Tootfinder

VoI-aware Scheduling Schemes for Multi-Agent Formation Control
Federico Chiariotti, Marco Fabris
https://arxiv.org/abs/2507.06392 https://

VoI-aware Scheduling Schemes for Multi-Agent Formation Control
Formation control allows agents to maintain geometric patterns using local information, but most existing methods assume ideal communication. This paper introduces a goal-oriented framework combining control, cooperative positioning, and communication scheduling for first-order formation tracking. Each agent estimates its position using 6G network-based triangulation, and the scheduling of information updates is governed by Age of Information (AoI) and Value of Information (VoI) metrics. We des…

Age-Aware CSI Acquisition of a Finite-State Markovian Channel
Onur Ayan, Jiping Luo, Xueli An, Nikolaos Pappas
https://arxiv.org/abs/2507.05042 https://

Age-Aware CSI Acquisition of a Finite-State Markovian Channel
The Age of Information (AoI) has emerged as a critical metric for quantifying information freshness; however, its interplay with channel estimation in partially observable wireless systems remains underexplored. This work considers a transmitter-receiver pair communicating over an unreliable channel with time-varying reliability levels. The transmitter observes the instantaneous link reliability through a channel state information acquisition procedure, during which the data transmission is int…

Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameters
Sohom Bhattacharya, Yongzhuo Chen, Muxuan Liang
https://arxiv.org/abs/2507.07941

Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameters
In the age of large and heterogeneous datasets, the integration of information from diverse sources is essential to improve parameter estimation. Multi-task learning offers a powerful approach by enabling simultaneous learning across related tasks. In this work, we introduce a late fusion framework for multi-task learning with semiparametric models that involve infinite-dimensional nuisance parameters, focusing on applications such as heterogeneous treatment effect estimation across multiple da…

Measuring the co-evolution of online engagement with (mis)information and its visibility at scale
Yueting Han, Paolo Turrini, Marya Bazzi, Giulia Andrighetto, Eugenia Polizzi, Manlio De Domenico
https://arxiv.org/abs/2506.06106

Measuring the co-evolution of online engagement with (mis)information and its visibility at scale
Online attention is an increasingly valuable resource in the digital age, with extraordinary events such as the COVID-19 pandemic fuelling fierce competition around it. As misinformation pervades online platforms, users seek credible sources, while news outlets compete to attract and retain their attention. Here we measure the co-evolution of online "engagement" with (mis)information and its "visibility", where engagement corresponds to user interactions on social media, and visibility to fluct…

On the Distribution of Age of Information in Time-varying Updating Systems
Jin Xu, Weiqi Wang, Natarajan Gautam
https://arxiv.org/abs/2507.03799 https://…

On the Distribution of Age of Information in Time-varying Updating Systems
Age of Information (AoI) is a crucial metric for quantifying information freshness in real-time systems where the sampling rate of data packets is time-varying. Evaluating AoI under such conditions is challenging, as system states become temporally correlated and traditional stationary analysis is inapplicable. We investigate an $M_{t}/G/1/1$ queueing system with a time-varying sampling rate and probabilistic preemption, proposing a novel analytical framework based on multi-dimensional partial …

Intuitive dissection of the Gaussian information bottleneck method with an application to optimal prediction
Vahe Galstyan, Age Tjalma, Pieter Rein ten Wolde
https://arxiv.org/abs/2507.05183

Intuitive dissection of the Gaussian information bottleneck method with an application to optimal prediction
Efficient signal representation is essential for the functioning of living and artificial systems operating under resource constraints. A widely recognized framework for deriving such representations is the information bottleneck method, which yields the optimal strategy for encoding a random variable, such as the signal, in a way that preserves maximal information about a functionally relevant variable, subject to an explicit constraint on the amount of information encoded. While in its genera…

Let’s be crystal clear about what this law actually accomplishes: It makes it harder for adults to access perfectly legal (and often helpful) information and services. It forces people to create detailed trails of their online activit…

Didn’t Take Long To Reveal The UK’s Online Safety Act Is Exactly The Privacy-Crushing Failure Everyone Warned About
Well, well, well. The “age assurance” part of the UK’s Online Safety Act has finally gone into effect, with its age checking requirements kicking in a week and a half ago. And what do you kno…

Let’s be crystal clear about what this law actually accomplishes: It makes it harder for adults to access perfectly legal (and often helpful) information and services. It forces people to create detailed trails of their online activit…

Didn’t Take Long To Reveal The UK’s Online Safety Act Is Exactly The Privacy-Crushing Failure Everyone Warned About
Well, well, well. The “age assurance” part of the UK’s Online Safety Act has finally gone into effect, with its age checking requirements kicking in a week and a half ago. And what do you kno…

"“I Don’t Think Librarians Can Save Us”: The Material Conditions of Information Literacy Instruction in the Misinformation Age"
https://crl.acrl.org/index.php/crl/article/view/26856
"This national qualitative study investigates academic librarians’ instruc…

Patents as Knowledge Artifacts: An Information Science Perspective on Global Innovation
M. S. Rajeevan, B. Mini Devi
https://arxiv.org/abs/2508.00871 https://

Patents as Knowledge Artifacts: An Information Science Perspective on Global Innovation
In an age of fast-paced technological change, patents have evolved into not only legal mechanisms of intellectual property, but also structured storage containers of knowledge full of metadata, categories, and formal innovation. This chapter proposes to reframe patents in the context of information science, by focusing on patents as knowledge artifacts, and by seeing patents as fundamentally tied to the global movement of scientific and technological knowledge. With a focus on three areas, the …

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Andrea Munari, Cedomir Stefanovic
https://arxiv.org/abs/2506.04793

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Age of Information (AoI) has emerged as a key metric for assessing data freshness in IoT applications, where a large number of devices report time-stamped updates to a monitor. Such systems often rely on random access protocols based on variations of ALOHA at the link layer, where collision resolution algorithms play a fundamental role to enable reliable delivery of packets. In this context, we provide the first analytical characterization of average AoI for the classical Capetanakis tree-based…

The Age of Sensorial Zero Trust: Why We Can No Longer Trust Our Senses
Fabio Correa Xavier
https://arxiv.org/abs/2507.00907 https://a…

The Age of Sensorial Zero Trust: Why We Can No Longer Trust Our Senses
In a world where deepfakes and cloned voices are emerging as sophisticated attack vectors, organizations require a new security mindset: Sensorial Zero Trust [9]. This article presents a scientific analysis of the need to systematically doubt information perceived through the senses, establishing rigorous verification protocols to mitigate the risks of fraud based on generative artificial intelligence. Key concepts, such as Out-of-Band verification, Vision-Language Models (VLMs) as forensic col…

In the digital age, misinformation spreads rapidly, making it increasingly difficult to ensure the integrity of information. AI presents new opportunities to support fact-checking and news classification. Join Giovanna Monti and Lucian Precup as they share insights from their work developing an AI-driven platform integrating search capabilities, an intelligent assistant and a RAG system.
Learn more:

Hello!
I have a happy favour to ask.
Last year, I had a US intern working with us and she now is looking for help that you- good reader of this account- could give.
(She needs academic survey participants)
Check out her flyer below, click the link, and please RT
http…

Research Study on Data Privacy and Collective Redress
A researcher at University College Dublin wants to conduct anonymous interviews to learn about why you would or would not participate in a legal action to rectify a data protection violation. This information can be used to help nonprofit organizations better represent you when organizations violate your data protection rights. Provide your email to receive more information. All personally identifiable information will be deleted following completion of the study.

Enhanced Velocity-Adaptive Scheme: Joint Fair Access and Age of Information Optimization in Vehicular Networks
Xiao Xu, Qiong Wu, Pingyi Fan, Kezhi Wang, Nan Cheng, Wen Chen, Khaled B. Letaief
https://arxiv.org/abs/2507.18328

Enhanced Velocity-Adaptive Scheme: Joint Fair Access and Age of Information Optimization in Vehicular Networks
In this paper, we consider the fair access problem and the Age of Information (AoI) under 5G New Radio (NR) Vehicle-to-Infrastructure (V2I) Mode 2 in vehicular networks. Specifically, vehicles follow Mode 2 to communicate with Roadside Units (RSUs) to obtain accurate data for driving assistance.Nevertheless, vehicles often have different velocity when they are moving in adjacent lanes, leading to difference in RSU dwelltime and communication duration. This results in unfair access to network re…

Spatio-Temporal Information Freshness for Remote Source Monitoring in IoT Systems
Andrea Munari, Federico Chiariotti, Leonardo Badia, Petar Popovski
https://arxiv.org/abs/2506.04804

Spatio-Temporal Information Freshness for Remote Source Monitoring in IoT Systems
The widespread adoption of age of information (AoI) as a meaningful and analytically tractable information freshness metric has led to a wide body of work on the timing performance of Internet of things (IoT) systems. However, the spatial correlation inherent to environmental monitoring has been mostly neglected in the recent literature, due to the significant modeling complexity it introduces. In this work, we address this gap by presenting a model of spatio-temporal information freshness, con…

An Age-based Study into Interactive Narrative Visualization Engagement
Nina Errey, Yi Chen, Yu Dong, Quang Vinh Nguyen, Xiaoru Yuan, Tuck Wah Leong, Christy Jie Liang
https://arxiv.org/abs/2507.12734

An Age-based Study into Interactive Narrative Visualization Engagement
Research has shown that an audiences' age impacts their engagement in digital media. Interactive narrative visualization is an increasingly popular form of digital media that combines data visualization and storytelling to convey important information. However, audience age is often overlooked by interactive narrative visualization authors. Using an established visualization engagement questionnaire, we ran an empirical experiment where we compared end-user engagement to audience age. We found …

Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images
Fangyijie Wang, Yuan Liang, Sourav Bhattacharjee, Abey Campbell, Kathleen M. Curran, Gu\'enol\'e Silvestre
https://arxiv.org/abs/2506.20407

Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images
Accurate gestational age (GA) estimation, ideally through fetal ultrasound measurement, is a crucial aspect of providing excellent antenatal care. However, deriving GA from manual fetal biometric measurements depends on the operator and is time-consuming. Hence, automatic computer-assisted methods are demanded in clinical practice. In this paper, we present a novel feature fusion framework to estimate GA using fetal ultrasound images without any measurement information. We adopt a deep learning…

"And quite an adventure the life of Margittai Neumann Janos Lajos was. A child prodigy, he published his first paper in mathematics before age 20. He was the indisputable champion of applied mathematics in the 20th century. His work yielded groundbreaking advances in theoretical mathematics, quantum mechanics, game theory, economics, fluid dynamics, artificial intelligence, electrodynamics, meteorology, and computing."

William Aspray
There was a moment in which Kurt Gödel, Albert Einstein, and John von Neumann were all roaming the halls of the Institute for Advanced Studies in Princeton at the same time. Let that information sink in. Humanity experiences such gatherings of brilliant minds in a remote location of the space-time continuum only every so often; maybe the ancient Greeks and the men of the Renaissance witnessed such periods in time, as did the IAS staff at the end of World War II. How much will we have to wait f…

Bridging the Gap: Enhancing News Interpretation Across Diverse Audiences with Large Language Models
Leyi Ouyang
https://arxiv.org/abs/2507.21055 https://ar…

Bridging the Gap: Enhancing News Interpretation Across Diverse Audiences with Large Language Models
In the interconnected world, news media are critical in conveying information to public across diverse domains including technology, finance, and agriculture. Journalists make efforts to present accurate information, however, the interpretation of news often varies significantly among different audiences due to their specific expertise and age. In this work, we investigate how to identify these comprehension gaps and provide solutions to improve audiences understanding of news content, particul…

The proportion of the U.S. population who are Latino or Asian American is expected to rise to 33% by 2050,
and will number over 135 million people.
Understanding rates of Age Related Macular Degeneration, #AMD, in these groups is imperative,
so that clinicians can have better insight into who is most at risk for developing this disease and health policy-makers can use this information to he…

Racial Differences in Age-Related Macular Degeneration Rates in the United States: A Longitudinal Analysis of a Managed Care Network

Protoplanetary Disk Survival Time-scales: A Blind Survey of Young Clusters up to 100 Myr in the Solar Vicinity
Gregory Mathews Ben, Jessy Jose, Jes\'us Hern\'andez
https://arxiv.org/abs/2507.01619

Protoplanetary Disk Survival Time-scales: A Blind Survey of Young Clusters up to 100 Myr in the Solar Vicinity
We study the protoplanetary disk lifetimes using a large sample of young stellar objects in nearby clusters. To investigate the final phase of disk dissipation, we selected 32 clusters, located within 500 pc and aged between 1 and 100 Myr, with membership determined using Gaia data. The Age and mass information of the sources are obtained through spectral energy distribution (SED) analysis and using evolutionary models of various ages. Using the IR data from 2MASS and WISE catalogues, we employ…

Safe Deep Reinforcement Learning for Resource Allocation with Peak Age of Information Violation Guarantees
Berire Gunes Reyhan, Sinem Coleri
https://arxiv.org/abs/2507.08653

Safe Deep Reinforcement Learning for Resource Allocation with Peak Age of Information Violation Guarantees
In Wireless Networked Control Systems (WNCSs), control and communication systems must be co-designed due to their strong interdependence. This paper presents a novel optimization theory-based safe deep reinforcement learning (DRL) framework for ultra-reliable WNCSs, ensuring constraint satisfaction while optimizing performance, for the first time in the literature. The approach minimizes power consumption under key constraints, including Peak Age of Information (PAoI) violation probability, tra…

Podcast: The Tea Hack Just Keeps Getting Worse https://www.404media.co/podcast-the-tea-hack-just-keeps-getting-worse/

A Survey on False Information Detection: From A Perspective of Propagation on Social Networks
Kun Xie, Sibo Wang
https://arxiv.org/abs/2506.18052 https://

A Survey on False Information Detection: From A Perspective of Propagation on Social Networks
The proliferation of false information in the digital age has become a pressing concern, necessitating the development of effective and robust detection methods. This paper offers a comprehensive review of existing false information detection techniques, approached from a novel perspective that emphasizes the propagation characteristics of misinformation. We introduce a new taxonomy that categorizes these methods into homogeneous and heterogeneous propagation-based approaches, providing a deepe…

Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Framework
Beining Wu, Jun Huang, Qiang Duan, Liang Dong, Zhipeng Cai
https://arxiv.org/abs/2507.00856

Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Framework
This paper aims to enhance the performance of Vehicular Platooning (VP) systems integrated with Wireless Federated Learning (WFL). In highly dynamic environments, vehicular platoons experience frequent communication changes and resource constraints, which significantly affect information exchange and learning model synchronization. To address these challenges, we first formulate WFL in VP as a joint optimization problem that simultaneously considers Age of Information (AoI) and Federated Learni…

This https://arxiv.org/abs/2505.03458 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

The classification of Alzheimer's disease and mild cognitive impairment improved by dynamic functional network analysis
Brain network analysis using functional MRI has advanced our understanding of cortical activity and its changes in neurodegenerative disorders that cause dementia. Recently, research in brain connectivity has focused on dynamic (time-varying) brain networks that capture both spatial and temporal information on cortical, regional co-activity patterns. However, this approach has been largely unexplored within the Alzheimer's spectrum. We analysed age- and sex-matched static and dynamic fMRI brain…

On the Age of Information in Single-Server Queues with Aged Updates
Fernando Miguelez, Urtzi Ayesta, Josu Doncel, Maria Dolores Ugarte
https://arxiv.org/abs/2506.19648

On the Age of Information in Single-Server Queues with Aged Updates
The Age of Information (AoI) is a performance metric that quantifies the freshness of data in systems where timely updates are critical. Most state-of-the-art methods typically assume that packets enter the monitored system with zero age, neglecting situations, such as those prevalent in multi-hop networks or distributed sensing, where packets experience prior delays. In this paper, the AoI is investigated when packets have a non-zero initial age. We derive an expression for the average AoI in …

State- versus Reaction-Based Information Processing in Biochemical Networks
Anne-Lena Moor, Age Tjalma, Manuel Reinhardt, Pieter Rein ten Wolde, Christoph Zechner
https://arxiv.org/abs/2505.13373

State- versus Reaction-Based Information Processing in Biochemical Networks
Trajectory mutual information is frequently used to quantify information transfer in biochemical systems. Tractable solutions of the trajectory mutual information can be obtained via the widely used Linear-Noise Approximation (LNA) using Gaussian channel theory. This approach is expected to be accurate for sufficiently large systems. However, recent observations show that there are cases, where the mutual information obtained this way differs qualitatively from results derived using an exact Ma…

This https://arxiv.org/abs/2410.23394 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Auditing for Bias in Ad Delivery Using Inferred Demographic Attributes
Auditing social-media algorithms has become a focus of public-interest research and policymaking to ensure their fairness across demographic groups such as race, age, and gender in consequential domains such as the presentation of employment opportunities. However, such demographic attributes are often unavailable to auditors and platforms. When demographics data is unavailable, auditors commonly infer them from other available information. In this work, we study the effects of inference error …

This https://arxiv.org/abs/2505.07212 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

The Language of Influence: Sentiment, Emotion, and Hate Speech in State Sponsored Influence Operations
State-sponsored influence operations (SIOs) have become a pervasive and complex challenge in the digital age, particularly on social media platforms where information spreads rapidly and with minimal oversight. These operations are strategically employed by nation-state actors to manipulate public opinion, exacerbate social divisions, and project geopolitical narratives, often through the dissemination of misleading or inflammatory content. Despite increasing awareness of their existence, the s…

Age of Information in Unreliable Tandem Queues
Muthukrishnan Senthilkumar, Aresh Dadlani, Hina Tabassum
https://arxiv.org/abs/2506.09245 https://

Age of Information in Unreliable Tandem Queues
Stringent demands for timely information delivery, driven by the widespread adoption of real-time applications and the Internet of Things, have established the age of information (AoI) as a critical metric for quantifying data freshness. Existing AoI models often assume multi-hop communication networks with fully reliable nodes, which may not accurately capture scenarios involving node transmission failures. This paper presents an analytical framework for two configurations of tandem queue syst…

On the Role of Age and Semantics of Information in Remote Estimation of Markov Sources
Jiping Luo, Nikolaos Pappas
https://arxiv.org/abs/2507.18514 https://

On the Role of Age and Semantics of Information in Remote Estimation of Markov Sources
This paper investigates the semantics-aware remote estimation of a finite-state Markov chain. We employ the maximum a posteriori (MAP) estimator and aim to devise a transmission policy to optimize estimation performance subject to a transmission frequency constraint. We leverage two metrics, namely the Age of Consecutive Error (AoCE) and the Age of Information (AoI), to quantify, respectively, the significance of estimation error at the transmitter and the predictability of outdated information…

Bidirectional Age of Incorrect Information: A Performance Metric for Status Updates in Virtual Dynamic Environments
Chiara Schiavo, Manuele Favero, Alessandro Buratto, Leonardo Badia
https://arxiv.org/abs/2507.13312

Bidirectional Age of Incorrect Information: A Performance Metric for Status Updates in Virtual Dynamic Environments
Virtual dynamic environments (VDEs) such as the Metaverse and digital twins (DTs) require proper representation of the interacting entities to map their characteristics within the simulated or augmented space. Keeping these representations accurate and up-to-date is crucial for seamless interaction and system reliability. In this paper, we propose bidirectional age of incorrect information (BAoII) to address this aspect. BAoII quantifies the time-dependent penalty paid by an entity in a VDE due…

AI, AGI, and learning efficiency
My 4-month-old kid is not DDoSing Wikipedia right now, nor will they ever do so before learning to speak, read, or write. Their entire "training corpus" will not top even 100 million "tokens" before they can speak & understand language, and do so with real intentionally.
Just to emphasize that point: 100 words-per-minute times 60 minutes-per-hour times 12 hours-per-day times 365 days-per-year times 4 years is a mere 105,120,000 words. That's a ludicrously *high* estimate of words-per-minute and hours-per-day, and 4 years old (the age of my other kid) is well after basic speech capabilities are developed in many children, etc. More likely the available "training data" is at least 1 or 2 orders of magnitude less than this.
The point here is that large language models, trained as they are on multiple *billions* of tokens, are not developing their behavioral capabilities in a way that's remotely similar to humans, even if you believe those capabilities are similar (they are by certain very biased ways of measurement; they very much aren't by others). This idea that humans must be naturally good at acquiring language is an old one (see e.g. #AI #LLM #AGI

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
Geng Sun, Likun Zhang, Jiahui Li, Jing Wu, Jiacheng Wang, Zemin Sun, Changyuan Zhao, Victor C. M. Leung
https://arxiv.org/abs/2507.08429

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
The integration of unmanned aerial vehicles (UAVs) with Internet of Things (IoT) networks offers promising solutions for efficient data collection. However, the limited energy capacity of UAVs remains a significant challenge. In this case, laser beam directors (LBDs) have emerged as an effective technology for wireless charging of UAVs during operation, thereby enabling sustained data collection without frequent returns to charging stations (CSs). In this work, we investigate the age of informa…

From Timestamps to Versions: Version AoI in Single- and Multi-Hop Networks
Erfan Delfani, Nikolaos Pappas
https://arxiv.org/abs/2507.23433 https://arxiv.or…

From Timestamps to Versions: Version AoI in Single- and Multi-Hop Networks
Timely and informative data dissemination in communication networks is essential for enhancing system performance and energy efficiency, as it reduces the transmission of outdated or redundant data. Timeliness metrics, such as Age of Information (AoI), effectively quantify data freshness; however, these metrics fail to account for the intrinsic informativeness of the content itself. To address this limitation, content-based metrics have been proposed that combine both timeliness and informative…