Tootfinder

Case Studies: Effective Approaches for Navigating Cross-Border Cloud Data Transfers Amid U.S. Government Privacy and Safety Concerns
Motunrayo Adebayo
https://arxiv.org/abs/2509.00006

Case Studies: Effective Approaches for Navigating Cross-Border Cloud Data Transfers Amid U.S. Government Privacy and Safety Concerns
This study attempts to explain the impact of information exchange from one country to another, as well as the legal and technological implications for these exchanges. Due to the emergence of cloud technology, possibilities for free exchange of information between countries have increased rapidly, as it has become possible to save information in a country and access it in almost any part of the world. Countries all around the world have been confronted with developing frameworks to facilitate t…

BidenCash carding market domains seized in international operation
https://www.bleepingcomputer.com/news/security/bidencash-carding-market-domains-seized-in-international-operation/

BidenCash carding market domains seized in international operation
Earlier today, law enforcement seized multiple domains of BidenCash, the infamous dark web market for stolen credit cards, personal information, and SSH access.

Privacy, Informed Consent and the Demand for Anonymisation of Smart Meter Data
Saurab Chhachhi, Fei Teng
https://arxiv.org/abs/2509.00101 https://arxiv.org…

Privacy, Informed Consent and the Demand for Anonymisation of Smart Meter Data
Access to smart meter data offers system-wide benefits but raises significant privacy concerns due to the personal information it contains. Privacy-preserving techniques could facilitate wider access, though they introduce privacy-utility trade-offs. Understanding consumer valuations for anonymisation can help identify appropriate trade-offs. However, existing studies do not focus on anonymisation specifically or account for information asymmetries regarding privacy risks, raising questions abo…

Coordinated Multi-BS SSB Beam Design for Enhanced Initial Access Coverage
Hakime BarghiZanjani, Bikshapathi Gouda, Antti T\"olli
https://arxiv.org/abs/2506.02760

Coordinated Multi-BS SSB Beam Design for Enhanced Initial Access Coverage
Ensuring strong synchronization signal block (SSB) coverage is essential for reliable user equipment (UE) connection during initial access. While techniques such as power boosting and network densification are commonly used, this work explores joint transmission (JT) of SSBs as an alternative to enhance coverage. Although JT is widely applied in data transmission, its use for SSBs has not been explored due to the lack of channel state information, which prevents coherent signal alignment across…

Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis
Rafi Al Attrach, Pedro Moreira, Rajna Fani, Renato Umeton, Leo Anthony Celi
https://arxiv.org/abs/2507.01053

Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis
As ever-larger clinical datasets become available, they have the potential to unlock unprecedented opportunities for medical research. Foremost among them is Medical Information Mart for Intensive Care (MIMIC-IV), the world's largest open-source EHR database. However, the inherent complexity of these datasets, particularly the need for sophisticated querying skills and the need to understand the underlying clinical settings, often presents a significant barrier to their effective use. M3 lowers…

From One-Dimensional Codes to Two-Dimensional Codes: A Universal Framework for the Bounded-Weight Constraint
Viet Hai Le, Thanh Phong Pham, Tuan Thanh Nguyen, Kui Cai, Kees A. Schouhamer Immink
https://arxiv.org/abs/2509.01240

From One-Dimensional Codes to Two-Dimensional Codes: A Universal Framework for the Bounded-Weight Constraint
Recent developments in storage- especially in the area of resistive random access memory (ReRAM)- are attempting to scale the storage density by regarding the information data as two-dimensional (2D), instead of one-dimensional (1D). Correspondingly, new types of 2D constraints are introduced into the input information data to improve the system reliability. While 1D constraints have been extensively investigated in the literature, the study for 2D constraints is much less profound. Particularl…

Filing: credit reporting giant TransUnion discloses a data breach affecting 4.4M customers' personal info but claims "no credit information was accessed" (Zack Whittaker/TechCrunch)
https://techcrunch.com/2025/08/28/tran

TransUnion says hackers stole 4.4 million customers' personal information | TechCrunch
The credit reporting giant confirmed unauthorized access to a third-party application storing the personal information of its customers.

Credit reporting giant TransUnion has disclosed a data breach
affecting more than 4.4 million customers’ personal information.
In a filing with Maine’s attorney general’s office on Thursday, TransUnion attributed the July 28 breach to unauthorized access of a third-party application storing customers’ personal data for its U.S. consumer support operations.
TransUnion claimed “no credit information was accessed,” but provided no immediate evidence for its claim.
The d…

TransUnion says hackers stole 4.4 million customers' personal information | TechCrunch
The credit reporting giant confirmed unauthorized access to a third-party application storing the personal information of its customers, including Social Security numbers.

Quantum state reconstruction with variational quantum circuit
Shabnam Jabeen, Dmytro Kurdydyk, Aadi Palnitkar, Mihir Talati, Jeffrey Yan, Jinghong Yang
https://arxiv.org/abs/2507.01246

Quantum state reconstruction with variational quantum circuit
Reconstructing quantum states from measurement data represents a formidable challenge in quantum information science, especially as system sizes grow beyond the reach of traditional tomography methods. While recent studies have explored quantum machine learning (QML) for quantum state tomography (QST), nearly all rely on idealized assumptions, such as direct access to the unknown quantum state as quantum data input, which are incompatible with current hardware constraints. In this work, we pres…

On Performance of IoT Networks with Coordinated NOMA Transmission: Covert Monitoring and Information Decoding
Thai-Hoc Vu, Anh-Tu Le, Ngo Hoang Tu, Tan N. Nguyen, Miroslav Voznak
https://arxiv.org/abs/2509.01935

On Performance of IoT Networks with Coordinated NOMA Transmission: Covert Monitoring and Information Decoding
This work investigates the covertness and security performance of Internet-of-Things (IoTs) networks under Rayleigh fading environments. Specifically, a cellular source transmits covert information to cell-edge users with the assistance of an IoT master node, employing a coordinated direct and relay transmission strategy combined with non-orthogonal multiple access (NOMA). This approach not only enhances spectrum utilization but also generates friendly interference to complicate a warden's surv…

Russia jails man for 16 years over pro-Ukraine cyberattacks on critical infrastructure https://therecord.media/russia-jails-man-over-pro-ukraine-cyberattacks

On the Complexity of Knapsack under Explorable Uncertainty: Hardness and Algorithms
Jens Schl\"oter
https://arxiv.org/abs/2507.02657 https://

On the Complexity of Knapsack under Explorable Uncertainty: Hardness and Algorithms
In the knapsack problem under explorable uncertainty, we are given a knapsack instance with uncertain item profits. Instead of having access to the precise profits, we are only given uncertainty intervals that are guaranteed to contain the corresponding profits. The actual item profit can be obtained via a query. The goal of the problem is to adaptively query item profits until the revealed information suffices to compute an optimal (or approximate) solution to the underlying knapsack instance.…

ARMOUR US: Android Runtime Zero-permission Sensor Usage Monitoring from User Space
Yan Long, Jiancong Cui, Yuqing Yang, Tobias Alam, Zhiqiang Lin, Kevin Fu
https://arxiv.org/abs/2507.02177

ARMOUR US: Android Runtime Zero-permission Sensor Usage Monitoring from User Space
This work investigates how to monitor access to Android zero-permission sensors which could cause privacy leakage to users. Moreover, monitoring such sensitive access allows security researchers to characterize potential sensor abuse patterns. Zero-permission sensors such as accelerometers have become an indispensable part of Android devices. The critical information they provide has attracted extensive research investigating how data collectors could capture more sensor data to enable both ben…

Synthetic generation of online social networks through homophily
Alejandro Buitrago L\'opez, Javier Pastor-Galindo, Jos\'e A. Ruip\'erez-Valiente
https://arxiv.org/abs/2509.02762

Synthetic generation of online social networks through homophily
Online social networks (OSNs) have become increasingly relevant for studying social behavior and information diffusion. Nevertheless, they are limited by restricted access to real OSN data due to privacy, legal, and platform-related constraints. In response, synthetic social networks serve as a viable approach to support controlled experimentation, but current generators reproduce only topology and overlook attribute-driven homophily and semantic realism. This work proposes a homophily-based …

maria goes NIFTy: Gaussian Process-Based Reconstruction and Denoising of Simulated (Sub-)Millimetre Single-Dish Telescope Data
Jonas W\"urzinger, Joshiwa van Marrewijk, Thomas W. Morris, Richard Fuchs, Tony Mroczkowski, Lukas Heinrich
https://arxiv.org/abs/2509.01600

maria goes NIFTy: Gaussian Process-Based Reconstruction and Denoising of Simulated (Sub-)Millimetre Single-Dish Telescope Data
(Sub-)millimetre single-dish telescopes feature faster mapping speeds and access larger spatial scales than their interferometric counterparts. However, atmospheric fluctuations tend to dominate their signals and complicate recovery of the astronomical sky. Here we develop a framework for Gaussian process-based sky reconstruction and separation of the atmospheric emission from the astronomical signal based on Numerical Information Field Theory (\texttt{NIFTy}). To validate this novel approach, …

Trump wins as judge allows DOGE to access 'sensitive' info
https://lawandcrime.com/high-profile/still-cannot-step-in-trump-admin-scores-victory-as-judge-denies-labor-unions-injunction-and-allows-doge-to-access-stockpile-of-extremely-sensitive-information/

DICOM De-Identification via Hybrid AI and Rule-Based Framework for Scalable, Uncertainty-Aware Redaction
Kyle Naddeo, Nikolas Koutsoubis, Rahul Krish, Ghulam Rasool, Nidhal Bouaynaya, Tony OSullivan, Raj Krish
https://arxiv.org/abs/2507.23736

DICOM De-Identification via Hybrid AI and Rule-Based Framework for Scalable, Uncertainty-Aware Redaction
Access to medical imaging and associated text data has the potential to drive major advances in healthcare research and patient outcomes. However, the presence of Protected Health Information (PHI) and Personally Identifiable Information (PII) in Digital Imaging and Communications in Medicine (DICOM) files presents a significant barrier to the ethical and secure sharing of imaging datasets. This paper presents a hybrid de-identification framework developed by Impact Business Information Solutio…

Positioning AI Tools to Support Online Harm Reduction Practice: Applications and Design Directions
Kaixuan Wang, Jason T. Jacques, Chenxin Diao
https://arxiv.org/abs/2506.22941

Positioning AI Tools to Support Online Harm Reduction Practice: Applications and Design Directions
Access to accurate and actionable harm reduction information can directly impact the health outcomes of People Who Use Drugs (PWUD), yet existing online channels often fail to meet their diverse and dynamic needs due to limitations in adaptability, accessibility, and the pervasive impact of stigma. Large Language Models (LLMs) present a novel opportunity to enhance information provision, but their application in such a high-stakes domain is under-explored and presents socio-technical challenges…

DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router
Minghao Guo, Qingcheng Zeng, Xujiang Zhao, Yanchi Liu, Wenchao Yu, Mengnan Du, Haifeng Chen, Wei Cheng
https://arxiv.org/abs/2507.22050

DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router
Large Language Models (LLMs) excel at many reasoning tasks but struggle with knowledge-intensive queries due to their inability to dynamically access up-to-date or domain-specific information. Retrieval-Augmented Generation (RAG) has emerged as a promising solution, enabling LLMs to ground their responses in external sources. However, existing RAG methods lack fine-grained control over both the query and source sides, often resulting in noisy retrieval and shallow reasoning. In this work, we in…

Enhancing Manufacturing Knowledge Access with LLMs and Context-aware Prompting
Sebastian Monka, Irlan Grangel-Gonz\'alez, Stefan Schmid, Lavdim Halilaj, Marc Rickart, Oliver Rudolph, Rui Dias
https://arxiv.org/abs/2507.22619

Enhancing Manufacturing Knowledge Access with LLMs and Context-aware Prompting
Knowledge graphs (KGs) have transformed data management within the manufacturing industry, offering effective means for integrating disparate data sources through shared and structured conceptual schemas. However, harnessing the power of KGs can be daunting for non-experts, as it often requires formulating complex SPARQL queries to retrieve specific information. With the advent of Large Language Models (LLMs), there is a growing potential to automatically translate natural language queries into…

Ukrainian hack uncovers 'thousands of files' proving Russia's mass abduction of children, intelligence claims: https://benborges.xyz/2025/07/30/ukrainian-hack-uncovers-thousands-of.html

In its white paper ‘Beyond AI & Copyright’, @… emphasises two structural risks of AI-supported access to knowledge:
1. the concentration of control over knowledge in the hands of a few powerful actors
2. the erosion of the institutions and economic foundations of human information production.
To preserve digital knowledge communities, he calls for …

Multi-dimensional frequency-bin entanglement-based quantum key distribution network
George Claudiu Crisan, Antoine Henry, Dario Alessandro Fioretto, Juan Rafael Alvarez, St\'ephan Monfray, Fr\'ed\'eric Boeuf, Laurent Vivien, Eric Cassan, Carlos Alonso-Ramos, Nadia Belabas
https://arxiv.org/abs/2507.00972

Multi-dimensional frequency-bin entanglement-based quantum key distribution network
Quantum networks enhance quantum communication schemes and link multiple users over large areas. Harnessing high dimensional quantum states - i.e. qu-d-its - allows for a denser transfer of information with increased robustness to noise compared to qubits. Frequency encoding enables access to such qu-d-its at telecom wavelengths, while manipulating quantum information with off-the-shelf fibered devices. We use a low free spectral range silicon microresonator to generate Bell states of dimensi…

"Microsoft can't protect French data from US government access"
#microsoft

Microsoft can't protect French data from US government access
Company admits under oath that American authorities can demand European citizen information despite security promises.

This https://arxiv.org/abs/2502.19030 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Sampling nodes and hyperedges via random walks on large hypergraphs
Hypergraphs provide a fundamental framework for representing complex systems involving interactions among three or more entities. As empirical hypergraphs grow in size, characterizing their structural properties becomes increasingly challenging due to computational complexity and, in some cases, restricted access to complete data, requiring efficient sampling methods. Random walks offer a practical approach to hypergraph sampling, as they rely solely on local neighborhood information from nodes…

A Review of Various Datasets for Machine Learning Algorithm-Based Intrusion Detection System: Advances and Challenges
Sudhanshu Sekhar Tripathy, Bichitrananda Behera
https://arxiv.org/abs/2506.02438

A Review of Various Datasets for Machine Learning Algorithm-Based Intrusion Detection System: Advances and Challenges
IDS aims to protect computer networks from security threats by detecting, notifying, and taking appropriate action to prevent illegal access and protect confidential information. As the globe becomes increasingly dependent on technology and automated processes, ensuring secured systems, applications, and networks has become one of the most significant problems of this era. The global web and digital technology have significantly accelerated the evolution of the modern world, necessitating the u…

TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness
Pritam Mishra, Coloma Ballester, Dimosthenis Karatzas
https://arxiv.org/abs/2506.20588

TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness
The increasing ubiquity of video content and the corresponding demand for efficient access to meaningful information have elevated video summarization and video highlights as a vital research area. However, many state-of-the-art methods depend heavily either on supervised annotations or on attention-based models, which are computationally expensive and brittle in the face of distribution shifts that hinder cross-domain applicability across datasets. We introduce a pioneering self-supervised vid…

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…

Derivation of CRB and Refined SINR Expressions for OTFS-RSMA LEO ISAC Systems
Bruno Felipe Costa, Taufik Abr\~ao
https://arxiv.org/abs/2506.02771 https://

Derivation of CRB and Refined SINR Expressions for OTFS-RSMA LEO ISAC Systems
This document provides detailed step-by-step derivations for the Cramér-Rao Bounds (CRB) for sensing parameters and the refined Signal-to-Interference-plus-Noise Ratio (SINR) expressions under imperfect Channel State Information (CSI) and imperfect Successive Interference Cancellation (SIC) for the Orthogonal Time Frequency Space (OTFS) Rate-Splitting Multiple Access (RSMA) framework presented in our main work "An Integrated OTFS-RSMA Framework for LEO Satellite ISAC: Modeling, Metrics, and Po…

Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation
Chang Liu, Yixin Wang, Moontae Lee
https://arxiv.org/abs/2506.21362

Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation
Efficient access to high-quality information is vital for online platforms. To promote more useful information, users not only create new content but also evaluate existing content, often through helpfulness voting. Although aggregated votes help service providers rank their user content, these votes are often biased by disparate accessibility per position and the cascaded influence of prior votes. For a fairer assessment of information quality, we propose the Counterfactual Voting Adjustment (…

As part of my spam this morning, from Indian telecoms provider Airtel: "to find the right information in seconds" 🙄.

"DOGE secured the power to view records that contain competitors’ trade secrets, nonpublic details about government contracts, and sensitive regulatory actions or other information."
'Vulnerable': New alarm as Musk's 'God tier access' to damaging data revealed - Raw Story
https://www.rawstory.com/musk-private-data/

Cell-Free Massive MIMO SWIPT with Beyond Diagonal Reconfigurable Intelligent Surfaces
Duc Thien Hua, Mohammadali Mohammadi, Hien Quoc Ngo, Michail Matthaiou
https://arxiv.org/abs/2507.23702

Cell-Free Massive MIMO SWIPT with Beyond Diagonal Reconfigurable Intelligent Surfaces
We investigate the integration of beyond diagonal reconfigurable intelligent surfaces (BDRISs) into cell free massive multiple input multiple output (CFmMIMO) systems to enhance simultaneous wireless information and power transfer (SWIPT). To simultaneously support two groups of users energy receivers (ERs) and information receivers (IRs) without sacrificing time frequency resources, a subset of access points (APs) is dedicated to serving ERs with the aid of a BDRIS, while the remaining APs foc…

Safe and Efficient Data-driven Connected Cruise Control
Haosong Xiao, Chaozhe R. He
https://arxiv.org/abs/2507.22227 https://arxiv.org/pdf/2507.22227

Safe and Efficient Data-driven Connected Cruise Control
In this paper, we design a safe and efficient cruise control for the connected automated vehicle with access to motion information from multiple vehicles ahead via vehicle-to-vehicle (V2V) communication. Position and velocity data collected from a chain of human-driven vehicles are systematically leveraged to design a connected cruise controller that smoothly responds to traffic perturbations while maximizing energy efficiency. A safety filter derived from a control barrier function provides th…

NGOs urge Zelensky to veto bill restricting access to real estate registers: https://benborges.xyz/2025/08/26/ngos-urge-zelensky-to-veto.html

Morae: Proactively Pausing UI Agents for User Choices
Yi-Hao Peng, Dingzeyu Li, Jeffrey P. Bigham, Amy Pavel
https://arxiv.org/abs/2508.21456 https://arxiv…

Morae: Proactively Pausing UI Agents for User Choices
User interface (UI) agents promise to make inaccessible or complex UIs easier to access for blind and low-vision (BLV) users. However, current UI agents typically perform tasks end-to-end without involving users in critical choices or making them aware of important contextual information, thus reducing user agency. For example, in our field study, a BLV participant asked to buy the cheapest available sparkling water, and the agent automatically chose one from several equally priced options, wit…

Model fine-tuning without compromising information access controls.
"Copilot Tuning" attaches fine-tuning datasets to LLMs while respecting your permissions. See how:
youtu.be/6udJzJAyT5I
#CopilotTuning #copilot

I agree, really think twice or just don't... Also think about US government accessing your personal data if they want....
https://techcrunch.com/2025/07/19/for-privacy-and-security-think-twice-before-granting-ai-acces…

For privacy and security, think twice before granting AI access to your personal data | TechCrunch
AI chatbots, assistants and agents are increasingly asking for gross levels of access to your personal data under the guise of needing your information to make them work.

Geospatial Question Answering on Historical Maps Using Spatio-Temporal Knowledge Graphs and Large Language Models
Ziyi Liu, Sidi Wu, Lorenz Hurni
https://arxiv.org/abs/2508.21491

Geospatial Question Answering on Historical Maps Using Spatio-Temporal Knowledge Graphs and Large Language Models
Recent advances have enabled the extraction of vectorized features from digital historical maps. To fully leverage this information, however, the extracted features must be organized in a structured and meaningful way that supports efficient access and use. One promising approach is question answering (QA), which allows users -- especially those unfamiliar with database query languages -- to retrieve knowledge in a natural and intuitive manner. In this project, we developed a GeoQA system by in…

Information availability in different languages and various technological constraints related to multilinguism on the Internet
Sonal Khosla, Haridasa Acharya
https://arxiv.org/abs/2508.17918

Information availability in different languages and various technological constraints related to multilinguism on the Internet
The usage of Internet has grown exponentially over the last two decades. The number of Internet users has grown from 16 Million to 1650 Million from 1995 to 2010. It has become a major repository of information catering almost every area. Since the Internet has its origin in USA which is English speaking country there is huge dominance of English on the World Wide Web. Although English is a globally acceptable language, still there is a huge population in the world which is not able to access t…

I just implemented librenms-agent and the certificate check on my systems.
I just love the way I can easily access information about a system across its configuration.
For the certificate check I need the domain/s of the system.
While I'm sure this could be further improved it is already a lot of fun to use.
```
az-librenms-certificate = {
enable = true;
domains = [
{ fqdn = "${config.services.freshrss.virtualHost}&qu…

medicX-KG: A Knowledge Graph for Pharmacists' Drug Information Needs
Lizzy Farrugia, Lilian M. Azzopardi, Jeremy Debattista, Charlie Abela
https://arxiv.org/abs/2506.17959

medicX-KG: A Knowledge Graph for Pharmacists' Drug Information Needs
The role of pharmacists is evolving from medicine dispensing to delivering comprehensive pharmaceutical services within multidisciplinary healthcare teams. Central to this shift is access to accurate, up-to-date medicinal product information supported by robust data integration. Leveraging artificial intelligence and semantic technologies, Knowledge Graphs (KGs) uncover hidden relationships and enable data-driven decision-making. This paper presents medicX-KG, a pharmacist-oriented knowledge gr…

Damn straight he (Trudeau) was a pain, to you. Exactly what we want. https://mstdn.ca/@AlisonCreekside/114729209755196986

Alison Creekside (@AlisonCreekside@mstdn.ca)
Attached: 1 image Pillaged from BlueSky: Secretary of the US Dept of Homeland Security Kristi Noem : "The former Prime Minister of Canada Justin Trudeau is a trainwreck. He was hard to work with. Wasn't willing to share criminal background information with us. Wasn't willing to allow us access to their data systems." #cdnpoli

Polish president's veto won't threaten Ukraine's Starlink access, Nawrocki's office claims: https://benborges.xyz/2025/08/26/polish-presidents-veto-wont-threaten.html

2/2 I continued blogging Alberniweather and on FB and Twitter but I gradually removed my personal self from Facebook and eventually during the Pandemic, I decided the Facebook environment was just too toxic even for weather stuff and I shut down my page and left Facebook completely.
The impact on traffic to Alberniweather.ca and its prominence in the community was, and still is, significant.
I have diehard followers, many who have become friends over the years, I still get the odd call from media, or even the public about random weather things.
I have good connections with a few folks at Environment Canada (though their staff have become thinner and more transient :(
and major events still get spikes of local traffic but I since about 2022, and after I removed myself from Twitter that year, I don’t blog nearly as much. I would do a few posts in a week, and then go months without posting. I just got out of the habit I guess.
But I am still interested in the weather. I still feel like Alberniweather is a useful service for people in my community. I still feel a willing obligation to inform people about the weather and I believe I am trusted to do so by the public and local leaders. I’ve never made any money at it, I sold ad space on the website for a few years but it wasn’t worth the hassle and I didn’t feel comfortable taking the money when I was councillor. I have had some generous spontaneous donations at times.
But mainly I do it because it’s interesting, and I hope it is useful for people especially when people are looking for information during a major event.
The highest traffic I have ever had on Alberniweather pre-FB exit was the local Dog Mountain forest fire in 2015.
post-FB exit: the #underwoodfire
People want easy access to reliable local, trusted, information.
Large media orgs have mostly given up on this.
I am grateful we still have an active local newspaper and radio and that both trust me and I trust them.
@… @…

On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
Tao Guo, Junxiao Wang, Fushuo Huo, Laizhong Cui, Song Guo, Jie Gui, Dacheng Tao
https://arxiv.org/abs/2508.16261

On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
Federated Learning (FL) enables training models across decentralized data silos while preserving client data privacy. Recent research has explored efficient methods for post-training large language models (LLMs) within FL to address computational and communication challenges. While existing approaches often rely on access to LLMs' internal information, which is frequently restricted in real-world scenarios, an inference-only paradigm (black-box FedLLM) has emerged to address these limitations. …

Shifting Narratives: A Longitudinal Analysis of Media Trends and Public Attitudes on Homelessness
Akshay Irudayaraj (Brown University), Nathan Ye (University of California--Berkeley), Yash Chainani (University of California--Berkeley)
https://arxiv.org/abs/2506.21794

Shifting Narratives: A Longitudinal Analysis of Media Trends and Public Attitudes on Homelessness
Within the field of media framing, homelessness has been a historically under-researched topic. Framing theory states that the media's method of presenting information plays a pivotal role in controlling public sentiment toward a topic. The sentiment held towards homeless individuals influences their ability to access jobs, housing, and resources as a result of discrimination. This study analyzes the topic and sentiment trends in related media articles to validate framing theory within the scop…

The IRMA Dataset: A Structured Audio-MIDI Corpus for Iranian Classical Music
Sepideh Shafiei, Shapour Hakam
https://arxiv.org/abs/2508.19876 https://arxiv.…

The IRMA Dataset: A Structured Audio-MIDI Corpus for Iranian Classical Music
We present the IRMA Dataset (Iranian Radif MIDI Audio), a multi-level, open-access corpus designed for the computational study of Iranian classical music, with a particular emphasis on the radif, a structured repertoire of modal-melodic units central to pedagogy and performance. The dataset combines symbolic MIDI representations, phrase-level audio-MIDI alignment, musicological transcriptions in PDF format, and comparative tables of theoretical information curated from a range of performers and…

Probing graph topology from local quantum measurements
F. Romeo, J. Settino
https://arxiv.org/abs/2507.23689 https://arxiv.org/pdf/2507.23689

Probing graph topology from local quantum measurements
We show that global properties of an unknown quantum network, such as the average degree, hub density, and the number of closed paths of fixed length, can be inferred from strictly local quantum measurements. In particular, we demonstrate that a malicious agent with access to only a small subset of nodes can initialize quantum states locally and, through repeated short-time measurements, extract sensitive structural information about the entire network. The intrusion strategy is inspired by ext…

Isto é interessante. Relatório sobre educação nos países da OCDE.
https://www.oecd.org/en/publications/education-at-a-glance-2024_c00cad36-en.html

Broadband Modelling of GRB 230812B Afterglow: Implications for VHE $\gamma$-ray Detection with IACTs
Shraddha Mohnani, Biswajit Banerjee, Davide Miceli, Lara Nava, Gor Oganesyan, Pawan Tiwari, Annarita Ierardi, Alessio L. De Santis, Samanta Macera, Amit Shukla, Marica Branchesi, Swarna Chatterjee, Sushmita Agarwal, Abhirup Datta, Kuldeep Kumar Yadav, G. C. Anupama

Broadband Modelling of GRB 230812B Afterglow: Implications for VHE $γ$-ray Detection with IACTs
A significant fraction of the energy from the $γ$-ray burst (GRB) jets, after powering the keV-MeV emission, forms an ultra-relativistic shock propagating into the circumburst medium. The particles in the medium accelerate through the shock and produce afterglow emission. Recently, a few GRB afterglows have been observed in TeV $γ$-rays by Cherenkov Telescopes. This provides access to broadband spectra of GRB afterglows containing rich information about the microphysics of relativistic shocks…

Proton launches Lumo, an AI chatbot to summarize documents, generate code, and more and says it will protect users' information via "zero-access" encryption (Emma Roth/The Verge)
https://www.theverge.com/news/711860/proton-privacy-focused-ai-chatbot

Proton is launching a privacy-focused AI chatbot
Proton is launching a privacy-focused AI chatbot called Lumo. The chatbot can perform a range of tasks while encrypting chats and keeping them off Proton’s servers. 

Price of Uncertainty for Consensus Games
Yunzhe Bai, Alec Sun
https://arxiv.org/abs/2508.17557 https://arxiv.org/pdf/2508.17557

Price of Uncertainty for Consensus Games
Many game-theoretic models assume that players have access to accurate information, but uncertainty in observed data is frequently present in real-world settings. In this paper, we consider a model of uncertainty where adversarial perturbations of relative magnitude $1+\varepsilon$ are introduced to players' observed costs. The effect of uncertainty on social cost is denoted as the price of uncertainty. We prove a tight bound on the price of uncertainty for consensus games of $Θ(\varepsilon^2 …

Analysis of Semantic Communication for Logic-based Hypothesis Deduction
Ahmet Faruk Saz, Siheng Xiong, Faramarz Fekri
https://arxiv.org/abs/2508.21755 https://

Analysis of Semantic Communication for Logic-based Hypothesis Deduction
This work presents an analysis of semantic communication in the context of First-Order Logic (FOL)-based deduction. Specifically, the receiver holds a set of hypotheses about the State of the World (SotW), while the transmitter has incomplete evidence about the true SotW but lacks access to the ground truth. The transmitter aims to communicate limited information to help the receiver identify the hypothesis most consistent with true SotW. We formulate the objective as approximating the posterio…

Replaced article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis
Rafi Al Attrach, Pedro Moreira, Rajna Fani, Renato Umeton, Leo Anthony Celi

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

Bill Atkinson, Macintosh Pioneer and Inventor of Hypercard, Dies at 74
Atkinson’s gleeful brilliance helped people draw on computer screens and access information via links.
https://www.wired.com/story/bill-atkinson-apple-engineer-dies/

Bill Atkinson, Macintosh Pioneer and Inventor of Hypercard, Dies at 74
Atkinson’s gleeful brilliance helped people draw on computer screens and access information via links.

MMSearch-R1: Incentivizing LMMs to Search
Jinming Wu, Zihao Deng, Wei Li, Yiding Liu, Bo You, Bo Li, Zejun Ma, Ziwei Liu
https://arxiv.org/abs/2506.20670 h…

MMSearch-R1: Incentivizing LMMs to Search
Robust deployment of large multimodal models (LMMs) in real-world scenarios requires access to external knowledge sources, given the complexity and dynamic nature of real-world information. Existing approaches such as retrieval-augmented generation (RAG) and prompt engineered search agents rely on rigid pipelines, often leading to inefficient or excessive search behaviors. We present MMSearch-R1, the first end-to-end reinforcement learning framework that enables LMMs to perform on-demand, multi…

Location Information Sharing Using Software Defined Radio in Multi-UAV Systems
Mehmet Kaan Erol, Eyup Emre Ulku
https://arxiv.org/abs/2506.17678 https://…

Location Information Sharing Using Software Defined Radio in Multi-UAV Systems
SDR (Software Defined Radio) provides flexible, reproducible, and longer-lasting radio tools for military and civilian wireless communications infrastructure. SDR is a radio communication system whose components are implemented as software. This study aims to establish multi-channel wireless communication with FANET between two SDRs to share location information and examine it in a realistic test environment. We used multi-channel token circulation as a channel access protocol and GNU Radio pla…

Adaptive BSTs for Single-Source and All-to-All Requests: Algorithms and Lower Bounds
Maryam Shiran
https://arxiv.org/abs/2507.20228 https://arxiv.org/pdf/2…

Adaptive BSTs for Single-Source and All-to-All Requests: Algorithms and Lower Bounds
Adaptive binary search trees are a fundamental data structure for organizing hierarchical information. Their ability to dynamically adjust to access patterns makes them particularly valuable for building responsive and efficient networked and distributed systems. We present a unified framework for adaptive binary search trees with fixed restructuring cost, analyzed under two models: the single-source model, where the cost of querying a node is proportional to its distance from a fixed source,…

Wi-Fi Sensing Tool Release: Gathering 802.11ax Channel State Information from a Commercial Wi-Fi Access Point
Zisheng Wang, Feng Li, Hangbin Zhao, Zihuan Mao, Yaodong Zhang, Qisheng Huang, Bo Cao, Mingming Cao, Baolin He, Qilin Hou
https://arxiv.org/abs/2506.16957

Wi-Fi Sensing Tool Release: Gathering 802.11ax Channel State Information from a Commercial Wi-Fi Access Point
Wi-Fi sensing has emerged as a powerful technology, leveraging channel state information (CSI) extracted from wireless data packets to enable diverse applications, ranging from human presence detection to gesture recognition and health monitoring. However, CSI extraction from commercial Wi-Fi access point lacks and out of date. This paper introduces ZTECSITool,a toolkit designed to capture high-resolution CSI measurements from commercial Wi-Fi 6 (802.11ax) access points, supporting bandwidths u…

Consumer Beware! Exploring Data Brokers' CCPA Compliance
Elina van Kempen, Isita Bagayatkar, Pavel Frolikov, Chloe Georgiou, Gene Tsudik
https://arxiv.org/abs/2506.21914

Consumer Beware! Exploring Data Brokers' CCPA Compliance
Data brokers collect and sell the personal information of millions of individuals, often without their knowledge or consent. The California Consumer Privacy Act (CCPA) grants consumers the legal right to request access to, or deletion of, their data. To facilitate these requests, California maintains an official registry of data brokers. However, the extent to which these entities comply with the law is unclear. This paper presents the first large-scale, systematic study of CCPA compliance of…

UK to pay for EU defense fund access amidst growing Russia threat, FT reports: https://benborges.xyz/2025/07/22/uk-to-pay-for-eu.html

Using Tactile Charts to Support Comprehension and Learning of Complex Visualizations for Blind and Low-Vision Individuals
Tingying He, Maggie McCracken, Daniel Hajas, Sarah Creem-Regehr, Alexander Lex
https://arxiv.org/abs/2507.21462

Using Tactile Charts to Support Comprehension and Learning of Complex Visualizations for Blind and Low-Vision Individuals
We investigate whether tactile charts support comprehension and learning of complex visualizations for blind and low-vision (BLV) individuals and contribute four tactile chart designs and an interview study. Visualizations are powerful tools for conveying data, yet BLV individuals typically can rely only on assistive technologies -- primarily alternative texts -- to access this information. Prior research shows the importance of mental models of chart types for interpreting these descriptions, …

The Missing Link: Joint Legal Citation Prediction using Heterogeneous Graph Enrichment
Lorenz Wendlinger, Simon Alexander Nonn, Abdullah Al Zubaer, Michael Granitzer
https://arxiv.org/abs/2506.22165

The Missing Link: Joint Legal Citation Prediction using Heterogeneous Graph Enrichment
Legal systems heavily rely on cross-citations of legal norms as well as previous court decisions. Practitioners, novices and legal AI systems need access to these relevant data to inform appraisals and judgments. We propose a Graph-Neural-Network (GNN) link prediction model that can identify Case-Law and Case-Case citations with high proficiency through fusion of semantic and topological information. We introduce adapted relational graph convolutions operating on an extended and enriched versio…

"Musk and his allies systematically built a false narrative of widespread fraud at the Social Security Administration based on misinterpreted data, using their claims to justify an aggressive effort to gain access to personal information on millions of Americans."
Gift link.

Inside DOGE’s Chaotic Takeover of Social Security
The drama offers a case study in how Elon Musk’s team sought to run a critical government agency through misinformation and social media blasts — and how longtime employees responded.

Harnessing RLHF for Robust Unanswerability Recognition and Trustworthy Response Generation in LLMs
Shuyuan Lin, Lei Duan, Philip Hughes, Yuxuan Sheng
https://arxiv.org/abs/2507.16951

Harnessing RLHF for Robust Unanswerability Recognition and Trustworthy Response Generation in LLMs
Conversational Information Retrieval (CIR) systems, while offering intuitive access to information, face a significant challenge: reliably handling unanswerable questions to prevent the generation of misleading or hallucinated content. Traditional approaches often rely on external classifiers, which can introduce inconsistencies with the core generative Large Language Models (LLMs). This paper introduces Self-Aware LLM for Unanswerability (SALU), a novel approach that deeply integrates unanswer…

Scale AI emphasizes that it remains an independent company and says Meta will not have access to Scale's internal systems or customers' confidential information (Scale AI)
https://scale.com/blog/customer-trust-scale-meta-deal

Scale Remains Independent After Meta Investment | Scale
Customer trust and data security remain Scale’s top priorities.

Privileged Self-Access Matters for Introspection in AI
Siyuan Song, Harvey Lederman, Jennifer Hu, Kyle Mahowald
https://arxiv.org/abs/2508.14802 https://ar…

Privileged Self-Access Matters for Introspection in AI
Whether AI models can introspect is an increasingly important practical question. But there is no consensus on how introspection is to be defined. Beginning from a recently proposed ''lightweight'' definition, we argue instead for a thicker one. According to our proposal, introspection in AI is any process which yields information about internal states through a process more reliable than one with equal or lower computational cost available to a third party. Using experiments where LLMs reason …

Non-spatial symmetries in quantum nonlinear spectroscopy
Li Sun, Chong Chen, Ren-Bao Liu
https://arxiv.org/abs/2508.20445 https://arxiv.org/pdf/2508.20445

Non-spatial symmetries in quantum nonlinear spectroscopy
Nonlinear spectroscopy is a powerful approach to extracting information, in particular higher-order correlations of physical quantities. Quantum nonlinear spectroscopy (QNS) can access exponentially more types of correlations than its classical counterpart, since the responses to ``classical forces'' correspond to contour-time-ordered correlations (CTOCs) that involve only commutators, while in QNS ``quantum forces'' from a quantum sensor induce responses corresponding to CTOCs that involve bot…

Mind the Third Eye! Benchmarking Privacy Awareness in MLLM-powered Smartphone Agents
Zhixin Lin, Jungang Li, Shidong Pan, Yibo Shi, Yue Yao, Dongliang Xu
https://arxiv.org/abs/2508.19493

Mind the Third Eye! Benchmarking Privacy Awareness in MLLM-powered Smartphone Agents
Smartphones bring significant convenience to users but also enable devices to extensively record various types of personal information. Existing smartphone agents powered by Multimodal Large Language Models (MLLMs) have achieved remarkable performance in automating different tasks. However, as the cost, these agents are granted substantial access to sensitive users' personal information during this operation. To gain a thorough understanding of the privacy awareness of these agents, we present …

A security researcher said
flaws in a carmaker’s online dealership portal
exposed the private information
and vehicle data of its customers,
and could have allowed hackers to remotely break into any of its customers’ vehicles.
Eaton Zveare, who works as a security researcher at software delivery company Harness,
told TechCrunch the flaw he discovered
allowed the creation of an admin account
that granted “unfettered access” to the unnamed carma…

Security flaws in a carmaker's web portal let one hacker remotely unlock cars from anywhere | TechCrunch
Security researcher Eaton Zveare told TechCrunch that the flaws he discovered in the carmaker's centralized dealer portal exposed vast access to customer and vehicle data. With this access, Zveare said he could remotely take over a customer's account and unlock their cars, and more.

Of the People, By the Algorithm: How AI Transforms Democratic Representation
Yuval Rymon
https://arxiv.org/abs/2508.19036 https://arxiv.org/pdf/2508.19036

Of the People, By the Algorithm: How AI Transforms Democratic Representation
This review examines how AI technologies are transforming democratic representation, focusing on citizen participation and algorithmic decision-making. The analysis reveals that AI technologies are reshaping democratic processes in fundamental ways: enabling mass-scale deliberation, changing how citizens access and engage with political information, and transforming how representatives make and implement decisions. While AI offers unprecedented opportunities for enhancing democratic participati…

The Random Variables of the DNA Coverage Depth Problem
\c{S}eyma Bodur, Stefano Lia, Hiram H. L\'opez, Rati Ludhani, Alberto Ravagnani, Lisa Seccia
https://arxiv.org/abs/2507.20645

The Random Variables of the DNA Coverage Depth Problem
DNA data storage systems encode digital data into DNA strands, enabling dense and durable storage. Efficient data retrieval depends on coverage depth, a key performance metric. We study the random access coverage depth problem and focus on minimizing the expected number of reads needed to recover information strands encoded via a linear code. We compute the asymptotic performance of a recently proposed code construction, establishing and refining a conjecture in the field by giving two independ…

Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs
Travis Thompson, Seung-Hwan Lim, Paul Liu, Ruoying He, Dongkuan Xu
https://arxiv.org/abs/2506.19967

Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs
Large Language Models (LLMs) have achieved impressive capabilities in language understanding and generation, yet they continue to underperform on knowledge-intensive reasoning tasks due to limited access to structured context and multi-hop information. Retrieval-Augmented Generation (RAG) partially mitigates this by grounding generation in retrieved context, but conventional RAG and GraphRAG methods often fail to capture relational structure across nodes in knowledge graphs. We introduce Infere…

Access Control for Information-Theoretically Secure Key-Document Stores
Yin Li, Sharad Mehrota, Shantanu Sharma, Komal Kumari
https://arxiv.org/abs/2507.10730

Access Control for Information-Theoretically Secure Key-Document Stores
This paper presents a novel key-based access control technique for secure outsourcing key-value stores where values correspond to documents that are indexed and accessed using keys. The proposed approach adopts Shamir's secret-sharing that offers unconditional or information-theoretic security. It supports keyword-based document retrieval while preventing leakage of the data, access rights of users, or the size (\textit{i}.\textit{e}., volume of the output that satisfies a query). The proposed …

SimLab: A Platform for Simulation-based Evaluation of Conversational Information Access Systems
Nolwenn Bernard, Sharath Chandra Etagi Suresh, Krisztian Balog, ChengXiang Zhai
https://arxiv.org/abs/2507.04888

SimLab: A Platform for Simulation-based Evaluation of Conversational Information Access Systems
Research on interactive and conversational information access systems, including search engines, recommender systems, and conversational assistants, has been hindered by the difficulty in evaluating such systems with reproducible experiments. User simulation provides a promising solution, but there is a lack of infrastructure and tooling to support this kind of evaluation. To facilitate simulation-based evaluation of conversational information access systems, we introduce SimLab, the first clou…

Seamless and Efficient Interactions within a Mixed-Dimensional Information Space
Chen Chen
https://arxiv.org/abs/2506.04545 https://a…

Seamless and Efficient Interactions within a Mixed-Dimensional Information Space
Mediated by today's visual displays, information space allows users to discover, access and interact with a wide range of digital and physical information. The information presented in this space may be digital, physical or a blend of both, and appear across different dimensions - such as texts, images, 3D content and physical objects embedded within real-world environment. Navigating within the information space often involves interacting with mixed-dimensional entities, visually represented i…

Slow Fluid Antenna Multiple Access with Multiport Receivers
Jos\'e P. Gonz\'alez-Coma, F. Javier L\'opez-Mart\'inez
https://arxiv.org/abs/2507.17505 https://

Slow Fluid Antenna Multiple Access with Multiport Receivers
We investigate whether equipping fluid-antenna (FA) receivers with multiple ($L>1$) radiofrequency (RF) chains can improve the performance of the slow fluid-antenna multiple access (FAMA) technique, which enables open-loop connectivity with channel state information (CSI) available only at the receiver side. We analyze the case of slow-FAMA users equipped with multiport receivers, so that $L$ ports of the FA are selected and combined to reduce interference. We show that a joint design of the po…

List of the Kremlin’s secret contractors: Russian businesses profiting from the temporarily occupied territories of Ukraine: https://benborges.xyz/2025/07/22/list-of-the-kremlins-secret.html

Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting
Zhuomin Chen, Dan Li, Jiahui Zhou, Shunyu Wu, Haozheng Ye, Jian Lou, See-Kiong Ng
https://arxiv.org/abs/2508.16059

Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting
Time series (TS) data are ubiquitous across various application areas, rendering time series forecasting (TSF) a fundamental task. With the astounding advances in large language models (LLMs), a variety of methods have been developed to adapt LLMs for time series forecasting. Despite unlocking the potential of LLMs in comprehending TS data, existing methods are inherently constrained by their shallow integration of TS information, wherein LLMs typically access TS representations at shallow laye…

Rethinking Multi-User Communication in Semantic Domain: Enhanced OMDMA by Shuffle-Based Orthogonalization and Diffusion Denoising
Maojun Zhang, Guangxu Zhu, Xiaoming Chen, Kaibin Huang, Zhaoyang Zhang
https://arxiv.org/abs/2507.20477

Rethinking Multi-User Communication in Semantic Domain: Enhanced OMDMA by Shuffle-Based Orthogonalization and Diffusion Denoising
Inter-user interference remains a critical bottleneck in wireless communication systems, particularly in the emerging paradigm of semantic communication (SemCom). Compared to traditional systems, inter-user interference in SemCom severely degrades key semantic information, often causing worse performance than Gaussian noise under the same power level. To address this challenge, inspired by the recently proposed concept of Orthogonal Model Division Multiple Access (OMDMA) that leverages semantic…

The US supreme court on Friday permitted DOGE, the so-called ‘department of government efficiency’, broad access to personal information on millions of Americans in Social Security Administration data systems while a legal challenge plays out.
At the request of the Justice Department, the justices put on hold US district judge Ellen Hollander’s order that had largely blocked Doge’s access to “personally identifiable information”
in data such as medical and financial records while …

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics
Meysam Alizadeh, Fabrizio Gilardi, Zeynab Samei, Mohsen Mosleh
https://arxiv.org/abs/2507.12372

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics
Large language models (LLMs) have traditionally relied on static training data, limiting their knowledge to fixed snapshots. Recent advancements, however, have equipped LLMs with web browsing capabilities, enabling real time information retrieval and multi step reasoning over live web content. While prior studies have demonstrated LLMs ability to access and analyze websites, their capacity to directly retrieve and analyze social media data remains unexplored. Here, we evaluate whether web brows…

The Democratic Paradox in Large Language Models' Underestimation of Press Freedom
I. Loaiza, R. Vestrelli, A. Fronzetti Colladon, R. Rigobon
https://arxiv.org/abs/2506.18045

The Democratic Paradox in Large Language Models' Underestimation of Press Freedom
As Large Language Models (LLMs) increasingly mediate global information access for millions of users worldwide, their alignment and biases have the potential to shape public understanding and trust in fundamental democratic institutions, such as press freedom. In this study, we uncover three systematic distortions in the way six popular LLMs evaluate press freedom in 180 countries compared to expert assessments of the World Press Freedom Index (WPFI). The six LLMs exhibit a negative misalignmen…

Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting
Zhuomin Chen, Dan Li, Jiahui Zhou, Shunyu Wu, Haozheng Ye, Jian Lou, See-Kiong Ng
https://arxiv.org/abs/2508.16059

Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting
Time series (TS) data are ubiquitous across various application areas, rendering time series forecasting (TSF) a fundamental task. With the astounding advances in large language models (LLMs), a variety of methods have been developed to adapt LLMs for time series forecasting. Despite unlocking the potential of LLMs in comprehending TS data, existing methods are inherently constrained by their shallow integration of TS information, wherein LLMs typically access TS representations at shallow laye…

RL-Finetuned LLMs for Privacy-Preserving Synthetic Rewriting
Zhan Shi, Yefeng Yuan, Yuhong Liu, Liang Cheng, Yi Fang
https://arxiv.org/abs/2508.19286 https://

RL-Finetuned LLMs for Privacy-Preserving Synthetic Rewriting
The performance of modern machine learning systems depends on access to large, high-quality datasets, often sourced from user-generated content or proprietary, domain-specific corpora. However, these rich datasets inherently contain sensitive personal information, raising significant concerns about privacy, data security, and compliance with regulatory frameworks. While conventional anonymization techniques can remove explicit identifiers, such removal may result in performance drop in downstre…

Efficient Remote Monitoring through Noisy Random Access with Retransmissions
Sergey Foss, Dmitriy Kim, Andrey Turlikov
https://arxiv.org/abs/2507.12368 htt…

Efficient Remote Monitoring through Noisy Random Access with Retransmissions
We consider a rare event monitoring system consisting of a set of devices and a base station, where devices transmit information about rare events to the base station using a random multiple access scheme. We introduce a model in which the presence of noise in the multiple access channel can cause message loss even in the absence of transmission collisions. The occurrence of events is modeled by a family of independent two-state Markov chains (with states 0 and 1). We analyze how repeated trans…

Leveraging Synthetic Data for Question Answering with Multilingual LLMs in the Agricultural Domain
Rishemjit Kaur, Arshdeep Singh Bhankhar, Surangika Ranathunga, Jashanpreet Singh Salh, Sudhir Rajput, Vidhi, Kashish Mahendra, Bhavika Berwal, Ritesh Kumar
https://arxiv.org/abs/2507.16974…

Leveraging Synthetic Data for Question Answering with Multilingual LLMs in the Agricultural Domain
Enabling farmers to access accurate agriculture-related information in their native languages in a timely manner is crucial for the success of the agriculture field. Although large language models (LLMs) can be used to implement Question Answering (QA) systems, simply using publicly available general-purpose LLMs in agriculture typically offer generic advisories, lacking precision in local and multilingual contexts due to insufficient domain-specific training and scarcity of high-quality, regio…

“The Maha report is essentially a distraction from the real causes of poor health,”
said Elizabeth Jacobs, professor emerita at the University of Arizona and a founding member of Defend Public Health.
“This administration does not want to address things like poverty and education and access to healthcare.
Instead, they’re distracting the public with information on solutions to problems that don’t actually exist.
When the foundation of your policy is not evidence-based…

Non-Asymptotic Achievable Rate-Distortion Region for Indirect Wyner-Ziv Source Coding
Jiahui Wei, Philippe Mary, Elsa Dupraz
https://arxiv.org/abs/2507.17432 https://

Non-Asymptotic Achievable Rate-Distortion Region for Indirect Wyner-Ziv Source Coding
In the Wyner-Ziv source coding problem, a source $X$ has to be encoded while the decoder has access to side information $Y$. This paper investigates the indirect setup, in which a latent source $S$, unobserved by both the encoder and the decoder, must also be reconstructed at the decoder. This scenario is increasingly relevant in the context of goal-oriented communications, where $S$ can represent semantic information obtained from $X$. This paper derives the indirect Wyner-Ziv rate-distortion …

Cross-Modal Distillation For Widely Differing Modalities
Cairong Zhao, Yufeng Jin, Zifan Song, Haonan Chen, Duoqian Miao, Guosheng Hu
https://arxiv.org/abs/2507.16296

Cross-Modal Distillation For Widely Differing Modalities
Deep learning achieved great progress recently, however, it is not easy or efficient to further improve its performance by increasing the size of the model. Multi-modal learning can mitigate this challenge by introducing richer and more discriminative information as input. To solve the problem of limited access to multi-modal data at the time of use, we conduct multi-modal learning by introducing a teacher model to transfer discriminative knowledge to a student model during training. However, t…

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward
Yong Deng, Guoqing Wang, Zhenzhe Ying, Xiaofeng Wu, Jinzhen Lin, Wenwen Xiong, Yuqin Dai, Shuo Yang, Zhanwei Zhang, Qiwen Wang, Yang Qin, Changhua Meng
https://arxiv.org/abs/2508.12800

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward
Large language models (LLMs) exhibit remarkable problem-solving abilities, but struggle with complex tasks due to static internal knowledge. Retrieval-Augmented Generation (RAG) enhances access to external information, yet remains limited in multi-hop reasoning and strategic search due to rigid workflows. Recent advancements in agentic deep research empower LLMs to autonomously reason, search, and synthesize information. However, current approaches relying on outcome-based reinforcement learnin…

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…

Lightweight Electronic Signatures and Reliable Access Control Included in Sensor Networks to Prevent Cyber Attacks from Modifying Patient Data
Mishall Al-Zubaidie
https://arxiv.org/abs/2506.08828

Lightweight Electronic Signatures and Reliable Access Control Included in Sensor Networks to Prevent Cyber Attacks from Modifying Patient Data
Digital terrorism is a major cause of securing patient/healthcare providers data and information. Sensitive topics that may have an impact on a patient's health or even national security include patient health records and information on healthcare providers. Health databases and data sets have been continually breached by many, regular assaults, as well as local and remote servers equipped with wireless sensor networks (WSNs) in diverse locations. The problem was addressed by some contemporary …

AI/ML Life Cycle Management for Interoperable AI Native RAN
Chu-Hsiang Huang, Chao-Kai Wen, Geoffrey Ye Li
https://arxiv.org/abs/2507.18538 https://arxiv.o…

AI/ML Life Cycle Management for Interoperable AI Native RAN
Artificial intelligence (AI) and machine learning (ML) models are rapidly permeating the 5G Radio Access Network (RAN), powering beam management, channel state information (CSI) feedback, positioning, and mobility prediction. However, without a standardized life-cycle management (LCM) framework, challenges, such as model drift, vendor lock-in, and limited transparency, hinder large-scale adoption. 3GPP Releases 16-20 progressively evolve AI/ML from experimental features to managed, interoperabl…

Minimax Data Sanitization with Distortion Constraint and Adversarial Inference
Amirarsalan Moatazedian, Yauhen Yakimenka, R\'emi A. Chou, J\"org Kliewer
https://arxiv.org/abs/2507.17942

Minimax Data Sanitization with Distortion Constraint and Adversarial Inference
We study a privacy-preserving data-sharing setting where a privatizer transforms private data into a sanitized version observed by an authorized reconstructor and two unauthorized adversaries, each with access to side information correlated with the private data. The reconstructor is evaluated under a distortion function, while each adversary is evaluated using a separate loss function. The privatizer ensures the reconstructor distortion remains below a fixed threshold while maximizing the mi…

Communication Complexity of Exact Sampling under R\'enyi Information
Spencer Hill, Fady Alajaji, Tam\'as Linder
https://arxiv.org/abs/2506.12219 ht…

Communication Complexity of Exact Sampling under Rényi Information
We study the problem of communicating a sample from a probability distribution $P$ given shared access to a sequence distributed according to another probability distribution $Q$. Li and El Gamal used the Poisson functional representation to show that the minimum expected message length to communicate a sample from $P$ can be upper bounded by $D(P||Q) + \log (D(P||Q) + 1) + 4$, where $D(\, \cdot \, || \, \cdot\, )$ is the Kullback-Leibler divergence. We generalize …