Tootfinder

Drinking water shortage looming in the Netherlands. Not the climate change impact you'd expect in this wet place, with growing annual precipitation under climate change.
But periods of drought make more resources necessary, and provinces fail to organize it, due to pollution and competing use.

from my link log —
How to write mathematics. (1973)
https://sites.math.washington.edu/~lind/Resources/Halmos.pdf
saved 2025-02-22

Hateful man, that Pete. Too stupid to know it's bad luck to just rename a boat without the ceremony [Renaming a Boat https://www.discoverboating.com/resources/ceremony-for-renaming-your-boat]
Pete Hegseth orders Navy to remove Harvey Milk's name from ship during Pride Month - LGBTQ Nation
https://www.lgbtqnation.com/2025/06/pete-hegseth-orders-navy-to-remove-harvey-milks-name-from-ship-during-pride-month/

Someone in my LinkedIn network posted this, and I have no inkling if it is genuine or sarcasm (see: Poe's Law).
Full text of the post in the image Alt Text.
NOTE: Please do not dogpile this person due to my toot.
#LLMs #WorkerReplacement

A mean field game model with non-local spatial interactions and resources accumulation
Daria Ghilli, Fausto Gozzi, Cristiano Ricci, Giovanni Zanco
https://arxiv.org/abs/2506.01200

A mean field game model with non-local spatial interactions and resources accumulation
We study a family of Mean Field Games arising in modeling the behavior of strategic economic agents which move across space maximizing their utility from consumption and have the possibility to accumulate resources for production (such as human capital). The resulting mean field game PDE system is not covered in the actual literature on the topic as it displays weaker assumptions on the regularity of the data (in particular Lipschitz continuity and boundedness of the objective are lost), state …

Current view of the Madre fire from the California Valley camera.
Numerous aerial resources continue to work the fire, with additional still en route, including a 2nd VLAT (very large air tanker) which is en route from Washington State
https://share.watchduty.org/i/53616/re

Watch Duty - Wildfire Maps & Alerts
Real-time information about wildfire and firefighting efforts nearby

How do Pre-Trained Models Support Software Engineering? An Empirical Study in Hugging Face
Alexandra Gonz\'alez, Xavier Franch, David Lo, Silverio Mart\'inez-Fern\'andez
https://arxiv.org/abs/2506.03013

How do Pre-Trained Models Support Software Engineering? An Empirical Study in Hugging Face
Open-Source Pre-Trained Models (PTMs) provide extensive resources for various Machine Learning (ML) tasks, yet these resources lack a classification tailored to Software Engineering (SE) needs. To address this gap, we derive a taxonomy encompassing 147 SE tasks and apply an SE-oriented classification to PTMs in a popular open-source ML repository, Hugging Face (HF). Our repository mining study began with a systematically gathered database of PTMs from the HF API, considering their model card de…

Sparse Imagination for Efficient Visual World Model Planning
Junha Chun, Youngjoon Jeong, Taesup Kim
https://arxiv.org/abs/2506.01392 https://

Sparse Imagination for Efficient Visual World Model Planning
World model based planning has significantly improved decision-making in complex environments by enabling agents to simulate future states and make informed choices. However, ensuring the prediction accuracy of world models often demands substantial computational resources, posing a major challenge for real-time applications. This computational burden is particularly restrictive in robotics, where resources are severely constrained. To address this limitation, we propose a Sparse Imagination fo…

Distributedness based scheduling
Paritosh Ranjan, Surajit Majumder, Prodip Roy, Bhuban Padhan
https://arxiv.org/abs/2506.02581 https://

Distributedness based scheduling
Efficient utilization of computing resources in a Kubernetes cluster is often constrained by the uneven distribution of pods with similar usage patterns. This paper presents a novel scheduling strategy designed to optimize the distributedness of Kubernetes resources based on their usage magnitude and patterns across CPU, memory, network, and storage. By categorizing resource usage into labels such as "cpu high spike" or "memory medium always," and applying these to deployed pods, the system cal…

"#OpenAccess and #Citation #Impact: Modality, Funding, Publisher, and Disciplinary Trends at the University of Kentucky"

Quantum Imaginary-Time Evolution with Polynomial Resources in Time
Lei Zhang, Jizhe Lai, Xian Wu, Xin Wang
https://arxiv.org/abs/2507.00908 https://…

Quantum Imaginary-Time Evolution with Polynomial Resources in Time
Imaginary-time evolution is fundamental to analyzing quantum many-body systems, yet classical simulation requires exponentially growing resources in both system size and evolution time. While quantum approaches reduce the system-size scaling, existing methods rely on heuristic techniques with measurement precision or success probability that deteriorates as evolution time increases. We present a quantum algorithm that prepares normalized imaginary-time evolved states using an adaptive normaliza…

Iranian Cyber Actors May Target Vulnerable US Networks and Entities of Interest (CISA)
https://www.cisa.gov/resources-tools/resources/iranian-cyber-actors-may-target-vulnerable-us-networks-and-entities-interest
http://www.memeorandum.com/250630/p72#a250630p72

This https://arxiv.org/abs/2502.20576 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

OmniRouter: Budget and Performance Controllable Multi-LLM Routing
Large language models (LLMs) deliver superior performance but require substantial computational resources and operate with relatively low efficiency, while smaller models can efficiently handle simpler tasks with fewer resources. LLM routing is a crucial paradigm that dynamically selects the most suitable large language models from a pool of candidates to process diverse inputs, ensuring optimal resource utilization while maintaining response quality. Existing routing frameworks typically model…

Selbst wenn die #Erderwärmung langfristig wieder unter 1,5 °C fällt, bleiben viele #Gletscherverluste unumkehrbar.
Bei einem vorübergehenden Temperaturanstieg auf 3 °C verlieren #Gletscher

Irreversible glacier change and trough water for centuries after overshooting 1.5 °C - Nature Climate Change
How mountain glaciers will react to temporarily overshooting 1.5 °C of warming is poorly understood. Here the authors show irreversible global glacier loss for centuries after overshoot, implying long-term reductions in glacial water resources with amplified impacts in regions where glaciers regrow.

More than 3 million gallons of oil field wastewater, a.k.a. produced water, a.k.a. brine, spilled due to a pipeline leak in northwest #NorthDakota 's Williams County on Monday. It's one of the larger spills recorded in the state. #Bakken

3 million gallon oil field wastewater spill hits Northwest North Dakota
A Continental Resources pipeline leaked over 3 million gallons of produced water in Williams County on Monday,...

Optimal Coordination of Flexible DERs in Local Energy and Flexibility Markets to Ensure Social Equity
Niloofar Pourghaderi, Milad Kabirifar, Payman Dehghanian
https://arxiv.org/abs/2506.02179

Optimal Coordination of Flexible DERs in Local Energy and Flexibility Markets to Ensure Social Equity
Local electricity markets offer a promising solution for integrating renewable energy sources and other distributed energy resources (DERs) into distribution networks. These markets enable the effective utilization of flexible resources by facilitating coordination among various agents. Beyond technical and economic considerations, addressing social equity within these local communities is critical and requires dedicated attention in market-clearing frameworks. This paper proposes a social equi…

"I religiously followed your blog along with the blogs of Jeffrey Zeldman, Dan Cederholm, and Doug Bowman. You were blogging constantly and it was great for people who were getting immersed in web design and code."
https://veerle.duoh.com
@…

Veerle's Blog 4.0 | Graphic & Web Design Articles & Illustrator and…
Hi, I'm Veerle! Explore my design tutorials to gain valuable insights and resources that have shaped my own ( web ) design journey. Discover the…

How to prepare for a 8h train ride: go running.
Now of to Prague to #FlockToFedora; looking forward to meet a lot of old friends there and make new ones.
Ohh, and I give a talk there, too: When and how to use upstream Linux kernels to fix or improve Fedora –

Resources listed for the EU project "Assisting the process of integrating children with impaired vision in school system" https://visionassist.eu/en/resources/

This https://arxiv.org/abs/2505.23337 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Matryoshka Model Learning for Improved Elastic Student Models
Industry-grade ML models are carefully designed to meet rapidly evolving serving constraints, which requires significant resources for model development. In this paper, we propose MatTA, a framework for training multiple accurate Student models using a novel Teacher-TA-Student recipe. TA models are larger versions of the Student models with higher capacity, and thus allow Student models to better relate to the Teacher model and also bring in more domain-specific expertise. Furthermore, multiple…

Balancing Profit and Fairness in Risk-Based Pricing Markets
Jesse Thibodeau, Hadi Nekoei, Afaf Ta\"ik, Janarthanan Rajendran, Golnoosh Farnadi
https://arxiv.org/abs/2506.00140

Balancing Profit and Fairness in Risk-Based Pricing Markets
Dynamic, risk-based pricing can systematically exclude vulnerable consumer groups from essential resources such as health insurance and consumer credit. We show that a regulator can realign private incentives with social objectives through a learned, interpretable tax schedule. First, we provide a formal proposition that bounding each firm's \emph{local} demographic gap implicitly bounds the \emph{global} opt-out disparity, motivating firm-level penalties. Building on this insight we introduce …

Self-Reinforcing Prototype Evolution with Dual-Knowledge Cooperation for Semi-Supervised Lifelong Person Re-Identification
Kunlun Xu, Fan Zhuo, Jiangmeng Li, Xu Zou, Jiahuan Zhou
https://arxiv.org/abs/2507.01884

Self-Reinforcing Prototype Evolution with Dual-Knowledge Cooperation for Semi-Supervised Lifelong Person Re-Identification
Current lifelong person re-identification (LReID) methods predominantly rely on fully labeled data streams. However, in real-world scenarios where annotation resources are limited, a vast amount of unlabeled data coexists with scarce labeled samples, leading to the Semi-Supervised LReID (Semi-LReID) problem where LReID methods suffer severe performance degradation. Existing LReID methods, even when combined with semi-supervised strategies, suffer from limited long-term adaptation performance du…

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

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

Read it in Two Steps: Translating Extremely Low-Resource Languages with Code-Augmented Grammar Books
Chen Zhang, Jiuheng Lin, Xiao Liu, Zekai Zhang, Yansong Feng
https://arxiv.org/abs/2506.01796

Read it in Two Steps: Translating Extremely Low-Resource Languages with Code-Augmented Grammar Books
While large language models (LLMs) have shown promise in translating extremely low-resource languages using resources like dictionaries, the effectiveness of grammar books remains debated. This paper investigates the role of grammar books in translating extremely low-resource languages by decomposing it into two key steps: grammar rule retrieval and application. To facilitate the study, we introduce ZhuangRules, a modularized dataset of grammar rules and their corresponding test sentences. Our …

november17: November17 members (2009)
A network representing connections among members of the November 17 (N17) Greek terrorist group. Nodes are members, and an edge exists if two members have some connection in the past. Metadata include role, function, resources. Some attributes are missing.
This network has 22 nodes and 66 edges.
Tags: Social, Offline, Unweighted, Metadata

This https://arxiv.org/abs/2410.17401 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Foundation model-based agents are increasingly used to automate complex tasks, enhancing efficiency and productivity. However, their access to sensitive resources and autonomous decision-making also introduce significant security risks, where successful attacks could lead to severe consequences. To systematically uncover these vulnerabilities, we propose AdvAgent, a black-box red-teaming framework for attacking web agents. Unlike existing approaches, AdvAgent employs a reinforcement learning-ba…

Who Gets the Kidney? Human-AI Alignment, Indecision, and Moral Values
John P. Dickerson, Hadi Hosseini, Samarth Khanna, Leona Pierce
https://arxiv.org/abs/2506.00079

Who Gets the Kidney? Human-AI Alignment, Indecision, and Moral Values
The rapid integration of Large Language Models (LLMs) in high-stakes decision-making -- such as allocating scarce resources like donor organs -- raises critical questions about their alignment with human moral values. We systematically evaluate the behavior of several prominent LLMs against human preferences in kidney allocation scenarios and show that LLMs: i) exhibit stark deviations from human values in prioritizing various attributes, and ii) in contrast to humans, LLMs rarely express indec…

A Data Science Approach to Calcutta High Court Judgments: An Efficient LLM and RAG-powered Framework for Summarization and Similar Cases Retrieval
Puspendu Banerjee, Aritra Mazumdar, Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
https://arxiv.org/abs/2507.01058

A Data Science Approach to Calcutta High Court Judgments: An Efficient LLM and RAG-powered Framework for Summarization and Similar Cases Retrieval
The judiciary, as one of democracy's three pillars, is dealing with a rising amount of legal issues, needing careful use of judicial resources. This research presents a complex framework that leverages Data Science methodologies, notably Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) techniques, to improve the efficiency of analyzing Calcutta High Court verdicts. Our framework focuses on two key aspects: first, the creation of a robust summarization mechanism that distills…

Flexible Mixed Precision Quantization for Learned Image Compression
Md Adnan Faisal Hossain, Zhihao Duan, Fengqing Zhu
https://arxiv.org/abs/2506.01221 htt…

Flexible Mixed Precision Quantization for Learned Image Compression
Despite its improvements in coding performance compared to traditional codecs, Learned Image Compression (LIC) suffers from large computational costs for storage and deployment. Model quantization offers an effective solution to reduce the computational complexity of LIC models. However, most existing works perform fixed-precision quantization which suffers from sub-optimal utilization of resources due to the varying sensitivity to quantization of different layers of a neural network. In this p…

Degrees of Freedom of Spatial Multiplexing in Distance Domain of Arbitrary Continuous-Aperture Array in Near-Field Region
Son T. Duong, Tho Le-Ngoc
https://arxiv.org/abs/2507.01227

Degrees of Freedom of Spatial Multiplexing in Distance Domain of Arbitrary Continuous-Aperture Array in Near-Field Region
Extremely large aperture array operating in the near-field regime unlocks additional spatial resources that can be exploited to simultaneously serve multiple users even when they share the same angular direction, a capability not achievable in conventional far-field systems. A fundamental question, however, remains: What is the maximum spatial degree of freedom (DoF) of spatial multiplexing in the distance domain? In this paper, we address this open problem by investigating the spatial DoF of…

MobileRAG: A Fast, Memory-Efficient, and Energy-Efficient Method for On-Device RAG
Taehwan Park, Geonho Lee, Min-Soo Kim
https://arxiv.org/abs/2507.01079 h…

MobileRAG: A Fast, Memory-Efficient, and Energy-Efficient Method for On-Device RAG
Retrieval-Augmented Generation (RAG) has proven effective on server infrastructures, but its application on mobile devices is still underexplored due to limited memory and power resources. Existing vector search and RAG solutions largely assume abundant computation resources, making them impractical for on-device scenarios. In this paper, we propose MobileRAG, a fully on-device pipeline that overcomes these limitations by combining a mobile-friendly vector search algorithm, \textit{EcoVector}, …

Minority Representation in Network Rankings: Methods for Estimation, Testing, and Fairness
Hui Shen, Peter W. MacDonald, Eric D. Kolaczyk
https://arxiv.org/abs/2507.01136

Minority Representation in Network Rankings: Methods for Estimation, Testing, and Fairness
Networks, composed of nodes and their connections, are widely used to model complex relationships across various fields. Centrality metrics often inform decisions such as identifying key nodes or prioritizing resources. However, networks frequently suffer from missing or incorrect edges, which can systematically centrality-based decisions and distort the representation of certain protected groups. To address this issue, we introduce a formal definition of minority representation, measured as th…

eduGAIN is expanding across Africa! 🌍
Five new countries: 🇹🇬 Togo, 🇧🇫 Burkina Faso, 🇲🇼 Malawi, 🇬🇭 Ghana, and 🇹🇿 Tanzania have joined, bringing the total on the continent to 14. 🎉
At the heart of this progress is eduID.africa (by UbuntuNet Alliance & WACREN under #AfricaConnect3), and now more researchers and students can now access global services with one trusted identity.

Five new African members join eduGAIN! | GÉANT CONNECT Online
Today, online services are crucial for research and education. These can be for e-learning, teaching and conferencing, scientific collaboration, analysing and sharing data, accessing journals and libraries. Access to these resources is usually controlled with a user name and password. As the number and variety of services expand, often being delivered by service providers outside

A Reinforcement Learning-Based Telematic Routing Protocol for the Internet of Underwater Things
Mohammadhossein Homaei, Mehran Tarif, Agustin Di Bartolo, Oscar Mogollon Gutierrez, Mar Avila
https://arxiv.org/abs/2506.00133

A Reinforcement Learning-Based Telematic Routing Protocol for the Internet of Underwater Things
The Internet of Underwater Things (IoUT) faces major challenges such as low bandwidth, high latency, mobility, and limited energy resources. Traditional routing protocols like RPL, which were designed for land-based networks, do not perform well in these underwater conditions. This paper introduces RL-RPL-UA, a new routing protocol that uses reinforcement learning to improve performance in underwater environments. Each node includes a lightweight RL agent that selects the best parent node based…

Ich bin kein #Prepper, jedenfalls bisher nicht. Aber diesen Ansatz zu sanftem #Preppen finde ich in Zeiten der tiefen Umbrüche bedenkenswert:
#SanftesPreppen
"Es ist Preppen, aber n…

Gentle Prepperism: A Roundup of Resources + Tips for Navigating the Next Era
In a world that feels increasingly uncertain, it’s easy to ping-pong between panic and paralysis. But there’s another way: Gentle Prepperism.

"In Empire of #AI, journalist Karen Hao writes about the rise of #OpenAI and the impacts of AI around the world. Below is an extract from the book on the effects on Chile's mineral reserves and water resources."

Voyager: Real-Time Splatting City-Scale 3D Gaussians on Your Phone
Zheng Liu, He Zhu, Xinyang Li, Yirun Wang, Yujiao Shi, Wei Li, Jingwen Leng, Minyi Guo, Yu Feng
https://arxiv.org/abs/2506.02774

Voyager: Real-Time Splatting City-Scale 3D Gaussians on Your Phone
3D Gaussian Splatting (3DGS) is an emerging technique for photorealistic 3D scene rendering. However, rendering city-scale 3DGS scenes on mobile devices, e.g., your smartphones, remains a significant challenge due to the limited resources on mobile devices. A natural solution is to offload computation to the cloud; however, naively streaming rendered frames from the cloud to the client introduces high latency and requires bandwidth far beyond the capacity of current wireless networks. In this…

Frugal Machine Learning for Energy-efficient, and Resource-aware Artificial Intelligence
John Violos, Konstantina-Christina Diamanti, Ioannis Kompatsiaris, Symeon Papadopoulos
https://arxiv.org/abs/2506.01869

Frugal Machine Learning for Energy-efficient, and Resource-aware Artificial Intelligence
Frugal Machine Learning (FML) refers to the practice of designing Machine Learning (ML) models that are efficient, cost-effective, and mindful of resource constraints. This field aims to achieve acceptable performance while minimizing the use of computational resources, time, energy, and data for both training and inference. FML strategies can be broadly categorized into input frugality, learning process frugality, and model frugality, each focusing on reducing resource consumption at different…

This https://arxiv.org/abs/2502.17701 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMs
Evacuation decision prediction is critical for efficient and effective wildfire response by helping emergency management anticipate traffic congestion and bottlenecks, allocate resources, and minimize negative impacts. Traditional statistical methods for evacuation decision prediction fail to capture the complex and diverse behavioral logic of different individuals. In this work, for the first time, we introduce FLARE, short for facilitating LLM for advanced reasoning on wildfire evacuation dec…

iQUEST: An Iterative Question-Guided Framework for Knowledge Base Question Answering
Shuai Wang, Yinan Yu
https://arxiv.org/abs/2506.01784 https://

iQUEST: An Iterative Question-Guided Framework for Knowledge Base Question Answering
While Large Language Models (LLMs) excel at many natural language processing tasks, they often suffer from factual inaccuracies in knowledge-intensive scenarios. Integrating external knowledge resources, particularly knowledge graphs (KGs), provides a transparent and updatable foundation for more reliable reasoning. Knowledge Base Question Answering (KBQA), which queries and reasons over KGs, is central to this effort, especially for complex, multi-hop queries. However, multi-hop reasoning pose…

An Open and Collaborative Database of Properties of Materials for High-Temperature Superconducting-Based Devices
Pablo Cayado, Jo\~ao Rosas, Jo\~ao Murta-Pina, Harold S. Ruiz
https://arxiv.org/abs/2506.01617

An Open and Collaborative Database of Properties of Materials for High-Temperature Superconducting-Based Devices
The successful integration of high-temperature superconductors (HTS) into modern technologies requires consistent, accessible, and comprehensive material data, a need that is currently unmet due to the fragmented and incomplete nature of existing resources. This paper introduces a new collaborative, open-access database specifically designed to address this gap by providing standardized data on HTS materials and crucial auxiliary components for HTS applications. The database encompasses extensi…

Efficient Resource Allocation under Adversary Attacks: A Decomposition-Based Approach
Mansoor Davoodi, Setareh Maghsudi
https://arxiv.org/abs/2506.23442 ht…

Efficient Resource Allocation under Adversary Attacks: A Decomposition-Based Approach
We address the problem of allocating limited resources in a network under persistent yet statistically unknown adversarial attacks. Each node in the network may be degraded, but not fully disabled, depending on its available defensive resources. The objective is twofold: to minimize total system damage and to reduce cumulative resource allocation and transfer costs over time. We model this challenge as a bi-objective optimization problem and propose a decomposition-based solution that integrate…

Thiel is fully supportive of burning up the Earth & dumping it for Mars.
Put aside the other jackass that wants to "Occupy Mars" & the utter stupidity of leaving Earth...
...who do you think he believes can/should AFFORD to leave earth after he's used all its resources?
https://

Linear Layouts: Robust Code Generation of Efficient Tensor Computation Using $\mathbb{F}_2$
Keren Zhou, Mario Lezcano, Adam Goucher, Akhmed Rakhmati, Jeff Niu, Justin Lebar, Pawel Szczerbuk, Peter Bell, Phil Tillet, Thomas Raoux, Zahi Moudallal
https://arxiv.org/abs/2505.23819

Linear Layouts: Robust Code Generation of Efficient Tensor Computation Using $\mathbb{F}_2$
Efficient tensor computation is a cornerstone of modern deep learning (DL) workloads, yet existing approaches struggle to achieve flexible and performant design and implementation of tensor layouts -- mappings between logical tensors and hardware resources. The increasing complexity of DL algorithms and hardware demands a generic and systematic approach to handling tensor layouts. In this work, we introduce Linear Layouts, a novel approach that models tensor layouts using linear algebra over $\…

OpenAI is expanding its consulting-like service to refine its models and build bespoke apps for large enterprise and government clients spending at least $10M (The Information)
https://www.theinformation.com/articles/openai-takes-page…

OpenAI Takes a Page From Palantir, Doubles Down on Consulting Services
As OpenAI pitches its artificial intelligence to big companies and government agencies, it’s taking a page from the playbook of many software firms by offeringin-house researchers and software engineers to customize AI for customers. OpenAI is adding staff and resources for a consulting-like ...

Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol Ecosystem
Hao Song, Yiming Shen, Wenxuan Luo, Leixin Guo, Ting Chen, Jiashui Wang, Beibei Li, Xiaosong Zhang, Jiachi Chen
https://arxiv.org/abs/2506.02040

Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol Ecosystem
The Model Context Protocol (MCP) is an emerging standard designed to enable seamless interaction between Large Language Model (LLM) applications and external tools or resources. Within a short period, thousands of MCP services have already been developed and deployed. However, the client-server integration architecture inherent in MCP may expand the attack surface against LLM Agent systems, introducing new vulnerabilities that allow attackers to exploit by designing malicious MCP servers. In th…

This https://arxiv.org/abs/2505.01136 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Descriptor: C++ Self-Admitted Technical Debt Dataset (CppSATD)
In software development, technical debt (TD) refers to suboptimal implementation choices made by the developers to meet urgent deadlines and limited resources, posing challenges for future maintenance. Self-Admitted Technical Debt (SATD) is a sub-type of TD, representing specific TD instances ``openly admitted'' by the developers and often expressed through source code comments. Previous research on SATD has focused predominantly on the Java programming language, revealing a significant gap in …

We in Game Workers Unite Ireland stand in solidarity with Animation Workers of Ireland, and the international trade union coalition happening to organise against the threat of AI in the animation industry, and we support their call to acton.
Join them Thursday 12 June at 14:00 at the Pâquier in Annecy!!
#Animation

🚀 Ab sofort können digitale Forschungswerkzeuge für die NFDI4Culture Registry ganz unkompliziert über ein Online-Erfassungsformular vorgeschlagen werden: https://nfdi4culture.de/de/resources/registry/formular.html.
💡 Zielgruppe sind Forschende und Entwickler*innen gleiche…

Navigating the Edge-Cloud Continuum: A State-of-Practice Survey
Loris Belcastro, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio
https://arxiv.org/abs/2506.02003

Navigating the Edge-Cloud Continuum: A State-of-Practice Survey
The edge-cloud continuum has emerged as a transformative paradigm that meets the growing demand for low-latency, scalable, end-to-end service delivery by integrating decentralized edge resources with centralized cloud infrastructures. Driven by the exponential growth of IoT-generated data and the need for real-time responsiveness, this continuum features multi-layered architectures. However, its adoption is hindered by infrastructural challenges, fragmented standards, and limited guidance for d…

Extended-variable probabilistic computing with p-dits
Christian Duffee, Jordan Athas, Andrea Grimaldi, Deborah Volpe, Giovanni Finocchio, Ermin Wei, Pedram Khalili Amiri
https://arxiv.org/abs/2506.00269

Extended-variable probabilistic computing with p-dits
Ising machines can solve combinatorial optimization problems by representing them as energy minimization problems. A common implementation is the probabilistic Ising machine (PIM), which uses probabilistic (p-) bits to represent coupled binary spins. However, many real-world problems have complex data representations that do not map naturally into a binary encoding, leading to a significant increase in hardware resources and time-to-solution. Here, we describe a generalized spin model that supp…

GPTFootprint: Increasing Consumer Awareness of the Environmental Impacts of LLMs
Nora Graves, Vitus Larrieu, Yingyue Trace Zhang, Joanne Peng, Varun Nagaraj Rao, Yuhan Liu, Andr\'es Monroy-Hern\'andez
https://arxiv.org/abs/2505.24107

GPTFootprint: Increasing Consumer Awareness of the Environmental Impacts of LLMs
With the growth of AI, researchers are studying how to mitigate its environmental impact, primarily by proposing policy changes and increasing awareness among developers. However, research on AI end users is limited. Therefore, we introduce GPTFootprint, a browser extension that aims to increase consumer awareness of the significant water and energy consumption of LLMs, and reduce unnecessary LLM usage. GPTFootprint displays a dynamically updating visualization of the resources individual users…

REAP-T: A MATLAB Toolbox for Implementing Robust-to-Early Termination Model Predictive Control
Mohsen Amiri, Mehdi Hosseinzadeh
https://arxiv.org/abs/2507.00863

REAP-T: A MATLAB Toolbox for Implementing Robust-to-Early Termination Model Predictive Control
This paper presents a MATLAB toolbox for implementing robust-to-early termination model predictive control, abbreviated as REAP, which is designed to ensure a sub-optimal yet feasible solution when MPC computations are prematurely terminated due to limited computational resources. Named REAP-T, this toolbox is a comprehensive, user-friendly, and modular platform that enables users to explore, analyze, and customize various components of REAP for their specific applications. Notable attributes o…

FERC’s Christie calls for dispatchable resources after grid operators come ‘close to the edge’ | Utility Dive
https://www.utilitydive.com/news/ferc-christie-dispatchable-resources-heat-wave-pjm-miso-iso-ne/751821/

Labour government running that line between "there's not enough available resources to support immigrants" and "it's critical for the country to have babies that won't be economically productive for many years".
(An apparent dichotomy I imagine there's a non-racist reason for. And to be fair, despite the headlines, they haven't gone full national-natalist, just suggesting making it easier for people to start families.)

Have more children, says Bridget Phillipson
Education Secretary warns Britons of ‘worrying repercussions’ of falling birth rate

Ahead of a vote on Republicans’ budget reconciliation package expected as soon as noon Saturday,
U.S. Senate Committee on Energy and Natural Resources Chair Mike Lee revived his effort to sell off public lands.
Senate Parliamentarian Elizabeth MacDonough has blocked multiple provisions of the GOP megabill,
including several under the jurisdiction of the Utah Republican’s panel.
Among them is his attack on public lands.
“Here we go again,” Sen. Ron Wyden (D-Ore.) …

Mike Lee Tries to Sneak Public Land Sale Back Into 'Big, Ugly Bill' Ahead of Senate Vote | Common Dreams
Ahead of an expected vote on Republicans' budget reconciliation package, U.S. Senate Committee on Energy and Natural Resources Chair Mike Lee revived his effort to sell off public lands.

This https://arxiv.org/abs/2406.15119 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation
Speech emotion recognition (SER) plays a crucial role in human-computer interaction. The emergence of edge devices in the Internet of Things (IoT) presents challenges in constructing intricate deep learning models due to constraints in memory and computational resources. Moreover, emotional speech data often contains private information, raising concerns about privacy leakage during the deployment of SER models. To address these challenges, we propose a data distillation framework to facilitate…

Cross-Modal Characterization of Thin Film MoS$_2$ Using Generative Models
Isaiah A. Moses, Chen Chen, Joan M. Redwing, Wesley F. Reinhart
https://arxiv.org/abs/2505.24065

Cross-Modal Characterization of Thin Film MoS$_2$ Using Generative Models
The growth and characterization of materials using empirical optimization typically requires a significant amount of expert time, experience, and resources. Several complementary characterization methods are routinely performed to determine the quality and properties of a grown sample. Machine learning (ML) can support the conventional approaches by using historical data to guide and provide speed and efficiency to the growth and characterization of materials. Specifically, ML can provide quant…

COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing Among Team of Autonomous LLM Agents
Manish Bhatt, Ronald F. Del Rosario, Vineeth Sai Narajala, Idan Habler
https://arxiv.org/abs/2506.01900

COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing Among Team of Autonomous LLM Agents
The meteoric rise and proliferation of autonomous Large Language Model (LLM) agents promise significant capabilities across various domains. However, their deployment is increasingly constrained by substantial computational demands, specifically for Graphics Processing Unit (GPU) resources. This paper addresses the critical problem of optimizing resource utilization in LLM agent systems. We introduce COALESCE (Cost-Optimized and Secure Agent Labour Exchange via Skill-based Competence Estimation…

This https://arxiv.org/abs/2503.02041 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCE_…

Interpolating Neural Network-Tensor Decomposition (INN-TD): a scalable and interpretable approach for large-scale physics-based problems
Deep learning has been extensively employed as a powerful function approximator for modeling physics-based problems described by partial differential equations (PDEs). Despite their popularity, standard deep learning models often demand prohibitively large computational resources and yield limited accuracy when scaling to large-scale, high-dimensional physical problems. Their black-box nature further hinders the application in industrial problems where interpretability and high precision are cr…

DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation
Jennifer Chen, Aidar Myrzakhan, Yaxin Luo, Hassaan Muhammad Khan, Sondos Mahmoud Bsharat, Zhiqiang Shen
https://arxiv.org/abs/2506.01954

DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation
Retrieval-Augmented Generation (RAG) methods have proven highly effective for tasks requiring factual consistency and robust knowledge retrieval. However, large-scale RAG systems consume significant computational resources and are prone to generating hallucinated content from Humans. In this work, we introduce $\texttt{DRAG}$, a novel framework for distilling RAG knowledge from large-scale Language Models (LLMs) into small LMs (SLMs). Our approach leverages evidence- and knowledge graph-based d…

Awesome #RaspberryPi
https://github.com/thibmaek/awesome-raspberry-pi

Quantized Dissipative Uncertain Model for Fractional T_S Fuzzy systems with Time_Varying Delays Under Networked Control System
Muhammad Shamrooz Aslam, Hazrat Bilal, Sumeera Shamrooz
https://arxiv.org/abs/2506.02788

Quantized Dissipative Uncertain Model for Fractional T_S Fuzzy systems with Time_Varying Delays Under Networked Control System
This paper addressed with the quantized dissipative uncertain problem for delayed fractional T_S Fuzzy system for event_triggered networked systems (E_NS), where the extended dissipativity analysis combines the H infinity, dissipativity, L2 and L infinity and passivity performance in a unified frame. To attain the high efficiency for available channel resources, measurement size decrease mechanism and event_triggered scheme (ETS) are proposed. Firstly, we present the ETS in which signal is tran…

Cyrus : A DRL-based Puncturing Solution to URLLC/eMBB Multiplexing in O-RAN
Ehsan Ghoreishi, Bahman Abolhassani, Yan Huang, Shiva Acharya, Wenjing Lou, Y. Thomas Hou
https://arxiv.org/abs/2506.00167

Cyrus+: A DRL-based Puncturing Solution to URLLC/eMBB Multiplexing in O-RAN
Puncturing is a promising technique in 3GPP to multiplex Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) traffic on the same 5G New Radio (NR) air interface. The essence of puncturing is to transmit URLLC packets on demand upon their arrival, by preempting the radio resources (or subcarriers) that are already allocated to eMBB traffic. Although it is considered most bandwidth efficient, puncturing URLLC data on eMBB can lead to degradation of eMBB's perfor…

DaiFu: In-Situ Crash Recovery for Deep Learning Systems
Zilong He, Pengfei Chen, Hongyu Zhang, Xiaoyun Li, Guangba Yu, Hongyang Chen, Zibin Zheng
https://arxiv.org/abs/2507.01628 …

DaiFu: In-Situ Crash Recovery for Deep Learning Systems
Deep learning (DL) systems have been widely adopted in many areas, and are becoming even more popular with the emergence of large language models. However, due to the complex software stacks involved in their development and execution, crashes are unavoidable and common. Crashes severely waste computing resources and hinder development productivity, so efficient crash recovery is crucial. Existing solutions, such as checkpoint-retry, are too heavyweight for fast recovery from crashes caused by …

Online Selection with Uncertain Disruption
Yihua Xu, S\"uleyman Kerimov, Sebastian Perez-Salazar
https://arxiv.org/abs/2505.22999 https://

Online Selection with Uncertain Disruption
In numerous online selection problems, decision-makers (DMs) must allocate on the fly limited resources to customers with uncertain values. The DM faces the tension between allocating resources to currently observed values and saving them for potentially better, unobserved values in the future. Addressing this tension becomes more demanding if an uncertain disruption occurs while serving customers. Without any disruption, the DM gets access to the capacity information to serve customers through…

Raiders take care of their own by hosting second annual Alumni Wellness Weekend https://www.raiders.com/news/raiders-second-annual-alumni-wellness-weekend-nfl

Behold :) My new #cybersecurity talk is ready and you can see it in the best events around you.
Title: The archetypes of the attackers.
Summary: This talk will lead you on a journey to discover the archetypes of attackers, the tools they use, their motivations for targeting what you've built, and how a geopolitical shift can alter their interest in your resources.

Bogomil Shopov - Бого's Speaker Profile
Human. Artist. Hacker. I care about free and open-source software(F/LOSS), cybersecurity, ethical design, privacy, and technology. 20+ experience in t...

SubMIT: A Physics Analysis Facility at MIT
Josh Bendavid (Massachusetts Institute of Technology, CERN), Mariarosaria D'Alfonso (Massachusetts Institute of Technology), Jan Eysermans (Massachusetts Institute of Technology), Chad Freer (Massachusetts Institute of Technology), Maxim Goncharov (Massachusetts Institute of Technology), Matthew Heine (Massachusetts Institute of Technology), Luca Lavezzo (Massachusetts Institute of Technology), Marianne Moore (Massachusetts Institute of Te…

SubMIT: A Physics Analysis Facility at MIT
The recently completed SubMIT platform is a small set of servers that provide interactive access to substantial data samples at high speeds, enabling sophisticated data analyses with very fast turnaround times. Additionally, it seamlessly integrates massive processing resources for large-scale tasks by connecting to a set of powerful batch processing systems. It serves as an ideal prototype for an Analysis Facility tailored to meet the demanding data and computational requirements anticipated d…

Communication via Sensing
Mohammad Kazemi, Tolga M. Duman, Deniz G\"und\"uz
https://arxiv.org/abs/2506.23000 https://arxiv.…

Communication via Sensing
We present an alternative take on the recently popularized concept of `$\textit{joint sensing and communications}$', which focuses on using communication resources also for sensing. Here, we propose the opposite, where we exploit the sensing capabilities of the receiver for communication. Our goal is to characterize the fundamental limits of communication over such a channel, which we call `$\textit{communication via sensing}$'. We assume that changes in the sensed attributes, e.g., location, s…

This https://arxiv.org/abs/0903.3183 has been replaced.
link: https://scholar.google.com/scholar?q=a

Physics education research: Resources for middle school science teachers
This resource letter intends to provide middle school science teachers with a collection of resources to aid them in planning and implementing a physical science curriculum. The resources are in the form of books, websites, journals, and organizations.

This https://arxiv.org/abs/2505.23436 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Emergent Risk Awareness in Rational Agents under Resource Constraints
Advanced reasoning models with agentic capabilities (AI agents) are deployed to interact with humans and to solve sequential decision-making problems under (approximate) utility functions and internal models. When such problems have resource or failure constraints where action sequences may be forcibly terminated once resources are exhausted, agents face implicit trade-offs that reshape their utility-driven (rational) behaviour. Additionally, since these agents are typically commissioned by a h…

Non-Gaussian enhancement of precision in quantum batteries
Beatriz Polo, Federico Centrone
https://arxiv.org/abs/2505.24604 https://a…

Non-Gaussian enhancement of precision in quantum batteries
We investigate the fundamental limits of converting light into useful work, with a focus on the role of quantum resources in energy harvesting processes. Specifically, we analyze how quantum coherence, non-Gaussianity, and entanglement affect the fluctuations in the energy output of bosonic quantum batteries. Our findings reveal potential pathways to enhance the efficiency and stability of energy extraction from quantum batteries, with implications for the development of quantum thermal machine…

In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration
Jiajie Fu, Haitong Tang, Arijit Khan, Sharad Mehrotra, Xiangyu Ke, Yunjun Gao
https://arxiv.org/abs/2506.02509

In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration
Entity Resolution (ER) is a fundamental data quality improvement task that identifies and links records referring to the same real-world entity. Traditional ER approaches often rely on pairwise comparisons, which can be costly in terms of time and monetary resources, especially with large datasets. Recently, Large Language Models (LLMs) have shown promising results in ER tasks. However, existing methods typically focus on pairwise matching, missing the potential of LLMs to perform clustering di…

Coordination of Electrical and Heating Resources by Self-Interested Agents
Rico Schrage, Jari Radler, Astrid Nie{\ss}e
https://arxiv.org/abs/2506.16277 htt…

Coordination of Electrical and Heating Resources by Self-Interested Agents
With the rise of distributed energy resources and sector coupling, distributed optimization can be a sensible approach to coordinate decentralized energy resources. Further, district heating, heat pumps, cogeneration, and sharing concepts like local energy communities introduce the potential to optimize heating and electricity output simultaneously. To solve this issue, we tackle the distributed multi-energy scheduling optimization problem, which describes the optimization of distributed energy…

🚀 Ab sofort können digitale Forschungswerkzeuge für die NFDI4Culture Registry ganz unkompliziert über ein Online-Erfassungsformular vorgeschlagen werden: https://nfdi4culture.de/de/resources/registry/formular.html.
💡 Zielgruppe sind Forschende und Entwickler*innen gleiche…

How the Center for Investigative Reporting is handling the lawsuit against OpenAI as one of the few nonprofits with the resources to take on a yearslong suit (Andrew Deck/Nieman Lab)
https://www.niemanlab.org/2025/06/what-it-takes-to-sue-op…

Perpetua Resources gets final federal permit for Stibnite #Gold project in Idaho | mining.com | #geology #antimony

Perpetua Resources gets final federal permit for Stibnite Gold project in Idaho 
The decision comes after eight years of rigorous inter-agency federal permitting, and was the last federal permit required to progress towards construction. 

D-Rex: Heterogeneity-Aware Reliability Framework and Adaptive Algorithms for Distributed Storage
Maxime Gonthier (University of Chicago, Argonne National Laboratory), Dante D. Sanchez-Gallegos (Universidad Carlos III de Madrid), Haochen Pan (University of Chicago), Bogdan Nicolae (Argonne National Laboratory), Sicheng Zhou (Southern University of Science and Technology), Hai Duc Nguyen (University of Chicago, Argonne National Laboratory), Valerie Hayot-Sasson (University of Chicago, Ar…

D-Rex: Heterogeneity-Aware Reliability Framework and Adaptive Algorithms for Distributed Storage
The exponential growth of data necessitates distributed storage models, such as peer-to-peer systems and data federations. While distributed storage can reduce costs and increase reliability, the heterogeneity in storage capacity, I/O performance, and failure rates of storage resources makes their efficient use a challenge. Further, node failures are common and can lead to data unavailability and even data loss. Erasure coding is a common resiliency strategy implemented in storage systems to mi…

🚚 Move your #Azure resources across subscriptions or resource groups—without downtime!
Use CLI, PowerShell, Python, or REST API to stay flexible and in control. ⚙️📦 Just update those resource IDs! #CloudManagement
Learn more:

Threadbox: Sandboxing for Modular Security
Maysara Alhindi, Joseph Hallett
https://arxiv.org/abs/2506.23683 https://arxiv.org/pdf/250…

Threadbox: Sandboxing for Modular Security
There are many sandboxing mechanisms provided by operating systems to limit what resources applications can access, however, sometimes the use of these mechanisms requires developers to refactor their code to fit the sandboxing model. In this work, we investigate what makes existing sandboxing mechanisms challenging to apply to certain types of applications, and propose Threadbox, a sandboxing mechanism that enables having modular and independent sandboxes, and can be applied to threads and san…

Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications
Srikanth Thudumu, Jason Fisher, Hung Du
https://arxiv.org/abs/2505.24765

Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications
Supervised Quantum Machine Learning (QML) represents an intersection of quantum computing and classical machine learning, aiming to use quantum resources to support model training and inference. This paper reviews recent developments in supervised QML, focusing on methods such as variational quantum circuits, quantum neural networks, and quantum kernel methods, along with hybrid quantum-classical workflows. We examine recent experimental studies that show partial indications of quantum advantag…

Raiders take care of their own by hosting second annual Alumni Wellness Weekend https://www.raiders.com/news/raiders-second-annual-alumni-wellness-weekend-nfl

This https://arxiv.org/abs/0808.3636 has been replaced.
link: https://scholar.google.com/scholar?q=a

Physics education research: Resources for graduate student instructors
This resource letter intends to provide physics instructors - particularly graduate student teaching assistants - at the introductory university level with a small but representative collection of resources to acquire a familiarity with research in physics education for guidance in everyday instruction. The resources are in the form of books, articles, websites, journals, and organizations.

A double selection entanglement distillation-based state estimator
Joshua Carlo A. Casapao, Ananda G. Maity, Naphan Benchasattabuse, Michal Hajdu\v{s}ek, Akihito Soeda, Rodney Van Meter, David Elkouss
https://arxiv.org/abs/2505.24280

A double selection entanglement distillation-based state estimator
With the advent of practical quantum communication networks drawing closer, there is a growing need for reliable estimation protocols that can efficiently characterize quantum resources with minimum resource overhead requirement. A novel approach to this problem is to integrate an estimator into an existing network task, thereby removing the need for an additional characterization protocol. In this work, we show that the measurement statistics of a double selection distillation protocol alone c…

This https://arxiv.org/abs/2411.16746 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

LoBAM: LoRA-Based Backdoor Attack on Model Merging
Model merging is an emerging technique that integrates multiple models fine-tuned on different tasks to create a versatile model that excels in multiple domains. This scheme, in the meantime, may open up backdoor attack opportunities where one single malicious model can jeopardize the integrity of the merged model. Existing works try to demonstrate the risk of such attacks by assuming substantial computational resources, focusing on cases where the attacker can fully fine-tune the pre-trained m…

Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games
David Guzman Piedrahita, Yongjin Yang, Mrinmaya Sachan, Giorgia Ramponi, Bernhard Sch\"olkopf, Zhijing Jin
https://arxiv.org/abs/2506.23276

Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games
As large language models (LLMs) are increasingly deployed as autonomous agents, understanding their cooperation and social mechanisms is becoming increasingly important. In particular, how LLMs balance self-interest and collective well-being is a critical challenge for ensuring alignment, robustness, and safe deployment. In this paper, we examine the challenge of costly sanctioning in multi-agent LLM systems, where an agent must decide whether to invest its own resources to incentivize cooperat…

Entanglement Detection with Variational Quantum Interference: Theory and Experiment
Rui Zhang, Zhenhuan Liu, Chendi Yang, Yue-Yang Fei, Xu-Fei Yin, Yingqiu Mao, Li Li, Nai-Le Liu, Yu-Ao Chen, Jian-Wei Pan
https://arxiv.org/abs/2505.24764

Entanglement Detection with Variational Quantum Interference: Theory and Experiment
Entanglement detection serves as a fundamental task in quantum information science, playing a critical role in quantum benchmarking and foundational studies. As the number of controllable qubits continues to increase, there emerges a pressing demand for scalable and robust entanglement detection protocols that can maintain high detection capability while requiring minimal resources. By integrating the positive partial transposition criterion with variational quantum interference, we develop an …

CrossPipe: Towards Optimal Pipeline Schedules for Cross-Datacenter Training
Tiancheng Chen, Ales Kubicek, Langwen Huang, Torsten Hoefler
https://arxiv.org/abs/2507.00217

CrossPipe: Towards Optimal Pipeline Schedules for Cross-Datacenter Training
Training large language models (LLMs) now requires resources that exceed a single datacenter, making cross-datacenter strategies increasingly crucial. We present CrossPipe, a framework designed to optimize model training across geographically distributed datacenters by explicitly modeling and mitigating the impact of network latency and limited bandwidth. It enables unified analysis and optimization incorporating both pipeline parallelism (PP) and opportunities for overlapping data parallelism …

This https://arxiv.org/abs/2411.05185 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

PentestAgent: Incorporating LLM Agents to Automated Penetration Testing
Penetration testing is a critical technique for identifying security vulnerabilities, traditionally performed manually by skilled security specialists. This complex process involves gathering information about the target system, identifying entry points, exploiting the system, and reporting findings. Despite its effectiveness, manual penetration testing is time-consuming and expensive, often requiring significant expertise and resources that many organizations cannot afford. While automated pen…

Green Metrics Tool: Measuring for fun and profit
Geerd-Dietger Hoffmann, Verena Majuntke
https://arxiv.org/abs/2506.23967 https://arx…

Green Metrics Tool: Measuring for fun and profit
The environmental impact of software is gaining increasing attention as the demand for computational resources continues to rise. In order to optimize software resource consumption and reduce carbon emissions, measuring and evaluating software is a first essential step. In this paper we discuss what metrics are important for fact base decision making. We introduce the Green Metrics Tool (GMT), a novel framework for accurately measuring the resource consumption of software. The tool provides a c…

Required reading.
✅ Human Rights Campaign | Tips for Preparedness, Peaceful Protesting, and Safety
https://www.hrc.org/resources/tips-for-preparedness-peaceful-protesting-and-safety

Tips for Preparedness, Peaceful Protesting, and Safety
Safety and preparedness are essential in uncertain times. Whether you're preparing for an emergency or participating in a peaceful protest, these…

QoS-aware State-Augmented Learnable Algorithm for Wireless Coexistence Parameter Management
Mohammad Reza Fasihi, Brian L. Mark
https://arxiv.org/abs/2506.22652

QoS-aware State-Augmented Learnable Algorithm for Wireless Coexistence Parameter Management
Efficient and fair coexistence in unlicensed spectrum is essential to support heterogeneous networks such as 5G NR-U and Wi-Fi, which often contend for shared wireless resources. We introduce a general framework for wireless Coexistence Parameter Management (CPM) based on state-augmented constrained reinforcement learning. We propose a novel algorithm, QaSAL-CPM, which incorporates state-augmentation by embedding the dual variables in the constrained optimization formulation directly into the a…

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

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

DAPFAM: A Domain-Aware Patent Retrieval Dataset Aggregated at the Family Level
Iliass Ayaou (ICube), Denis Cavallucci (ICube), Hicham Chibane (ICube)
https://arxiv.org/abs/2506.22141

DAPFAM: A Domain-Aware Patent Retrieval Dataset Aggregated at the Family Level
In the landscape of publicly available patent retrieval datasets, the need for explicit indomain and out-of-domain labeling, multi-jurisdiction coverage, balanced query domain representation and manageable sizes that support sub document level experiments on moderate computational resources is often overlooked. To address these gaps, we propose DAPFAM, a new open access domain-aware patent retrieval dataset constructed at the simple-family level. The dataset contains 1,247 domain balanced full …

Melding the Serverless Control Plane with the Conventional Cluster Manager for Speed and Compatibility
Leonid Kondrashov, Lazar Cvetkovi\'c, Hancheng Wang, Boxi Zhou, Dhairya Rungta, Dmitrii Ustiugov
https://arxiv.org/abs/2505.24551

Melding the Serverless Control Plane with the Conventional Cluster Manager for Speed and Compatibility
Modern serverless applications, often interactive with highly volatile traffic, challenge system scalability, demanding control planes that deliver low latency and cost efficiency. Analysis of production traces and existing systems reveals that current control plane designs (synchronous and asynchronous), particularly when built on conventional cluster managers like Kubernetes, struggle with this balance, often wasting significant CPU and memory resources on creating underutilized or idle insta…

Effectiveness of the DEJAMPS purification protocol in noisy entangled photon systems, a Monte Carlo simulation
Vasilis Skarlatos, Nikos Konofaos
https://arxiv.org/abs/2506.22830

Effectiveness of the DEJAMPS purification protocol in noisy entangled photon systems, a Monte Carlo simulation
Entanglement purification is a critical enabling technology for quantum communication, allowing high-fidelity entangled pairs to be distilled from noisy resources. We present a comprehensive Monte Carlo study of the DEJMPS purification protocol applied to polarization-entangled photon pairs subject to both amplitude-damping noise (gamma) and dephasing noise (p). By sweeping (gamma, p) over a two-dimensional grid and performing repeated stochastic trials, we map out the average fidelity and aver…

Turning AI Data Centers into Grid-Interactive Assets: Results from a Field Demonstration in Phoenix, Arizona
Philip Colangelo, Ayse K. Coskun, Jack Megrue, Ciaran Roberts, Shayan Sengupta, Varun Sivaram, Ethan Tiao, Aroon Vijaykar, Chris Williams, Daniel C. Wilson, Zack MacFarland, Daniel Dreiling, Nathan Morey, Anuja Ratnayake, Baskar Vairamohan
htt…

Turning AI Data Centers into Grid-Interactive Assets: Results from a Field Demonstration in Phoenix, Arizona
Artificial intelligence (AI) is fueling exponential electricity demand growth, threatening grid reliability, raising prices for communities paying for new energy infrastructure, and stunting AI innovation as data centers wait for interconnection to constrained grids. This paper presents the first field demonstration, in collaboration with major corporate partners, of a software-only approach--Emerald Conductor--that transforms AI data centers into flexible grid resources that can efficiently an…

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…

Performance Measurements in the AI-Centric Computing Continuum Systems
Praveen Kumar Donta, Qiyang Zhang, Schahram Dustdar
https://arxiv.org/abs/2506.22884

Performance Measurements in the AI-Centric Computing Continuum Systems
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Continuum (DCC). In this model, multiple layers such as cloud, edge, Internet of Things (IoT), and mobile platforms work together to support a wide range of applications. Recently, the emergence of Generative AI and large language models has further intensified the demand for computational resources across this continuum…