Tootfinder

Denmark, Sweden back funding US weapons for Ukraine: https://benborges.xyz/2025/07/15/denmark-sweden-back-funding-us.html

So Bitvise, the developer of an SSH client that competes with PuTTY, the widely-used open-source SSH and Telnet client, somehow got hold of the domain putty.org and is using it to promote its own products.
Here's how Bitvise responded to a tech blogger/journalist who wrote about this situation.
https://blog.pupred.…

Today a nice german word: "Birkenknopfhornblattwespe"
Latin name is Cimbex femoratus and it is very colorful as a robin 🐛
#insekten

France warns of war in 'heart of Europe,' names Russia 'most direct threat': https://benborges.xyz/2025/07/15/france-warns-of-war-in.html

Can We Trust Machine Learning? The Reliability of Features from Open-Source Speech Analysis Tools for Speech Modeling
Tahiya Chowdhury, Veronica Romero
https://arxiv.org/abs/2506.11072

Can We Trust Machine Learning? The Reliability of Features from Open-Source Speech Analysis Tools for Speech Modeling
Machine learning-based behavioral models rely on features extracted from audio-visual recordings. The recordings are processed using open-source tools to extract speech features for classification models. These tools often lack validation to ensure reliability in capturing behaviorally relevant information. This gap raises concerns about reproducibility and fairness across diverse populations and contexts. Speech processing tools, when used outside of their design context, can fail to capture b…

Information-Theoretic Detection of Unusual Source Code Changes
Adriano Torres, Sebastian Baltes, Christoph Treude, Markus Wagner
https://arxiv.org/abs/2506.06508

Information-Theoretic Detection of Unusual Source Code Changes
The code base of software projects evolves essentially through inserting and removing information to and from the source code. We can measure this evolution via the elements of information - tokens, words, nodes - of the respective representation of the code. In this work, we approach the measurement of the information content of the source code of open-source projects from an information-theoretic standpoint. Our focus is on the entropy of two fundamental representations of code: tokens and ab…

Unifying Chemical and Electrochemical Thermodynamics of Electrodes
Archie Mingze Yao, Amal Sebastian, Venkatasubramaian Viswanathan
https://arxiv.org/abs/2507.10677

Unifying Chemical and Electrochemical Thermodynamics of Electrodes
Batteries are critical for electrified transportation and aviation, yet thermodynamic understanding of electrode materials remains lacking, as indicated by the often-seen violation of the second law of thermodynamics of open-circuit voltage (OCV) models. On the other hand, thermodynamic modeling rarely utilizes electrochemical data such as OCV, entropic heat (dOCV/dT), which contains rich thermodynamic information. This work introduces a framework of thermodynamic modeling of materials for elec…

Path Integral Formalism for Quantum Open Systems
Ruofan Chen
https://arxiv.org/abs/2506.08802 https://arxiv.org/pdf/2506.08802…

Path Integral Formalism for Quantum Open Systems
This article provides a detailed derivation of the path integral formalism for both boson and fermion quantum open systems using coherent states. The formalism on the imaginary-time axis, Keldysh contour, and Kadanoff contour are given. The corresponding generating functional technique, which can be used to retrieve the environment information from the system correlation function, is also discussed.

The latest executive order from Trump administration removed the following sentence from a previous executive order.
" e) Open source software plays a critical role in Federal information systems."
🔗 https://www…

Sustaining Select Efforts to Strengthen the Nation's Cybersecurity and Amending Executive Order 13694 and Executive Order 14144
By the authority vested in me as President by the Constitution and the laws of the United States of America, including the International Emergency

At @oapenbooks.bsky.social, we have updated our #Metadata feeds, to better integrate our #OpenAccess #books into #libraries

A book is a book in any other markup language
Updating the OAPEN Library’s metadata feeds  Since the launch of the OAPEN Library in 2010, the metadata feeds for our collection of open access (OA) books and chapters have always been and will continue to be freely available for anyone to access, download, and use as they need from the OAPEN website.    Metadata is information … Continue reading "A book is a book in any other markup language"

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…

Comparative analysis of privacy-preserving open-source LLMs regarding extraction of diagnostic information from clinical CMR imaging reports
Sina Amirrajab, Volker Vehof, Michael Bietenbeck, Ali Yilmaz
https://arxiv.org/abs/2506.00060

Comparative analysis of privacy-preserving open-source LLMs regarding extraction of diagnostic information from clinical CMR imaging reports
Purpose: We investigated the utilization of privacy-preserving, locally-deployed, open-source Large Language Models (LLMs) to extract diagnostic information from free-text cardiovascular magnetic resonance (CMR) reports. Materials and Methods: We evaluated nine open-source LLMs on their ability to identify diagnoses and classify patients into various cardiac diagnostic categories based on descriptive findings in 109 clinical CMR reports. Performance was quantified using standard classification …

A Robust, Open-Source Framework for Spiking Neural Networks on Low-End FPGAs
Andrew Fan, Simon D. Levy
https://arxiv.org/abs/2507.07284 https://

A Robust, Open-Source Framework for Spiking Neural Networks on Low-End FPGAs
As the demand for compute power in traditional neural networks has increased significantly, spiking neural networks (SNNs) have emerged as a potential solution to increasingly power-hungry neural networks. By operating on 0/1 spikes emitted by neurons instead of arithmetic multiply-and-accumulate operations, SNNs propagate information temporally and spatially, allowing for more efficient compute power. To this end, many architectures for accelerating and simulating SNNs have been developed, inc…

The Pandora's Box Problem with Sequential Inspections
Ali Aouad, Jingwei Ji, Yaron Shaposhnik
https://arxiv.org/abs/2507.07508 https://

The Pandora's Box Problem with Sequential Inspections
The Pandora's box problem (Weitzman 1979) is a core model in economic theory that captures an agent's (Pandora's) search for the best alternative (box). We study an important generalization of the problem where the agent can either fully open boxes for a certain fee to reveal their exact values or partially open them at a reduced cost. This introduces a new tradeoff between information acquisition and cost efficiency. We establish a hardness result and employ an array of techniques in stochasti…

OMAR-RQ: Open Music Audio Representation Model Trained with Multi-Feature Masked Token Prediction
Pablo Alonso-Jim\'enez, Pedro Ramoneda, R. Oguz Araz, Andrea Poltronieri, Dmitry Bogdanov
https://arxiv.org/abs/2507.03482

OMAR-RQ: Open Music Audio Representation Model Trained with Multi-Feature Masked Token Prediction
Developing open-source foundation models is essential for advancing research in music audio understanding and ensuring access to powerful, multipurpose representations for music information retrieval. We present OMAR-RQ, a model trained with self-supervision via masked token classification methodologies using a large-scale dataset with over 330,000 hours of music audio. We experiment with different input features and quantization options, and achieve state-of-the-art performance in music taggin…

Mapping the reddening plane in the Galactic disk through interstellar extinction of open clusters
Yogesh C. Joshi (ARIES)
https://arxiv.org/abs/2506.04460 …

Mapping the reddening plane in the Galactic disk through interstellar extinction of open clusters
As thousands of new open clusters in the Galaxy have recently been reported with reddening or extinction information, we map the distribution and properties of the Galaxy's interstellar material in the Galactic disk as traced by these open clusters. By analyzing the distribution of interstellar extinction for 6215 open clusters located at low Galactic latitude b <= 6 deg, corresponding to the thin Galactic disk, we identify a reddening plane characterized by a dust layer whose thickness varies …

3D Reconstruction and Information Fusion between Dormant and Canopy Seasons in Commercial Orchards Using Deep Learning and Fast GICP
Ranjan Sapkota, Zhichao Meng, Martin Churuvija, Xiaoqiang Du, Zenghong Ma, Manoj Karkee
https://arxiv.org/abs/2507.01912

3D Reconstruction and Information Fusion between Dormant and Canopy Seasons in Commercial Orchards Using Deep Learning and Fast GICP
In orchard automation, dense foliage during the canopy season severely occludes tree structures, minimizing visibility to various canopy parts such as trunks and branches, which limits the ability of a machine vision system. However, canopy structure is more open and visible during the dormant season when trees are defoliated. In this work, we present an information fusion framework that integrates multi-seasonal structural data to support robotic and automated crop load management during the e…

Foundation Model-Aided Deep Reinforcement Learning for RIS-Assisted Wireless Communication
Mohammad Ghassemi, Sara Farrag Mobarak, Han Zhang, Ali Afana, Akram Bin Sediq, Melike Erol-Kantarci
https://arxiv.org/abs/2506.09855

Foundation Model-Aided Deep Reinforcement Learning for RIS-Assisted Wireless Communication
Reconfigurable intelligent surfaces (RIS) have emerged as a promising technology for enhancing wireless communication by dynamically controlling signal propagation in the environment. However, their efficient deployment relies on accurate channel state information (CSI), which leads to high channel estimation overhead due to their passive nature and the large number of reflective elements. In this work, we solve this challenge by proposing a novel framework that leverages a pre-trained open-sou…

The Frequency Response of Networks as Open Systems
Amirhossein Nazerian, Malbor Asllani, Melvyn Tyloo, Wai Lim Ku, Francesco Sorrentino
https://arxiv.org/abs/2507.04180

The Frequency Response of Networks as Open Systems
Many biological, technological, and social systems are effectively networks of interacting individual systems. Typically, these networks are not isolated objects, but interact with their environment through both signals and information that is received by specific nodes with an input function or released to the environment by other nodes with an output function. An important question is whether the structure of different networks, together with the particular selection of input and output nodes…

Spore in the Wild: Case Study on Spore.fun, a Real-World Experiment of Sovereign Agent Open-ended Evolution on Blockchain with TEEs
Botao Amber Hu, Helena Rong
https://arxiv.org/abs/2506.04236

Spore in the Wild: Case Study on Spore.fun, a Real-World Experiment of Sovereign Agent Open-ended Evolution on Blockchain with TEEs
In Artificial Life (ALife) research, replicating Open-Ended Evolution (OEE)-the continuous emergence of novelty observed in biological life-has traditionally been pursued within isolated closed system simulations, such as Tierra and Avida, which have typically plateaued after an initial burst of novelty, failing to achieve sustained OEE. Scholars suggest that OEE requires an "open" system that continually exchanges information or energy with its environment. A recent technological innovation in…

Object Navigation with Structure-Semantic Reasoning-Based Multi-level Map and Multimodal Decision-Making LLM
Chongshang Yan, Jiaxuan He, Delun Li, Yi Yang, Wenjie Song
https://arxiv.org/abs/2506.05896

Object Navigation with Structure-Semantic Reasoning-Based Multi-level Map and Multimodal Decision-Making LLM
The zero-shot object navigation (ZSON) in unknown open-ended environments coupled with semantically novel target often suffers from the significant decline in performance due to the neglect of high-dimensional implicit scene information and the long-range target searching task. To address this, we proposed an active object navigation framework with Environmental Attributes Map (EAM) and MLLM Hierarchical Reasoning module (MHR) to improve its success rate and efficiency. EAM is constructed by re…

This https://arxiv.org/abs/2207.03997 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Tutorial on Event Detection using Social Media Data Analysis: Applications, Challenges, and Open Problems
In recent years, social media has become one of the most popular platforms for communication. These platforms allow users to report real-world incidents that might swiftly and widely circulate throughout the whole social network. A social event is a real-world incident that is documented on social media. Social gatherings could contain vital documentation of crisis scenarios. Monitoring and analyzing this rich content can produce information that is extraordinarily valuable and help people and …

FediWall for the Night of Science on 21 June 2025 in Göttingen!
https://s.academiccloud.de/NtAwrV
During this long summer night, the scientific institutions on Göttingen Campus will offer a program brimming with information and activities. Enjoy open doors of lecture halls, libraries, …

UiS-IAI@LiveRAG: Retrieval-Augmented Information Nugget-Based Generation of Responses
Weronika {\L}ajewska, Ivica Kostric, Gabriel Iturra-Bocaz, Mariam Arustashvili, Krisztian Balog
https://arxiv.org/abs/2506.22210

UiS-IAI@LiveRAG: Retrieval-Augmented Information Nugget-Based Generation of Responses
Retrieval-augmented generation (RAG) faces challenges related to factual correctness, source attribution, and response completeness. The LiveRAG Challenge hosted at SIGIR'25 aims to advance RAG research using a fixed corpus and a shared, open-source LLM. We propose a modular pipeline that operates on information nuggets-minimal, atomic units of relevant information extracted from retrieved documents. This multistage pipeline encompasses query rewriting, passage retrieval and reranking, nugget d…

OAPEN blog: Two Years On: A Conversation with DFG on Supporting #OpenAccess #Books
#ScholComm

Two Years On: A Conversation with DFG on Supporting Open Access Books
It has been two years since OAPEN launched a dedicated collection of DFG-funded open access books. Part of this collection is supported by the DFG Open Access Publication Funding programme. To mark this occasion, OAPEN’s Funder Relations Manager, Laura Bandura-Morgan, interviewed Michael Geuenich, Programme Officer, Scientific Library Services and Information Systems, and Dr. Angela Holzer, … Continue reading "Two Years On: A Conversation with DFG on Supporting Open Access Books"

Information Geometry on the $\ell^2$-Simplex via the $q$-Root Transform
Levin Maier
https://arxiv.org/abs/2506.00485 https://arxiv.or…

Information Geometry on the $\ell^2$-Simplex via the $q$-Root Transform
In this paper, we introduce \emph{$\ell^p$-information geometry}, an infinite dimensional framework that shares key features with the geometry of the space of probability densities \( \mathrm{Dens}(M) \) on a closed manifold, while also incorporating aspects of measure-valued information geometry. We define the \emph{$\ell^2$-probability simplex} with a noncanonical differentiable structure induced via the \emph{$q$-root transform} from an open subset of the $\ell^p$-sphere. This structure rend…

This https://arxiv.org/abs/2302.13500 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Bi-Coupling Method and Applications
By developing a new technique called the bi-coupling argument, we estimate the relative entropy between different diffusion processes in terms of the distances of initial distributions and drift-diffusion coefficients. As an application, the entropy-cost inequality is established for McKean-Vlasov SDEs with spatial-distribution dependent noise, which is open for a long time and has potential applications in optimal transport, information theory and mean field particle systems.

This https://arxiv.org/abs/2308.02636 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Learning from Topology: Cosmological Parameter Estimation from the Large-scale Structure
The topology of the large-scale structure of the universe contains valuable information on the underlying cosmological parameters. While persistent homology can extract this topological information, the optimal method for parameter estimation from the tool remains an open question. To address this, we propose a neural network model to map persistence images to cosmological parameters. Through a parameter recovery test, we demonstrate that our model makes accurate and precise estimates, consider…

This https://arxiv.org/abs/2505.11205 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

IssueCourier: Multi-Relational Heterogeneous Temporal Graph Neural Network for Open-Source Issue Assignment
Issue assignment plays a critical role in open-source software (OSS) maintenance, which involves recommending the most suitable developers to address the reported issues. Given the high volume of issue reports in large-scale projects, manually assigning issues is tedious and costly. Previous studies have proposed automated issue assignment approaches that primarily focus on modeling issue report textual information, developers' expertise, or interactions between issues and developers based on h…

Bah it looks like pubpub are sunsetting https://www.knowledgefutures.org/updates/2025-06-update/

Dnipropetrovsk village likely contested despite Russia's claim of its capture: https://benborges.xyz/2025/07/08/dnipropetrovsk-village-likely-contested-despite.html

Interferometric and Bipartite OTOC for Non-Markovian Open Quantum Spin-Chains and Lipkin-Meshkov-Glick Model
Baibhab Bose, Devvrat Tiwari, Subhashish Banerjee
https://arxiv.org/abs/2506.23796

Interferometric and Bipartite OTOC for Non-Markovian Open Quantum Spin-Chains and Lipkin-Meshkov-Glick Model
The information scrambling phenomena in an open quantum system modeled by Ising spin chains coupled to Lipkin-Meshkov-Glick (LMG) baths are observed via an interferometric method for obtaining out-of-time-ordered correlators ($\mathcal{F}-$OTOC). We also use an anisotropic bath connecting to a system of tilted field Ising spin chain in order to confirm that such situations are suitable for the emergence of ballistic spreading of information manifested in the light cones in the $\mathcal{F}-$OTO…

The new building (the Leinweber Computer Science and Information Building or LCSIB) is open!
This is the view from a 4th floor conference room (lunchroom ha ha) of the Beyster Building.

Evaluating Language Models For Threat Detection in IoT Security Logs
Jorge J. Tejero-Fern\'andez, Alfonso S\'anchez-Maci\'an
https://arxiv.org/abs/2507.02390

Evaluating Language Models For Threat Detection in IoT Security Logs
Log analysis is a relevant research field in cybersecurity as they can provide a source of information for the detection of threats to networks and systems. This paper presents a pipeline to use fine-tuned Large Language Models (LLMs) for anomaly detection and mitigation recommendation using IoT security logs. Utilizing classical machine learning classifiers as a baseline, three open-source LLMs are compared for binary and multiclass anomaly detection, with three strategies: zero-shot, few-shot…

The Quasi-Radial Field-line Tracing (QRaFT): an Adaptive Segmentation of the Open-Flux Solar Corona
Vadim M. Uritsky, Christopher E. Rura, Cooper Downs, Shaela I. Jones, Charles Nickolos Arge, Nathalia Alzate
https://arxiv.org/abs/2506.14894

The Quasi-Radial Field-line Tracing (QRaFT): an Adaptive Segmentation of the Open-Flux Solar Corona
Optical observations of solar corona provide key information on its magnetic geometry. The large-scale open field of the corona plays an important role in shaping the ambient solar wind and constraining the propagation dynamics of the embedded structures, such as interplanetary coronal mass ejections. Rigorous analysis of the open-flux coronal regions based on coronagraph images can be quite challenging because of the depleted plasma density resulting in low signal-to-noise ratios. In this pape…

#Windows11's new #StickyNotes app (a thinly disguised #OneNote) is fucking annoying. Since it is so-called "smart", and it attempts to provide context around the "source" of your note, its window is…

The Sample Complexity of Distributed Simple Binary Hypothesis Testing under Information Constraints
Hadi Kazemi, Ankit Pensia, Varun Jog
https://arxiv.org/abs/2506.13686

The Sample Complexity of Distributed Simple Binary Hypothesis Testing under Information Constraints
This paper resolves two open problems from a recent paper, arXiv:2403.16981, concerning the sample complexity of distributed simple binary hypothesis testing under information constraints. The first open problem asks whether interaction reduces the sample complexity of distributed simple binary hypothesis testing. In this paper, we show that sequential interaction does not help. The second problem suggests tightening existing sample complexity bounds for communication-constrained simple binary …

OK, this seems interesting.
https://delightful.coding.social/delightful-fediverse-experience/

delightful fediverse experience
Delightful curated lists of free software, open science and information sources.

This https://arxiv.org/abs/2408.08208 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendation
Sequential Recommenders generate recommendations based on users' historical interaction sequences. However, in practice, these collected sequences are often contaminated by noisy interactions, which significantly impairs recommendation performance. Accurately identifying such noisy interactions without additional information is particularly challenging due to the absence of explicit supervisory signals indicating noise. Large Language Models (LLMs), equipped with extensive open knowledge and se…

I don't know if it'll be part of the government plan, but one thing that would help people attempting to measure the quality of their food intake might be a statutory requirement for the sellers of packaged food to publish ingredients and nutrition information as open data (with UPCs). This could then be used by apps (such as those using openfoodfacts.org).

Healthy food revolution to tackle obesity epidemic
New healthy food standard will see big businesses promoting healthier food and drink

Correlation Functions and Chaotic Behavior of the SYK Chain Model in Pure States
Seyyed M. H. Halataei
https://arxiv.org/abs/2506.01100 https://

Correlation Functions and Chaotic Behavior of the SYK Chain Model in Pure States
Recent investigations of Rényi entanglement entropy in the SYK chain of Majorana fermions have indicated that the model exhibits slow thermalization when initialized in certain states. The extent to which the heavy modes -- believed to underlie this behavior -- affect other aspects of the model remains an open question. In this work, I study thermalization and scrambling of information in individual energy eigenstates of the SYK chain using exact diagonalization. I show that two-point correlat…

What's in the Box? Reasoning about Unseen Objects from Multimodal Cues
Lance Ying, Daniel Xu, Alicia Zhang, Katherine M. Collins, Max H. Siegel, Joshua B. Tenenbaum
https://arxiv.org/abs/2506.14212

What's in the Box? Reasoning about Unseen Objects from Multimodal Cues
People regularly make inferences about objects in the world that they cannot see by flexibly integrating information from multiple sources: auditory and visual cues, language, and our prior beliefs and knowledge about the scene. How are we able to so flexibly integrate many sources of information to make sense of the world around us, even if we have no direct knowledge? In this work, we propose a neurosymbolic model that uses neural networks to parse open-ended multimodal inputs and then applie…

How to Keep Up With New CSS Features | CSS-Tricks
https://css-tricks.com/how-to-keep-up-with-new-css-features/
Oh, the State of CSS survey is open... And ßmore good sources.

Learning to flock in open space by avoiding collisions and staying together
Martino Brambati, Antonio Celani, Marco Gherardi, Francesco Ginelli
https://arxiv.org/abs/2506.15587

Learning to flock in open space by avoiding collisions and staying together
We investigate the emergence of cohesive flocking in open, boundless space using a multi-agent reinforcement learning framework. Agents integrate positional and orientational information from their closest topological neighbours and learn to balance alignment and attractive interactions by optimizing a local cost function that penalizes both excessive separation and close-range crowding. The resulting Vicsek-like dynamics is robust to algorithmic implementation details and yields cohesive colle…

German lawmakers call on Merz to increase aid to Ukraine, Bild reports: https://benborges.xyz/2025/07/06/german-lawmakers-call-on-merz.html

QISCIT: A validated concept inventory assessment for quantum information science
Kelley Durkin, Manshuo Lin, Michael H. Kolodrubetz, Ryan P. McMahan
https://arxiv.org/abs/2506.17122

QISCIT: A validated concept inventory assessment for quantum information science
Quantum information science (QIS) is a critical interdisciplinary field that requires a well-educated workforce in the near future. Numerous researchers and educators have been actively investigating how to best educate and prepare such a workforce. An open issue has been the lack of a validated tool to asses QIS understanding without requiring college-level math. In this paper, we present the systematic development and content validation of a new assessment instrument called the Quantum Inform…

LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
Fangfu Liu, Hao Li, Jiawei Chi, Hanyang Wang, Minghui Yang, Fudong Wang, Yueqi Duan
https://arxiv.org/abs/2507.02813

LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
Recovering 3D structures with open-vocabulary scene understanding from 2D images is a fundamental but daunting task. Recent developments have achieved this by performing per-scene optimization with embedded language information. However, they heavily rely on the calibrated dense-view reconstruction paradigm, thereby suffering from severe rendering artifacts and implausible semantic synthesis when limited views are available. In this paper, we introduce a novel generative framework, coined LangS…

rd-spiral: An open-source Python library for learning 2D reaction-diffusion dynamics through pseudo-spectral method
Sandy H. S. Herho, Iwan P. Anwar, Rusmawan Suwarman
https://arxiv.org/abs/2506.20633

rd-spiral: An open-source Python library for learning 2D reaction-diffusion dynamics through pseudo-spectral method
We introduce rd-spiral, an open-source Python library for simulating 2D reaction-diffusion systems using pseudo-spectral methods. The framework combines FFT-based spatial discretization with adaptive Dormand-Prince time integration, achieving exponential convergence while maintaining pedagogical clarity. We analyze three dynamical regimes: stable spirals, spatiotemporal chaos, and pattern decay, revealing extreme non-Gaussian statistics (kurtosis $>96$) in stable states. Information-theoretic m…

Forecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models
Stephen J. Lee, Cailinn Drouin
https://arxiv.org/abs/2505.22873

Forecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models
We present a novel framework for high-resolution forecasting of residential heating and electricity demand using probabilistic deep learning models. We focus specifically on providing hourly building-level electricity and heating demand forecasts for the residential sector. Leveraging multimodal building-level information -- including data on building footprint areas, heights, nearby building density, nearby building size, land use patterns, and high-resolution weather data -- and probabilistic…

An Adaptive Estimation Approach based on Fisher Information to Overcome the Challenges of LFP Battery SOC Estimation
Junzhe Shi, Shida Jiang, Shengyu Tao, Jaewong Lee, Manashita Borah, Scott Moura
https://arxiv.org/abs/2507.01173

An Adaptive Estimation Approach based on Fisher Information to Overcome the Challenges of LFP Battery SOC Estimation
Robust and Real-time State of Charge (SOC) estimation is essential for Lithium Iron Phosphate (LFP) batteries, which are widely used in electric vehicles (EVs) and energy storage systems due to safety and longevity. However, the flat Open Circuit Voltage (OCV)-SOC curve makes this task particularly challenging. This challenge is complicated by hysteresis effects, and real-world conditions such as current bias, voltage quantization errors, and temperature that must be considered in the battery m…

We had the pleasure of presenting at FIRST.org 2025, showcasing the Vulnerability-Lookup and GCVE.eu initiatives.
Slides are now available.
#cybersecurity #vulnerability #cve

Information Suppression in Large Language Models: Auditing, Quantifying, and Characterizing Censorship in DeepSeek
Peiran Qiu, Siyi Zhou, Emilio Ferrara
https://arxiv.org/abs/2506.12349

Information Suppression in Large Language Models: Auditing, Quantifying, and Characterizing Censorship in DeepSeek
This study examines information suppression mechanisms in DeepSeek, an open-source large language model (LLM) developed in China. We propose an auditing framework and use it to analyze the model's responses to 646 politically sensitive prompts by comparing its final output with intermediate chain-of-thought (CoT) reasoning. Our audit unveils evidence of semantic-level information suppression in DeepSeek: sensitive content often appears within the model's internal reasoning but is omitted or rep…

Polarization switching on the open surfaces of the wurtzite ferroelectric nitrides: ferroelectric subsystems and electrochemical reactivity
Yongtao Liu, Anton V. Ievlev, Eugene A. Eliseev, Nana Sun, Kazuki Okamoto, Hiroshi Funakubo, Anna N. Morozovska, Sergei Kalinin
https://arxiv.org/abs/2506.14452

Polarization switching on the open surfaces of the wurtzite ferroelectric nitrides: ferroelectric subsystems and electrochemical reactivity
Binary ferroelectric nitrides are promising materials for information technologies and power electronics. However, polarization switching in these materials is highly unusual. From the structural perspective, polarization reversal is associated with the change of the effective polarity at the surfaces and interfaces from N-to-M terminated, suggesting strong coupling between ferroelectric and chemical phenomena. Phenomenologically, macroscopic studies demonstrate the presence of complex time dep…

Multimodal Information Retrieval for Open World with Edit Distance Weak Supervision
KMA Solaiman, Bharat Bhargava
https://arxiv.org/abs/2506.20070 https://…

Multimodal Information Retrieval for Open World with Edit Distance Weak Supervision
Existing multi-media retrieval models either rely on creating a common subspace with modality-specific representation models or require schema mapping among modalities to measure similarities among multi-media data. Our goal is to avoid the annotation overhead incurred from considering retrieval as a supervised classification task and re-use the pretrained encoders in large language models and vision tasks. We propose "FemmIR", a framework to retrieve multimodal results relevant to information …

Ukraine, Denmark sign deal to launch Ukrainian military production on Danish soil: https://benborges.xyz/2025/07/04/ukraine-denmark-sign-deal-to.html

DefElement: an encyclopedia of finite element definitions
Matthew W. Scroggs, Pablo D. Brubeck, Joseph P. Dean, J{\o}rgen S. Dokken, India Marsden
https://arxiv.org/abs/2506.20188

DefElement: an encyclopedia of finite element definitions
DefElement is an online encyclopedia of finite element definitions that was created and is maintained by the authors of this paper. DefElement aims to make information about elements defined in the literature easily available in a standard format. There are a number of open-source finite element libraries available, and it can be difficult to check that an implementation of an element in a library matches the element's definition in the literature or implementation in another library, especiall…

🚀 Kubernetes Meetup in Nuremberg! 🇩🇪
Join us on June 2nd for an evening of tech talks, networking, and community fun at the next CNCF Meetup!
🎤 Speakers:
🔹 Sarah Julia Kriesch – Docker vs Podman and the Universe
🔹 Philip Laine – Spegel: A Stateless OCI Registry Mirror
📍 Location: Coworking-Space Nürnberg
🕕 18:00: Doors open for networking
🕡 18:30: Talks begin
🔗 Sign up here:

An Open Research Dataset of the 1932 Cairo Congress of Arab Music
Baris Bozkurt (College of Interdisciplinary Studies, Zayed University, Dubai, United Arab Emirates)
https://arxiv.org/abs/2506.14503

An Open Research Dataset of the 1932 Cairo Congress of Arab Music
This paper introduces ORD-CC32 , an open research dataset derived from the 1932 Cairo Congress of Arab Music recordings, a historically significant collection representing diverse Arab musical traditions. The dataset includes structured metadata, melodic and rhythmic mode tags (maqam and iqa), manually labeled tonic information, and acoustic features extracted using state-of-the-art pitch detection methods. These resources support computational studies of tuning, temperament, and regional varia…

Quark-Gluon Plasma as a Quantum Channel: Entanglement, Decoherence, and Hadronization
Fidele J. Twagirayezu
https://arxiv.org/abs/2507.02202 https://

Quark-Gluon Plasma as a Quantum Channel: Entanglement, Decoherence, and Hadronization
We propose a quantum information framework to model the quark-gluon plasma (QGP) as a composite quantum channel acting on a multi-qubit or multi-qutrit color-entangled system. The QGP's effects are represented by amplitude damping (jet quenching), $SU(3)$ depolarizing noise (decoherence), and a thermal hadronization channel projecting onto color-singlet states. This construction captures energy loss, decoherence, and confinement dynamics in a unified open quantum system framework. We analyze th…

Collaborative Beamforming for Communication Applications Using a Two-Element Fully-Wireless Open-Loop Coherent Distributed Array
Jason M. Merlo, Jeffrey A. Nanzer
https://arxiv.org/abs/2506.13014

Collaborative Beamforming for Communication Applications Using a Two-Element Fully-Wireless Open-Loop Coherent Distributed Array
In this work we demonstrate a proof of concept of a fully-wireless two-node open-loop coherent distributed communication system and evaluate its performance by transmitting QPSK , 64-, and 256-QAM constellations at a symbol rate of 2 MBd over a 58 m link in an urban environment. The system is implemented in a distributed manner with on-node processing using software-defined radios (SDRs) and wireless internode communication to share coordination information and does not rely on external time or…

Russian officer admits to downing Azerbaijani airliner in reported leak: https://benborges.xyz/2025/07/02/russian-officer-admits-to-downing.html

This https://arxiv.org/abs/2401.13980 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

A Superposition Code-Based Semantic Communication Approach with Quantifiable and Controllable Security
This paper addresses the challenge of achieving security in semantic communication (SemCom) over a wiretap channel, where a legitimate receiver coexists with an eavesdropper experiencing a poorer channel condition. Despite previous efforts to secure SemCom against eavesdroppers, guarantee of approximately zero information leakage remains an open issue. In this work, we propose a secure SemCom approach based on superposition codes, aiming to provide quantifiable and controllable security for dig…

This https://arxiv.org/abs/2411.05559 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum processes as thermodynamic resources: the role of non-Markovianity
Quantum thermodynamics studies how quantum systems and operations may be exploited as sources of work to perform useful thermodynamic tasks. In real-world conditions, the evolution of open quantum systems typically displays memory effects, resulting in a non-Markovian dynamics. The associated information backflow has been observed to provide advantage in certain thermodynamic tasks. However, a general operational connection between non-Markovianity and thermodynamics in the quantum regime has r…

Applying Large Language Models to Issue Classification: Revisiting with Extended Data and New Models
Gabriel Aracena, Kyle Luster, Fabio Santos, Igor Steinmacher, Marco A. Gerosa
https://arxiv.org/abs/2506.00128

Applying Large Language Models to Issue Classification: Revisiting with Extended Data and New Models
Effective prioritization of issue reports in software engineering helps to optimize resource allocation and information recovery. However, manual issue classification is laborious and lacks scalability. As an alternative, many open source software (OSS) projects employ automated processes for this task, yet this method often relies on large datasets for adequate training. Traditionally, machine learning techniques have been used for issue classification. More recently, large language models (LL…

Detectability and Parameter Estimation for Einstein Telescope Configurations with GWJulia
Andrea Begnoni, Stefano Anselmi, Mauro Pieroni, Alessandro Renzi, Angelo Ricciardone
https://arxiv.org/abs/2506.21530

Detectability and Parameter Estimation for Einstein Telescope Configurations with GWJulia
Future gravitational-wave (GW) detectors are expected to detect tens of thousands of compact binary coalescences (CBC) per year, depending also on the final detectors layout. For this reason, it is essential to have a fast, reliable tool for forecasting how different detector layouts will affect parameter estimation for these events. The Fisher Information Matrix (FIM) is a common tool for tackling this problem. In this paper, we present a new open source code GWJulia to perform FIM analysis of…

When LLMs Disagree: Diagnosing Relevance Filtering Bias and Retrieval Divergence in SDG Search
William A. Ingram, Bipasha Banerjee, Edward A. Fox
https://arxiv.org/abs/2507.02139 …

When LLMs Disagree: Diagnosing Relevance Filtering Bias and Retrieval Divergence in SDG Search
Large language models (LLMs) are increasingly used to assign document relevance labels in information retrieval pipelines, especially in domains lacking human-labeled data. However, different models often disagree on borderline cases, raising concerns about how such disagreement affects downstream retrieval. This study examines labeling disagreement between two open-weight LLMs, LLaMA and Qwen, on a corpus of scholarly abstracts related to Sustainable Development Goals (SDGs) 1, 3, and 7. We is…

Optimizing Indoor RIS-Aided Physical-Layer Security: A Codebook-Generation Methodology and Measurement-Based Analysis
Dimitris Kompostiotis, Dimitris Vordonis, Vassilis Paliouras, George C. Alexandropoulos
https://arxiv.org/abs/2506.22082

Optimizing Indoor RIS-Aided Physical-Layer Security: A Codebook-Generation Methodology and Measurement-Based Analysis
Sixth-Generation (6G) wireless networks aim to support innovative Internet-of-Things (IoT) applications that demand faster and more secure data transmission. While higher Open Systems Interconnection (OSI) layers employ measures like encryption and secure protocols to address data security, Physical-Layer Security (PLS) focuses on preventing information leakage to EavesDroppers (EDs) and mitigating the effects of jammers and spoofing attacks. In this context, the emerging technology of Reconfig…

Social Media Reactions to Open Source Promotions: AI-Powered GitHub Projects on Hacker News
Prachnachai Meakpaiboonwattana, Warittha Tarntong, Thai Mekratanavorakul, Chaiyong Ragkhitwetsagul, Pattaraporn Sangaroonsilp, Raula Kula, Morakot Choetkiertikul, Kenichi Matsumoto, Thanwadee Sunetnanta
https://arxiv.org/abs/2506.12643

Social Media Reactions to Open Source Promotions: AI-Powered GitHub Projects on Hacker News
Social media platforms have become more influential than traditional news sources, shaping public discourse and accelerating the spread of information. With the rapid advancement of artificial intelligence (AI), open-source software (OSS) projects can leverage these platforms to gain visibility and attract contributors. In this study, we investigate the relationship between Hacker News, a social news site focused on computer science and entrepreneurship, and the extent to which it influences de…

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…

Semidefinite Programming for the Asymmetric Stochastic Block Model
Julia Gaudio, Phawin Prongpaophan
https://arxiv.org/abs/2506.18754 https://

Semidefinite Programming for the Asymmetric Stochastic Block Model
We consider semidefinite programming (SDP) for the binary stochastic block model with equal-sized communities. Prior work of Hajek, Wu, and Xu proposed an SDP (sym-SDP) for the symmetric case where the intra-community edge probabilities are equal, and showed that the SDP achieves the information-theoretic threshold for exact recovery under the symmetry assumption. A key open question is whether SDPs can be used to achieve exact recovery for non-symmetric block models. In order to inform the des…

Context-Aware Scientific Knowledge Extraction on Linked Open Data using Large Language Models
Sajratul Y. Rubaiat, Hasan M. Jamil
https://arxiv.org/abs/2506.17580

Context-Aware Scientific Knowledge Extraction on Linked Open Data using Large Language Models
The exponential growth of scientific literature challenges researchers extracting and synthesizing knowledge. Traditional search engines return many sources without direct, detailed answers, while general-purpose LLMs may offer concise responses that lack depth or omit current information. LLMs with search capabilities are also limited by context window, yielding short, incomplete answers. This paper introduces WISE (Workflow for Intelligent Scientific Knowledge Extraction), a system addressing…

This https://arxiv.org/abs/2505.19253 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

DeepResearchGym: A Free, Transparent, and Reproducible Evaluation Sandbox for Deep Research
Deep research systems represent an emerging class of agentic information retrieval methods that generate comprehensive and well-supported reports to complex queries. However, most existing frameworks rely on dynamic commercial search APIs, which pose reproducibility and transparency challenges in addition to their cost. To address these limitations, we introduce DeepResearchGym, an open-source sandbox that combines a reproducible search API with a rigorous evaluation protocol for benchmarking d…

A GenAI System for Improved FAIR Independent Biological Database Integration
Syed N. Sakib, Kallol Naha, Sajratul Y. Rubaiat, Hasan M. Jamil
https://arxiv.org/abs/2506.17934

A GenAI System for Improved FAIR Independent Biological Database Integration
Life sciences research increasingly requires identifying, accessing, and effectively processing data from an ever-evolving array of information sources on the Linked Open Data (LOD) network. This dynamic landscape places a significant burden on researchers, as the quality of query responses depends heavily on the selection and semantic integration of data sources --processes that are often labor-intensive, error-prone, and costly. While the adoption of FAIR (Findable, Accessible, Interoperable,…