recent years. While the optimization errors of decentralized learning algorithms have been extensively studied, their generalization errors remain relatively under-explored. As the generalization errors reflect the scalability of trained models on unseen data and are crucial in determining the performance of …

Resilient cluster Mott states in layered Nb$_3$Cl$_8$ against pressure-induced symmetry breaking
Hongbin Qu, Xiaoqun Wang, Hai-Qing Li, ang Gang Li
https://arxiv.org/abs/2507.07624

Resilient cluster Mott states in layered Nb$_3$Cl$_8$ against pressure-induced symmetry breaking
In this work, by combining density-functional theory (DFT) with dynamical mean-field calculations (DMFT), we compare the crystal and electronic structures of the prototype cluster Mott insulator Nb$_{3}$Cl$_8$ at ambient and high-pressure. We explain the finite but significantly reduced charge gap experimentally observed at $P=9.7$ GPa. We reveal a local symmetry breaking of the Nb$_{3}$ trimer under pressure, reducing its symmetry from $C_{3v}$ to $C_{s}$. This leads to a strong bandwidth enha…

'TACO' Is the Secret to Trump's Resilience (Ross Douthat/New York Times)
https://www.nytimes.com/2025/05/31/opinion/trump-taco-resilient.html
http://www.memeorandum.com/250531/p40#a250531p40

Tell your Senators to vote NO on massive cuts to public media:
https://www.marketplace.org/action
This is a blatant attack on the only part of the media ecosystem that is resilient against political influence and control. That makes it the most valuable part. That's why the Rep…

#ProtectMyPublicMedia

Local Ambiguity Shaping for Doppler-Resilient Sequences Under Spectral and PAPR Constraints
Shi He, Lingsheng Meng, Yao Ge, Yong Liang Guan, David Gonz\'alez G., Zilong Liu
https://arxiv.org/abs/2506.01637

Local Ambiguity Shaping for Doppler-Resilient Sequences Under Spectral and PAPR Constraints
This paper focuses on designing Doppler-resilient sequences with low local Ambiguity Function (AF) sidelobes, subject to certain spectral and Peak-to-Average Power Ratio (PAPR) constraints. To achieve this, we propose two distinctoptimization algorithms: (i) an Alternating Minimization (AM) algorithm for superior Weighted Peak Sidelobe Level (WPSL) minimization, and (ii) a low-complexity Augmented Lagrangian-assisted Majorization Minimization (ALaMM) algorithm with effective WPSL suppression. T…

Fiona Hill’s argument is that
in a time of profound uncertainty,
Britain needs greater internal cohesion if it is to protect itself.
“We can’t rely exclusively on anyone any more,” she said,
arguing that Britain needed to have “a different mindset” based as much on traditional defence as on social resilience.
Some of that, Hill said, was about a greater recognition of the level of external threat and initiatives for greater integration,
by teaching first a…

Anomaly Detection for Sensing Security
Stefan Roth, Aydin Sezgin
https://arxiv.org/abs/2506.10718 https://arxiv.org/pdf/2506.10718

Anomaly Detection for Sensing Security
Various approaches in the field of physical layer security involve anomaly detection, such as physical layer authentication, sensing attacks, and anti-tampering solutions. Depending on the context in which these approaches are applied, anomaly detection needs to be computationally lightweight, resilient to changes in temperature and environment, and robust against phase noise. We adapt moving average filters, autoregression filters and Kalman filters to provide predictions of feature vectors th…

Extended Version of "Distributed Adaptive Resilient Consensus Control for Uncertain Nonlinear Multiagent Systems Against Deception Attacks"
Mengze Yu, Wei Wang, Jiaqi Yan
https://arxiv.org/abs/2506.07374

Extended Version of "Distributed Adaptive Resilient Consensus Control for Uncertain Nonlinear Multiagent Systems Against Deception Attacks"
This paper studies distributed resilient consensus problem for a class of uncertain nonlinear multiagent systems susceptible to deception attacks. The attacks invade both sensor and actuator channels of each agent. A specific class of Nussbaum functions is adopted to manage the attack-incurred multiple unknown control directions. Additionally, a general form of these Nussbaum functions is provided, which helps to ease the degeneration of output performance caused by Nussbaum gains. Then, by int…

Another of the supposed "defence experts" (aka #warmongers) advising Labour. The article identifies 2 others, "Lord Robertson, a former Nato secretary general, and the retired general Sir Richard Barrons".
Any experts on #peace,

Atmospheric Turbulence-Resilient Long-Range Fourier Ptychography
Junhao Zhang, Weilong Wei, Kaiyuan Yang, Qiang Zhou, Haotong Ma, Ge Ren, Zongliang Xie
https://arxiv.org/abs/2507.03943

Atmospheric Turbulence-Resilient Long-Range Fourier Ptychography
While Fourier ptychography (FP) offers super-resolution for macroscopic imaging, its real-world application is severely hampered by atmospheric turbulence, a challenge largely unaddressed in existing macroscopic FP research operating under idealized conditions. This work establishes, to our knowledge, the first comprehensive computational framework specifically designed for turbulence mitigation in long-range FP, termed Turbulence-Mitigated FP (TMFP). Rather than correcting pupil errors, an ima…

AI and Remote Sensing for Resilient and Sustainable Built Environments: A Review of Current Methods, Open Data and Future Directions
Ubada El Joulani, Tatiana Kalganova, Stergios-Aristoteles Mitoulis, Sotirios Argyroudis
https://arxiv.org/abs/2507.01547

AI and Remote Sensing for Resilient and Sustainable Built Environments: A Review of Current Methods, Open Data and Future Directions
Critical infrastructure, such as transport networks, underpins economic growth by enabling mobility and trade. However, ageing assets, climate change impacts (e.g., extreme weather, rising sea levels), and hybrid threats ranging from natural disasters to cyber attacks and conflicts pose growing risks to their resilience and functionality. This review paper explores how emerging digital technologies, specifically Artificial Intelligence (AI), can enhance damage assessment and monitoring of trans…

Resilient Pattern Mining
Pengxin Bian, Panagiotis Charalampopoulos, Lorraine A. K. Ayad, Manal Mohamed, Solon P. Pissis, Grigorios Loukides
https://arxiv.org/abs/2506.04935

Resilient Pattern Mining
Frequent pattern mining is a flagship problem in data mining. In its most basic form, it asks for the set of substrings of a given string $S$ of length $n$ that occur at least $τ$ times in $S$, for some integer $τ\in[1,n]$. We introduce a resilient version of this classic problem, which we term the $(τ, k)$-Resilient Pattern Mining (RPM) problem. Given a string $S$ of length $n$ and two integers $τ, k\in[1,n]$, RPM asks for the set of substrings of $S$ that occur at least $τ$ times in $S$,…

SCoRE: Streamlined Corpus-based Relation Extraction using Multi-Label Contrastive Learning and Bayesian kNN
Luca Mariotti, Veronica Guidetti, Federica Mandreoli
https://arxiv.org/abs/2507.06895

SCoRE: Streamlined Corpus-based Relation Extraction using Multi-Label Contrastive Learning and Bayesian kNN
The growing demand for efficient knowledge graph (KG) enrichment leveraging external corpora has intensified interest in relation extraction (RE), particularly under low-supervision settings. To address the need for adaptable and noise-resilient RE solutions that integrate seamlessly with pre-trained large language models (PLMs), we introduce SCoRE, a modular and cost-effective sentence-level RE system. SCoRE enables easy PLM switching, requires no finetuning, and adapts smoothly to diverse cor…

Training Strategies for Modality Dropout Resilient Multi-Modal Target Speaker Extraction
Srikanth Korse, Mohamed Elminshawi, Emanuel A. P. Habets, Srikanth Raj Chetupalli
https://arxiv.org/abs/2507.06566

Training Strategies for Modality Dropout Resilient Multi-Modal Target Speaker Extraction
The primary goal of multi-modal TSE (MTSE) is to extract a target speaker from a speech mixture using complementary information from different modalities, such as audio enrolment and visual feeds corresponding to the target speaker. MTSE systems are expected to perform well even when one of the modalities is unavailable. In practice, the systems often suffer from modality dominance, where one of the modalities outweighs the others, thereby limiting robustness. Our study investigates training st…

General Perturbation Resilient Dynamic String-Averaging for Inconsistent Problems with Superiorization
Kay Barshad, Yair Censor
https://arxiv.org/abs/2507.00717

General Perturbation Resilient Dynamic String-Averaging for Inconsistent Problems with Superiorization
In this paper we introduce a General Dynamic String-Averaging (GDSA) iterative scheme and investigate its convergence properties in the inconsistent case, that is, when the input operators don't have a common fixed point. The Dynamic String-Averaging Projection (DSAP) algorithm itself was introduced in an 2013 paper, where its strong convergence and bounded perturbation resilience were studied in the consistent case (that is, when the sets under consideration had a nonempty intersection). Resul…

Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management
Hussain Ahmad, Christoph Treude, Markus Wagner, Claudia Szabo
https://arxiv.org/abs/2506.05693

Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management
Horizontal Pod Auto-scalers (HPAs) are crucial for managing resource allocation in microservice architectures to handle fluctuating workloads. However, traditional HPAs fail to address resource disruptions caused by faults, cyberattacks, maintenance, and other operational challenges. These disruptions result in resource wastage, service unavailability, and HPA performance degradation. To address these challenges, we extend our prior work on Smart HPA and propose SecureSmart HPA, which offers re…

(YouTube) From blindness to cyber brilliance, from "seeing with sound" to securing cyberspace, the journey of Pranav Lal, congenitally blind user of The vOICe vision BCI in India https://www.youtube.com/watch?v=aWlVKDpZ6hU

Floridas #Korallenriffe haben in 40 Jahren 90 % ihrer gesunden Bestände verloren.
Ein neues Projekt pflanzt über 1000 gezüchtete #Elchgeweihkorallen aus, um den Lebensraum zu stabilisieren. Die widerstandsfähige Art wurde genetisch vielfältig vermehrt und könnte künftigen

Intelligent System of Emergent Knowledge: A Coordination Fabric for Billions of Minds
Moshi Wei, Sparks Li
https://arxiv.org/abs/2506.09335 https://…

Intelligent System of Emergent Knowledge: A Coordination Fabric for Billions of Minds
The Intelligent System of Emergent Knowledge (ISEK) establishes a decentralized network where human and artificial intelligence agents collaborate as peers, forming a self-organizing cognitive ecosystem. Built on Web3 infrastructure, ISEK combines three fundamental principles: (1) a decentralized multi-agent architecture resistant to censorship, (2) symbiotic AI-human collaboration with equal participation rights, and (3) resilient self-adaptation through distributed consensus mechanisms. The…

As I look at people around me, rarely I see anyone with such a strong symptoms of pollen #allergy as I have. I suppose it's unlikely that all people with allergies manage to keep to their basements, so I'm wondering: is it that my allergy is unusually strong (or resilient to medicine), or are others taking more medicine than I do.
Today I've taken a third pill already (3.5 times the base dosage in total), and once again I'm starting to have a runny nose. And that's after 2 hours since last pill, spent sitting in trains. If the allergy doesn't kill me, the medicine will…

The sheer confidence in her false answer defines insanity. It's unbelievable how resilient the US separation of powers is ->
Kristi Noem Falsely Defines Habeas Corpus as Trump’s Right to Deport People | The New York Times
https://www.youtube.com/shorts/aNf3Yb5N4J4

Microservices and Real-Time Processing in Retail IT: A Review of Open-Source Toolchains and Deployment Strategies
Aaditaa Vashisht (Department of Information Science,Engineering, RV College of Engineering, India), Rekha B S (Department of Information Science,Engineering, RV College of Engineering, India)
https://arxiv.org/abs/25…

Microservices and Real-Time Processing in Retail IT: A Review of Open-Source Toolchains and Deployment Strategies
With the rapid pace of digital transformation, the retail industry is increasingly depending on real-time, scalable, and resilient systems to manage financial transactions, analyze customer behavior, and streamline order processing. This literature review explores how modern event-driven and microservices-based architectures, particularly those leveraging Apache Kafka, Spring Boot, MongoDB, and Kubernetes are transforming retail and financial systems. By systematically reviewing academic public…

HaLert: A Resilient Smart City Architecture for Post-Disaster Based on Wi-Fi HaLow Mesh and SDN
Ana Rita Ortigoso, Gabriel Vieira, Daniel Fuentes, Lu\'is Fraz\~ao, Nuno Costa, Ant\'onio Pereira
https://arxiv.org/abs/2507.07841

HaLert: A Resilient Smart City Architecture for Post-Disaster Based on Wi-Fi HaLow Mesh and SDN
Events such as catastrophes and disasters are, in most cases, unpredictable. Consequently, reusing existing infrastructures to develop alternative communication strategies after disasters is essential to minimise the impact of these events on the population's ability to communicate and promptly receive alerts from authorities. In this context, the emergence of smart cities, characterised by dense and geographically distributed IoT networks, presents significant potential for such reuse. This wo…

This https://arxiv.org/abs/2503.11688 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNE_…

Towards Resilient and Sustainable Global Industrial Systems: An Evolutionary-Based Approach
This paper presents a new complex optimization problem in the field of automatic design of advanced industrial systems and proposes a hybrid optimization approach to solve the problem. The problem is multi-objective as it aims at finding solutions that minimize CO2 emissions, transportation time, and costs. The optimization approach combines an evolutionary algorithm and classical mathematical programming to design resilient and sustainable global manufacturing networks. Further, it makes use o…

Adaptive Variation-Resilient Random Number Generator for Embedded Encryption
Furqan Zahoor, Ibrahim A. Albulushi, Saleh Bunaiyan, Anupam Chattopadhyay, Hesham ElSawy, Feras Al-Dirini
https://arxiv.org/abs/2507.05523

Adaptive Variation-Resilient Random Number Generator for Embedded Encryption
With a growing interest in securing user data within the internet-of-things (IoT), embedded encryption has become of paramount importance, requiring light-weight high-quality Random Number Generators (RNGs). Emerging stochastic device technologies produce random numbers from stochastic physical processes at high quality, however, their generated random number streams are adversely affected by process and supply voltage variations, which can lead to bias in the generated streams. In this work, w…

“What we ultimately want, and what we believe we need, is a commons that is strong, resilient, growing, useful (to machines and to humans)—all the good things, frankly. But as our open infrastructures mature they become increasingly taken for granted, and the feeling that “this is for all of us” is replaced with “everyone is entitled to this”. While this sounds the same, it really isn’t. Because with entitlement comes misuse, the social contract breaks, reciprocation evaporates, and ultimately the magic weakens.”
Very glad to see that @… is working to address the deep challenges that have arisen at the intersection of the open movement and corporate AI.
https://creativecommons.org/2025/04/02/reciprocity-in-the-age-of-ai/
h/t @…

DP-RTFL: Differentially Private Resilient Temporal Federated Learning for Trustworthy AI in Regulated Industries
Abhijit Talluri
https://arxiv.org/abs/2505.23813

DP-RTFL: Differentially Private Resilient Temporal Federated Learning for Trustworthy AI in Regulated Industries
Federated Learning (FL) has emerged as a critical paradigm for enabling privacy-preserving machine learning, particularly in regulated sectors such as finance and healthcare. However, standard FL strategies often encounter significant operational challenges related to fault tolerance, system resilience against concurrent client and server failures, and the provision of robust, verifiable privacy guarantees essential for handling sensitive data. These deficiencies can lead to training disruption…

Replaced article(s) found for cs.PF. https://arxiv.org/list/cs.PF/new
[1/1]:
- Denoising Application Performance Models with Noise-Resilient Priors
de Morais, Gei{\ss}, Calotoiu, Corbin, Tarraf, Hoefler, Mohr, Wolf

Resilience through Automated Adaptive Configuration for Distribution and Replication
Scott D. Stoller, Balaji Jayasankar, Yanhong A. Liu
https://arxiv.org/abs/2506.10248

Resilience through Automated Adaptive Configuration for Distribution and Replication
This paper presents a powerful automated framework for making complex systems resilient under failures, by optimized adaptive distribution and replication of interdependent software components across heterogeneous hardware components with widely varying capabilities. A configuration specifies how software is distributed and replicated: which software components to run on each computer, which software components to replicate, which replication protocols to use, etc. We present an algorithm that,…

Corner Topology Makes Woven Baskets into Stiff, yet Resilient Metamaterials
Guowei Wayne Tu, Evgueni T. Filipov
https://arxiv.org/abs/2506.18197 https://…

Corner Topology Makes Woven Baskets into Stiff, yet Resilient Metamaterials
Basket weaving is a traditional craft used to create practical three-dimensional (3D) structures. While the geometry and aesthetics of baskets have received considerable attention, the underlying mechanics and modern engineering potential remain underexplored. This work shows that 3D woven structures offer similar stiffness yet substantially higher resilience than their non-woven continuous counterparts. We explore corner topologies that serve as building blocks to convert 2D woven sheets into …

Evolution of tripartite entanglement in three-qubit Quantum Gravity-Induced Entanglement of Masses (QGEM) with quantum decoherence
Pablo Guillermo Carmona Rufo, Anupam Mazumdar, Carlos Sab\'in
https://arxiv.org/abs/2507.01007

Evolution of tripartite entanglement in three-qubit Quantum Gravity-Induced Entanglement of Masses (QGEM) with quantum decoherence
The recently introduced quantum gravity-induced entanglement of masses (QGEM) protocol aims to test the quantum nature of gravity by witnessing the entanglement produced by the virtual exchange of a graviton between two spatially superposed masses. Shortly after the original proposal, further improvements upon the experiment were suggested, including the addition of a third mass, showing that three-qubit setups can be more resilient to higher rates of decoherence caused by the interaction of th…

Nonlinear Power Amplifier-Resilient Cell-Free Massive MIMO: A Joint Optimization Approach
Wei Jiang, Hans D. Schotten
https://arxiv.org/abs/2506.22094 http…

Nonlinear Power Amplifier-Resilient Cell-Free Massive MIMO: A Joint Optimization Approach
This letter analyzes the effects of power amplifiers (PAs) on the downlink of cell-free massive MIMO systems. We model signal transmission incorporating nonlinear PA distortion and derive a unified spectral efficiency (SE) expression applicable to arbitrary precoding schemes. To combat PA-induced performance degradation, a joint optimization approach for user association and max-min power control is proposed. Furthermore, a low-complexity alternative is developed to approximate the joint optimi…

Hierarchical Adversarially-Resilient Multi-Agent Reinforcement Learning for Cyber-Physical Systems Security
Saad Alqithami
https://arxiv.org/abs/2506.22445

Hierarchical Adversarially-Resilient Multi-Agent Reinforcement Learning for Cyber-Physical Systems Security
Cyber-Physical Systems play a critical role in the infrastructure of various sectors, including manufacturing, energy distribution, and autonomous transportation systems. However, their increasing connectivity renders them highly vulnerable to sophisticated cyber threats, such as adaptive and zero-day attacks, against which traditional security methods like rule-based intrusion detection and single-agent reinforcement learning prove insufficient. To overcome these challenges, this paper introdu…

Confidence Boosts Trust-Based Resilience in Cooperative Multi-Robot Systems
Luca Ballotta, \'Aron V\'ek\'assy, Stephanie Gil, Michal Yemini
https://arxiv.org/abs/2506.08807

Confidence Boosts Trust-Based Resilience in Cooperative Multi-Robot Systems
Wireless communication-based multi-robot systems open the door to cyberattacks that can disrupt safety and performance of collaborative robots. The physical channel supporting inter-robot communication offers an attractive opportunity to decouple the detection of malicious robots from task-relevant data exchange between legitimate robots. Yet, trustworthiness indications coming from physical channels are uncertain and must be handled with this in mind. In this paper, we propose a resilient prot…

Do Generative AI Tools Ensure Green Code? An Investigative Study
Samarth Sikand, Rohit Mehra, Vibhu Saujanya Sharma, Vikrant Kaulgud, Sanjay Podder, Adam P. Burden
https://arxiv.org/abs/2506.08790

Do Generative AI Tools Ensure Green Code? An Investigative Study
Software sustainability is emerging as a primary concern, aiming to optimize resource utilization, minimize environmental impact, and promote a greener, more resilient digital ecosystem. The sustainability or "greenness" of software is typically determined by the adoption of sustainable coding practices. With a maturing ecosystem around generative AI, many software developers now rely on these tools to generate code using natural language prompts. Despite their potential advantages, there is a …

FedP3E: Privacy-Preserving Prototype Exchange for Non-IID IoT Malware Detection in Cross-Silo Federated Learning
Rami Darwish, Mahmoud Abdelsalam, Sajad Khorsandroo, Kaushik Roy
https://arxiv.org/abs/2507.07258

FedP3E: Privacy-Preserving Prototype Exchange for Non-IID IoT Malware Detection in Cross-Silo Federated Learning
As IoT ecosystems continue to expand across critical sectors, they have become prominent targets for increasingly sophisticated and large-scale malware attacks. The evolving threat landscape, combined with the sensitive nature of IoT-generated data, demands detection frameworks that are both privacy-preserving and resilient to data heterogeneity. Federated Learning (FL) offers a promising solution by enabling decentralized model training without exposing raw data. However, standard FL algorithm…

SR-NCL: an Area-/Energy-Efficient Resilient NCL Architecture Based on Selective Redundancy
Hasnain A. Ziad, Alexander C. Bodoh, Ashiq A. Sakib
https://arxiv.org/abs/2506.15634

SR-NCL: an Area-/Energy-Efficient Resilient NCL Architecture Based on Selective Redundancy
Duplication-based redundancy schemes have proven to be effective in designing fully-resilient Quasi-delay Insensitive (QDI) asynchronous circuits. The complete resiliency, however, is accompanied by significant energy, latency, and area overhead. This paper presents a novel error-tolerant Null Convention Logic (NCL) architecture based on selective redundancy. Results demonstrate the efficacy of the proposed method in terms of area and energy utilization as compared to existing duplication-based…

This weekend I listened to the 'How to Age Up' podcast on climate change. A lot of good observations for how parents can help their children process the daily news cycle and manage their anxiety about the future.
Turns out one effective strategy is one I keep hearing from so many different sources - you build community. Building community makes communities more resilient. Building community makes you feel less alone - so you can help do the work to combat climate change/racism/…

Floquet-engineered decoherence-resilient protocols for wideband sensing beyond the linear standard quantum limit
Hao Wu, Clayton Z. C. Ho, Grant D. Mitts, Joshua A. Rabinowitz, Eric R. Hudson
https://arxiv.org/abs/2506.03010

This https://arxiv.org/abs/2506.01348 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Distributionally Robust Learning in Survival Analysis
We introduce an innovative approach that incorporates a Distributionally Robust Learning (DRL) approach into Cox regression to enhance the robustness and accuracy of survival predictions. By formulating a DRL framework with a Wasserstein distance-based ambiguity set, we develop a variant Cox model that is less sensitive to assumptions about the underlying data distribution and more resilient to model misspecification and data perturbations. By leveraging Wasserstein duality, we reformulate the …

The Effect of Network Topology on the Equilibria of Influence-Opinion Games
Yigit Ege Bayiz, Arash Amini, Radu Marculescu, Ufuk Topcu
https://arxiv.org/abs/2506.22293

The Effect of Network Topology on the Equilibria of Influence-Opinion Games
Online social networks exert a powerful influence on public opinion. Adversaries weaponize these networks to manipulate discourse, underscoring the need for more resilient social networks. To this end, we investigate the impact of network connectivity on Stackelberg equilibria in a two-player game to shape public opinion. We model opinion evolution as a repeated competitive influence-propagation process. Players iteratively inject \textit{messages} that diffuse until reaching a steady state, mo…

This https://arxiv.org/abs/2503.11688 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNE_…

Towards Resilient and Sustainable Global Industrial Systems: An Evolutionary-Based Approach
This paper presents a new complex optimization problem in the field of automatic design of advanced industrial systems and proposes a hybrid optimization approach to solve the problem. The problem is multi-objective as it aims at finding solutions that minimize CO2 emissions, transportation time, and costs. The optimization approach combines an evolutionary algorithm and classical mathematical programming to design resilient and sustainable global manufacturing networks. Further, it makes use o…

Whether you're directly affected or observing from the outside – this is a moment to reflect:
🔹 How resilient is your skillset in an uncertain economy?
🔹 Are you building for long-term adaptability or short-term optimization?
🔹 Are you open to considering a potentially lucrative side hustel as a means to weather economic storms?
If your answer to that last question is ‘Yes’ or ‘Maybe’, message me and we can chat further.

Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources
Roopkatha Banerjee, Prince Modi, Jinal Vyas, Chunduru Sri Abhijit, Tejus Chandrashekar, Harsha Varun Marisetty, Manik Gupta, Yogesh Simmhan
https://arxiv.org/abs/2507.02295

Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources
With the recent improvements in mobile and edge computing and rising concerns of data privacy, Federated Learning(FL) has rapidly gained popularity as a privacy-preserving, distributed machine learning methodology. Several FL frameworks have been built for testing novel FL strategies. However, most focus on validating the learning aspects of FL through pseudo-distributed simulation but not for deploying on real edge hardware in a distributed manner to meaningfully evaluate the federated aspects…

Resilient-Native and Intelligent Next-Generation Wireless Systems: Key Enablers, Foundations, and Applications
Mehdi Bennis, Sumudu Samarakoon, Tamara Alshammari, Chathuranga Weeraddana, Zhoujun Tian, Chaouki Ben Issaid
https://arxiv.org/abs/2506.22991

Resilient-Native and Intelligent Next-Generation Wireless Systems: Key Enablers, Foundations, and Applications
Just like power, water, and transportation systems, wireless networks are a crucial societal infrastructure. As natural and human-induced disruptions continue to grow, wireless networks must be resilient. This requires them to withstand and recover from unexpected adverse conditions, shocks, unmodeled disturbances and cascading failures. Unlike robustness and reliability, resilience is based on the understanding that disruptions will inevitably happen. Resilience, as elasticity, focuses on the …

Towards a Knowledge Base of Common Sustainability Weaknesses in Green Software Development
Priyavanshi Pathania, Rohit Mehra, Vibhu Saujanya Sharma, Vikrant Kaulgud, Sanjay Podder, Adam P. Burden
https://arxiv.org/abs/2506.08812

Towards a Knowledge Base of Common Sustainability Weaknesses in Green Software Development
With the climate crisis looming, engineering sustainable software systems become crucial to optimize resource utilization, minimize environmental impact, and foster a greener, more resilient digital ecosystem. For developers, getting access to automated tools that analyze code and suggest sustainabilityrelated optimizations becomes extremely important from a learning and implementation perspective. However, there is currently a dearth of such tools due to the lack of standardized knowledge, whi…

When Every Symbol Counts: Resilient Wireless Systems Under Finite Blocklength Constraints
Kevin Weinberger, Aydin Sezgin
https://arxiv.org/abs/2506.21664 h…

When Every Symbol Counts: Resilient Wireless Systems Under Finite Blocklength Constraints
As 6G evolves, wireless networks become essential for critical operations and enable innovative applications that demand seamless adaptation to dynamic environments and disruptions. Because these vital services require uninterrupted operation, their resilience to unforeseen disruptions is essential. However, implementing resilience necessitates rapid recovery procedures, which operate in the finite blocklength (FBL) regime, where short packets and added error-correction overhead can severely de…

Reconfigurable non-Abelian geometric phase in hybrid integrated photonics
Youlve Chen, Jiaxin Zhang, Jinlong Xiang, An He, Junying Li, Yikai Su, Xuhan Guo
https://arxiv.org/abs/2507.03955

Reconfigurable non-Abelian geometric phase in hybrid integrated photonics
The non-Abelian geometric phase possesses the capability of enabling robust and fault-resilient unitary transformations, making it a cornerstone of holonomic quantum computation. This "all-geometric" approach has successfully advanced the manipulation of electrons in condensed matter physics and has sparked growing interest in its implementation within photonics, an area that has traditionally relied on sensitive dynamic phases. However, a major limitation of the topologically protected and inh…

A novel model class for bowtie biological networks with universal classification properties
Charles A. Johnson (Daniel), Keon Ho (Daniel), Park, Enoch Yeung
https://arxiv.org/abs/2505.13703

A novel model class for bowtie biological networks with universal classification properties
Cell sensory transcription networks are the intracellular computation structure that regulates and drives cellular activity. Activity in these networks determines the the cell's ability to adapt to changes in its environment. Resilient cells successfully identify (classify) and appropriately respond to environmental shifts. We present a model for identification and response to environmental changes in resilient bacteria. This model combines two known motifs in transcription networks: dense over…

Inkspot: A stress-resilient, anthocyanin rich, dwarf tomato variant for off-world cultivation
Sarah Lang, A'nya Buckner, Solomon Jones, Gabriel Erwin, Sally Lee, Rafael Loureiro
https://arxiv.org/abs/2505.16890

"Africa has the highest rate of forest loss in the world—what the G20 can do about it"
#Africa #Trees #Forests #Environment

Africa has the highest rate of forest loss in the world—what the G20 can do about it
Africa needs its forests for sustainable development, poverty reduction, food security, and to make the continent more resilient to climate change. They take up 23% of the continent. At 674 million hectares in extent, these forests occupy an area the same size as the Amazon rainforest.

Error-resilient Reversal of Quantum Chaotic Dynamics Enabled by Scramblons
Yu-Chen Li, Tian-Gang Zhou, Shengyu Zhang, Ze Wu, Liqiang Zhao, Haochuan Yin, Xiaoxue An, Hui Zhai, Pengfei Zhang, Xinhua Peng
https://arxiv.org/abs/2506.19915

Error-resilient Reversal of Quantum Chaotic Dynamics Enabled by Scramblons
The emergence of the arrow of time in quantum many-body systems stems from the inherent tendency of Hamiltonian evolution to scramble quantum information and increase entanglement. While, in principle, one might counteract this temporal directionality by engineering a perfectly inverted Hamiltonian to reverse entanglement growth, such a scenario is fundamentally unstable because even minor imperfections in the backward evolution can be exponentially amplified, a hallmark of quantum many-body ch…

Robust and Resilient Networks with Integrated Sensing, Communication and Computation
Ming-Chun Lee, Christian Eckrich, Vahid Jamali, Yu-Chih Huang, Arash Asadi, Li-Chun Wang
https://arxiv.org/abs/2506.19518

Robust and Resilient Networks with Integrated Sensing, Communication and Computation
Emerging applications such as networked robotics, intelligent transportation, smart factories, and virtual and augmented reality demand integrated perception and connectivity enabled by wireless communication. This has driven growing interests in integrated sensing, communication, and computation (ISCC) systems, with a primary focus on their efficient co-designs. However, as ISCC systems increasingly support critical applications, they must not only deliver high performance but also demonstrate…

AI-Augmented OTDR Fault Localization Framework for Resilient Rural Fiber Networks in the United States
Sabab Al Farabi (Department of Industrial Engineering, Lamar University, Beaumont, Texas, USA)
https://arxiv.org/abs/2506.03041

AI-Augmented OTDR Fault Localization Framework for Resilient Rural Fiber Networks in the United States
This research presents a novel framework that combines traditional Optical Time-Domain Reflectometer (OTDR) signal analysis with machine learning to localize and classify fiber optic faults in rural broadband infrastructures. The proposed system addresses a critical need in the expansion of middle-mile and last-mile networks, particularly in regions targeted by the U.S. Broadband Equity, Access, and Deployment (BEAD) Program. By enhancing fault diagnosis through a predictive, AI-based model, th…

Aufbau suppressed coupled cluster as a post-linear-response method
Trine Kay Quady, Harrison Tuckman, Eric Neuscamman
https://arxiv.org/abs/2506.16680 http…

Aufbau suppressed coupled cluster as a post-linear-response method
We investigate the ability of Aufbau suppressed coupled cluster theory to act as a post-linear-response correction to widely used linear response methods for electronically excited states. We find that the theory is highly resilient to shortcomings in the underlying linear response method, with final results from less accurate starting points nearly as good as those from the best starting points. This pattern is especially stark in charge transfer states, where the approach converts starting po…

From On-chain to Macro: Assessing the Importance of Data Source Diversity in Cryptocurrency Market Forecasting
Giorgos Demosthenous, Chryssis Georgiou, Eliada Polydorou
https://arxiv.org/abs/2506.21246

From On-chain to Macro: Assessing the Importance of Data Source Diversity in Cryptocurrency Market Forecasting
This study investigates the impact of data source diversity on the performance of cryptocurrency forecasting models by integrating various data categories, including technical indicators, on-chain metrics, sentiment and interest metrics, traditional market indices, and macroeconomic indicators. We introduce the Crypto100 index, representing the top 100 cryptocurrencies by market capitalization, and propose a novel feature reduction algorithm to identify the most impactful and resilient features…

This https://arxiv.org/abs/2404.00306 has been replaced.
link: https://scholar.google.com/scholar?q=a

A blockchain-based intelligent recommender system framework for enhancing supply chain resilience
This research proposed a data-driven supply chain disruption response baseline framework based on intelligent recommender system technology as an initial SCRes reactive solution. To improve the data quality and reliability of the proposed IRS as a stable, secure, and resilient decision support system, blockchain technology is integrated into the baseline architecture. The smart contract is prototyped to demonstrate the information exchange mechanism under a BLC network environment. The BLC-IRS …

JANUS: Resilient and Adaptive Data Transmission for Enabling Timely and Efficient Cross-Facility Scientific Workflows
Vladislav Esaulov, Jieyang Chen, Norbert Podhorszki, Fred Suter, Scott Klasky, Anu G Bourgeois, Lipeng Wan
https://arxiv.org/abs/2506.17084

JANUS: Resilient and Adaptive Data Transmission for Enabling Timely and Efficient Cross-Facility Scientific Workflows
In modern science, the growing complexity of large-scale projects has increased reliance on cross-facility workflows, where institutions share resources and expertise to accelerate discovery. These workflows often involve transferring massive data over wide-area networks. While high-speed networks like ESnet and data transfer services like Globus have improved data mobility, challenges remain. Large data volumes can strain bandwidth, TCP suffers from retransmissions due to packet loss, and trad…

This https://arxiv.org/abs/2505.17226 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation
Federated Learning (FL) enables collaborative machine learning across decentralized data sources without sharing raw data. It offers a promising approach to privacy-preserving AI. However, FL remains vulnerable to adversarial threats from malicious participants, referred to as Byzantine clients, who can send misleading updates to corrupt the global model. Traditional aggregation methods, such as simple averaging, are not robust to such attacks. More resilient approaches, like the Krum algorithm…

Replaced article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[1/1]:
- How Resilient is QUIC to Security and Privacy Attacks?
Jayasree Sengupta, Debasmita Dey, Simone Ferlin-Reiter, Nirnay Ghosh, Vaibhav Bajpai

Minimal Construction of Graphs with Maximum Robustness
Haejoon Lee, Dimitra Panagou
https://arxiv.org/abs/2507.00415 https://arxiv.or…

Minimal Construction of Graphs with Maximum Robustness
The notions of network $r$-robustness and $(r,s)$-robustness have been earlier introduced in the literature to achieve resilient control in the presence of misbehaving agents. However, while higher robustness levels provide networks with higher tolerances against the misbehaving agents, they also require dense communication structures, which are not always desirable for systems with limited capabilities and energy capacities. Therefore, this paper studies the fundamental structures behind $r$-r…

Resilient Communication For Avalanche Response in Infrastructure-Limited Environments
Joshua Goulton, Milena Radenkovic
https://arxiv.org/abs/2506.22148 ht…

Resilient Communication For Avalanche Response in Infrastructure-Limited Environments
Delay Tolerant Networks (DTNs) offer a promising paradigm for maintaining communication in infrastructure limited environments, such as those encountered during natural disasters. This paper investigates the viability of leveraging an existing national transport system - the Swiss rail network - as a data mule backbone for disseminating critical avalanche alerts. Using The Opportunistic Network Environment (ONE) simulator, we model the entire Swiss rail network and conduct a rigorous comparativ…

Development of Hardware-in-Loop Framework for Satellite Communication Self-Healing Networks
Sambrama, Venkata Srirama Rohit Kantheti, Liang C Chu, Erik Blasch, Shih-Chun Lin
https://arxiv.org/abs/2506.01210

Development of Hardware-in-Loop Framework for Satellite Communication Self-Healing Networks
The use of Low Earth Orbit (LEO) satellites in the next generation (Next-G) communication systems has been gaining traction over the last few years due to their potential for providing global connectivity with low latency. Since they are the closest to the earth they come with their own set of disadvantages including high vulnerability to jamming and interference. To address these issues, this paper introduces a resilient, self-healing network designed to optimize signal quality under dynamic i…

Magnetic dilution in the triangular lattice antiferromagnet NaYb$_{1-x}$Lu$_{x}$O$_2$
Steven J. Gomez Alvarado, Brenden R. Ortiz, Soren Bear, Benito A. Gonzalez, Andrea N. Capa Salinas, Adam Berlie, Michael J. Graf, Stephen D. Wilson
https://arxiv.org/abs/2506.22613

Magnetic dilution in the triangular lattice antiferromagnet NaYb$_{1-x}$Lu$_{x}$O$_2$
The delafossite-like compound NaYbO$_2$ hosts a triangular lattice of Yb$^{3+}$ moments and is a promising candidate for realizing a quantum spin liquid state. Here we leverage the substitution of nonmagnetic Lu$^{3+}$ onto the Yb$^{3+}$ sites to track the evolution of the quantum disordered ground state with increasing magnetic disorder in NaYb$_{1-x}$Lu$_x$O$_2$. Low temperature $μ$SR measurements preclude conventional spin freezing and magnetic inhomogeneity, and instead resolve resilient, …

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Not eXactly Byzantine: Efficient and Resilient TEE-Based State Machine Replication
Marc Leinweber, Hannes Hartenstein

This https://arxiv.org/abs/2505.16890 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

"Scientists seek to save Florida’s dying reefs with hardy nursery-grown coral"
#US #USA #America #CoralReef…

Second Order State Hallucinations for Adversarial Attack Mitigation in Formation Control of Multi-Agent Systems
Laksh Patel, Akhilesh Raj
https://arxiv.org/abs/2506.17283

Second Order State Hallucinations for Adversarial Attack Mitigation in Formation Control of Multi-Agent Systems
The increasing deployment of multi-agent systems (MAS) in critical infrastructures such as autonomous transportation, disaster relief, and smart cities demands robust formation control mechanisms resilient to adversarial attacks. Traditional consensus-based controllers, while effective under nominal conditions, are highly vulnerable to data manipulation, sensor spoofing, and communication failures. To address this challenge, we propose Second-Order State Hallucination (SOSH), a novel framework …

Distributed Intelligence in the Computing Continuum with Active Inference
Victor Casamayor Pujol, Boris Sedlak, Tommaso Salvatori, Karl Friston, Schahram Dustdar
https://arxiv.org/abs/2505.24618

Distributed Intelligence in the Computing Continuum with Active Inference
The Computing Continuum (CC) is an emerging Internet-based computing paradigm that spans from local Internet of Things sensors and constrained edge devices to large-scale cloud data centers. Its goal is to orchestrate a vast array of diverse and distributed computing resources to support the next generation of Internet-based applications. However, the distributed, heterogeneous, and dynamic nature of CC platforms demands distributed intelligence for adaptive and resilient service management. Th…

Replaced article(s) found for cs.NI. https://arxiv.org/list/cs.NI/new
[1/1]:
- Resilient-By-Design: A Resiliency Framework for Future Wireless Networks
Nurul Huda Mahmood, Sumudu Samarakoon, Pawani Porambage, Mehdi Bennis, Matti Latva-aho

HybridRAG-based LLM Agents for Low-Carbon Optimization in Low-Altitude Economy Networks
Jinbo Wen, Cheng Su, Jiawen Kang, Jiangtian Nie, Yang Zhang, Jianhang Tang, Dusit Niyato, Chau Yuen
https://arxiv.org/abs/2506.15947

HybridRAG-based LLM Agents for Low-Carbon Optimization in Low-Altitude Economy Networks
Low-Altitude Economy Networks (LAENets) are emerging as a promising paradigm to support various low-altitude services through integrated air-ground infrastructure. To satisfy low-latency and high-computation demands, the integration of Unmanned Aerial Vehicles (UAVs) with Mobile Edge Computing (MEC) systems plays a vital role, which offloads computing tasks from terminal devices to nearby UAVs, enabling flexible and resilient service provisions for ground users. To promote the development of LA…