Tootfinder

Bellingcat tested LLMs for Geolocation.
#AI

Have LLMs Finally Mastered Geolocation? - bellingcat
We tasked LLMs from OpenAI, Google, Anthropic, Mistral and xAI to geolocate our unpublished holiday snaps. Here's how they did.

New apps are helping immigrants navigate Trump's deportation crackdown, including by alerting users to locations of ICE raids and informing them of their rights (Rest of World)
https://restofworld.org/2025/immigration-raids-migrant-safety-apps/

New apps help immigrants navigate Trump’s deportation crackdown
With tightening immigration policies and rising fears of deportation, new apps provide migrants with resources to stay prepared and connected.

O'Reilly: GenAI has adopted a colonialist business model.
https://www.linkedin.com/posts/timo3_proud-of-the-cloudflare-team-working-to-build-activity-7345899260506271745-mlHS

If you want to understand why O'Reilly is a supporter of this announcement, and want to ask both me and Matthew Prince about it, join our July 14 conversation on Live with Tim O'Reilly. | Tim O'Reilly
If you want to understand why O'Reilly is a supporter of this announcement, and want to ask both me and Matthew Prince about it, join our July 14 conversation on Live with Tim O'Reilly. AI has adopted colonialism as its business model: Extract resources from others and use it to enrich yourself and your customers at the expense of those whose resources you have taken, without giving much back. It's high time we started developing new mechanisms to enable content monetization for creators, not …

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

Exclusive: Ukraine pitches deepwater gas, oil refinery projects to US under landmark minerals deal: https://benborges.xyz/2025/07/07/exclusive-ukraine-pitches-deepwater-gas.html

This https://arxiv.org/abs/2506.03830 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Construction of Urban Greenland Resources Collaborative Management Platform
Nowadays, environmental protection has become a global consensus. At the same time, with the rapid development of science and technology, urbanisation has become a phenomenon that has become the norm. Therefore, the urban greening management system is an essential component in protecting the urban environment. The system utilises a transparent management process known as" monitoring - early warning - response - optimisation," which enhances the tracking of greening resources, streamlines mainte…

In Milwaukee bike news…
https://urbanmilwaukee.com/2025/07/05/philanthropist-donates-500-bikes-to-milwaukee-youths/
“Erik James gave away 500 bikes along with free resources and food for families.”

Philanthropist Donates 500 Bikes to Milwaukee Youths
Eric 'Shake' James saw something missing in Milwaukee’s underserved communities.

Madre Fire Daily Update from Los Padres National Forest:
Size: 79,936 Acres
Containment: 30%
Total Personnel: 1,358
The Madre Fire remains active due to dry fuels, sustained winds, and high temperatures.
Firefighters made good progress around the outer perimeter of the fire, creating direct and indirect lines, and increased containment.
The incident command team is utilizing a variety of resources including helicopters, dozers, engines, and hot shot crews.…

This https://arxiv.org/abs/2502.00722 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
Recent advancements in Large Language Models (LLMs) have led to increasingly diverse requests, accompanied with varying resource (compute and memory) demands to serve them. However, this in turn degrades the cost-efficiency of LLM serving as common practices primarily rely on homogeneous GPU resources. In response to this problem, this work conducts a thorough study about serving LLMs over heterogeneous GPU resources on cloud platforms. The rationale is that different GPU types exhibit distinct…

Tonight #Maven and Maven Exec plugin in combination with Weld brought me to me knees.
Weld refused to load my classes and resources even if Maven reports compilation is successful, I can see the classes in target/classes, and when using -X I see it adds the jars and target/classes to the classpath.
Still Weld throws a bunch of ClassNotFound exceptions.
To make things a lot worse, there're no good hits when searching.
😖 emoji-with-pulling-my-hair emoji-with-me-banging-my-head-against-the-desk 😩

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/

This https://arxiv.org/abs/2505.24765 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

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…

it is now possible to set arbitrary strap pins with #GlasgowInterfaceExplorer! use `glasgow multi <...> gpio --pins B0:3 B0=0 B1=H B2=L B3=1` to strap B0 strong low, B1 weak high, B2 weak low, B3 strong high
the GPIO applet doesn't take up USB endpoint resources, so this is "free": you can append ` gpio` to any applet command line you'd like

This https://arxiv.org/abs/2506.02040 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

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…

I’m well out of my depth here: my historical knowledge to speak to the issues is thin; my cultural knowledge is almost nonexistent. Reading that Standing Together site, seeing how they’ve crafted what they write, I see just how much nuance and awareness I •don’t• have.
I’m grateful to the people who’ve helped me learn, and who’ve pointed me to these resources — in this case @… and @…. Sometimes the Internet really is good for something.
/end

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/2503.05740 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

ChatWise: A Strategy-Guided Chatbot for Enhancing Cognitive Support in Older Adults
Cognitive health in older adults presents a growing challenge. Although conversational interventions show feasibility in improving cognitive wellness, human caregiver resources remain overloaded. AI-based chatbots have shown promise, yet existing work is often limited to implicit strategies or heavily depends on training and label resources. In response, we propose a strategy-guided AI chatbot named ChatWise that follows a dual-level conversation reasoning framework. It integrates macro-level s…

#Publishers and #Editors looking for guidance on how to #DefendResearch against #censorship

Nesting focusable elements is problematic. Have you seen any good blogposts, docs, or other #accessibility resources that go into *why* nesting is problematic?
I’m looking for something I could link to in a blogpost of my own, on a somewhat different topic. Preference is for something in-depth, and not marketing slop for a company (especially not for anyone affiliated with an overlay vendo…

ROSGuard: A Bandwidth Regulation Mechanism for ROS2-based Applications
Jon Altonaga Puente, Enrico Mezzetti, Irune Agirre Troncoso, Jaume Abella Ferrer, Francisco J. Cazorla Almeida
https://arxiv.org/abs/2506.04640

ROSGuard: A Bandwidth Regulation Mechanism for ROS2-based Applications
Multicore timing interference, arising when multiple requests contend for the same shared hardware resources, is a primary concern for timing verification and validation of time-critical applications. Bandwidth control and regulation approaches have been proposed in the literature as an effective method to monitor and limit the impact of timing interference at run time. These approaches seek for fine-grained control of the bandwidth consumption (at the microsecond level) to meet stringent timin…

Cloud-Based Interoperability in Residential Energy Systems
Darren Leniston, David Ryan, Ammar Malik, Jack Jackman, Terence O'Donnell
https://arxiv.org/abs/2506.05076

Cloud-Based Interoperability in Residential Energy Systems
As distributed energy resources (DERs) such as solar PV, batteries and electric vehicles become increasingly prevalent at the edge, maintaining grid stability requires advanced monitoring and control mechanisms. This paper presents a scalable smart grid gateway architecture that enables interoperability between Modbus-based inverters and IEEE 2030.5 cloud-based control systems. The proposed solution leverages Azure cloud services and edge-computing gateway devices to support dynamic configurati…

The people committed to DDoSing the #Apache #SpamAssassin RuleQA server seem to have substantial resources. I’ve blocked a lot of them, but they keep coming, asking about things like the May 7 2017 performance of a single rule in one contributor's stats. Not stuff real people want.
Of course…

#Archaeology #Neanderthals Ran “Fat Factories” 125,000 Years Ago
Groundbreaking discovery in Germany reveals large-scale fat processing by Neanderthals: Fat is a very valuable food, packed with calories, especially important when other resources might be scarce. Our earliest ancestors in Africa…

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

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…

How urban scaling and resource distribution shape social welfare and migration dynamics
Bryce Morsky
https://arxiv.org/abs/2506.03384 https://

How urban scaling and resource distribution shape social welfare and migration dynamics
Many outputs of cities scale in universal ways, including infrastructure, crime, and economic activity. Through a mathematical model, this study investigates the interplay between such scaling laws in human organization and governmental allocations of resources, focusing on impacts to migration patterns and social welfare. We find that if superlinear scaling resources of cities -- such as economic and social activity -- are the primary drivers of city dwellers' utility, then cities tend to conv…

This https://arxiv.org/abs/2506.00140 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

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 …

This https://arxiv.org/abs/2506.00691 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Optimizing Sensory Neurons: Nonlinear Attention Mechanisms for Accelerated Convergence in Permutation-Invariant Neural Networks for Reinforcement Learning
Training reinforcement learning (RL) agents often requires significant computational resources and extended training times. To address this, we build upon the foundation laid by Google Brain's Sensory Neuron, which introduced a novel neural architecture for reinforcement learning tasks that maintained permutation in-variance in the sensory neuron system. While the baseline model demonstrated significant performance improvements over traditional approaches, we identified opportunities to enhance…

"Space: 2075": #Space2075

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 …

After writing to my MP, it occurs to me that there may be people in the UK who would like to do so too, but may not know about these incredibly useful resources:
https://www.writetothem.com/

WriteToThem
WriteToThem is a website which provides an easy way to contact MPs, councillors and other elected representatives.

Construction of Urban Greenland Resources Collaborative Management Platform
Dongyang Lyu, Xiaoqi Li, Zongwei Li
https://arxiv.org/abs/2506.03830 https://…

Construction of Urban Greenland Resources Collaborative Management Platform
Nowadays, environmental protection has become a global consensus. At the same time, with the rapid development of science and technology, urbanisation has become a phenomenon that has become the norm. Therefore, the urban greening management system is an essential component in protecting the urban environment. The system utilises a transparent management process known as" monitoring - early warning - response - optimisation," which enhances the tracking of greening resources, streamlines mainte…

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…

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 –

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

Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing
Ke Ma, Junfei Xie
https://arxiv.org/abs/2506.04456 https://

Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing
Vehicle edge computing (VEC) brings abundant computing resources close to vehicles by deploying them at roadside units (RSUs) or base stations, thereby enabling diverse computation-intensive and delay sensitive applications. Existing task offloading strategies are often computationally expensive to execute or generate suboptimal solutions. In this paper, we propose a novel learning-based approach, Knowledge-guided Attention-inspired Task Offloading (KATO), designed to efficiently offload tasks …

This https://arxiv.org/abs/2408.04576 has been replaced.
initial toot: https://mastoxiv.page/@…

Time-cost-error trade-off relation in thermodynamics: The third law and beyond
Elucidating fundamental limitations inherent in physical systems is a central subject in physics. For important thermodynamic operations such as information erasure, cooling, and copying, resources like time and energetic cost must be expended to achieve the desired outcome within a predetermined error margin. In the context of cooling, the unattainability principle of the third law of thermodynamics asserts that infinite ``resources'' are needed to reach absolute zero. However, the precise ide…

Trump ordered his White House counsel and the attorney general on Wednesday to investigate former President Joseph R. Biden Jr. and his staff -- in Mr. Trump’s latest attempt to stoke outlandish conspiracy theories about his predecessor.
In an executive order, Mr. Trump put the power and resources of the federal government to work examining whether some of Mr. Biden’s presidential actions were legally invalid because his aides had enacted those policies without his knowledge.
The e…

Trump Orders Investigation of Biden and His Aides
The executive order is the latest effort by President Trump to stoke outlandish conspiracy theories about his predecessor and question the legality of his actions in office.

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…

This https://arxiv.org/abs/2506.00605 has been replaced.
link: https://scholar.google.com/scholar?q=a

ABCDEFGH: An Adaptation-Based Convolutional Neural Network-CycleGAN Disease-Courses Evolution Framework Using Generative Models in Health Education
With the advancement of modern medicine and the development of technologies such as MRI, CT, and cellular analysis, it has become increasingly critical for clinicians to accurately interpret various diagnostic images. However, modern medical education often faces challenges due to limited access to high-quality teaching materials, stemming from privacy concerns and a shortage of educational resources (Balogh et al., 2015). In this context, image data generated by machine learning models, partic…

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.

QiMeng: Fully Automated Hardware and Software Design for Processor Chip
Rui Zhang, Yuanbo Wen, Shuyao Cheng, Di Huang, Shaohui Peng, Jiaming Guo, Pengwei Jin, Jiacheng Zhao, Tianrui Ma, Yaoyu Zhu, Yifan Hao, Yongwei Zhao, Shengwen Liang, Ying Wang, Xing Hu, Zidong Du, Huimin Cui, Ling Li, Qi Guo, Yunji Chen
https://arxiv.org/abs…

QiMeng: Fully Automated Hardware and Software Design for Processor Chip
Processor chip design technology serves as a key frontier driving breakthroughs in computer science and related fields. With the rapid advancement of information technology, conventional design paradigms face three major challenges: the physical constraints of fabrication technologies, the escalating demands for design resources, and the increasing diversity of ecosystems. Automated processor chip design has emerged as a transformative solution to address these challenges. While recent breakthr…

"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."

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

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.

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. 

"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…

Trump’s national cyber director nominee grilled about his resume, proposed spending cuts https://therecord.media/sean-cairncross-oncd-nominee-senate-confirmation-hearing

The NASA Exoplanet Archive and Exoplanet Follow-up Observing Program: Data, Tools, and Usage
Jessie L. Christiansen, Douglas L. McElroy, Marcy Harbut, David R. Ciardi, Megan Crane, John Good, Kevin K. Hardegree-Ullman, Aurora Y. Kesseli, Michael B. Lund, Meca Lynn, Ananda Muthiar, Ricky Nilsson, Toba Oluyide, Michael Papin, Amalia Rivera, Melanie Swain, Nicholas D. Susemiehl, Raymond Tam, Julian van Eyken, Charles Beichman

The NASA Exoplanet Archive and Exoplanet Follow-up Observing Program: Data, Tools, and Usage
The NASA Exoplanet Archive and the Exoplanet Follow-up Observing Program service are two widely used resources for the exoplanet community. The NASA Exoplanet Archive provides a complete and accurate accounting of exoplanetary systems published by NASA missions and by the community in the refereed literature. In anticipation of continued exponential growth in the number of exoplanetary systems, and the increasing complexity in our characterization of these systems, the NASA Exoplanet Archive ha…

This https://arxiv.org/abs/2305.03556 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

Energy-Latency Aware Intelligent Reflecting Surface Aided Multi-cell Mobile Edge Computing
The explosive development of the Internet of Things (IoT) has led to increased interest in mobile edge computing (MEC), which provides computational resources at network edges to accommodate computation-intensive and latency-sensitive applications. Intelligent reflecting surfaces (IRSs) have gained attention as a solution to overcome blockage problems during the offloading uplink transmission in MEC systems. This paper explores IRS-aided multi-cell networks that enable servers to serve neighbor…

🚀 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…

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…

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training
Neil K. R. Sehgal, Hita Kambhamettu, Allen Chang, Andrew Zhu, Lyle Ungar, Sharath Chandra Guntuku
https://arxiv.org/abs/2507.02122

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training
Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like standardized patients. We present PAL (Palliative Assisted Learning-bot), a conversational system that simulates emotionally nuanced patient interactions and delivers structured feedback grounded in an existing empathy-based framework. PAL supports text and voice modalities and is designed to scaffold clinical skill-building through repeated, low-co…

This https://arxiv.org/abs/2506.02774 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

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…

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 …

This https://arxiv.org/abs/2503.22733 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

RBFleX-NAS: Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection
Neural Architecture Search (NAS) is an automated technique to design optimal neural network architectures for a specific workload. Conventionally, evaluating candidate networks in NAS involves extensive training, which requires significant time and computational resources. To address this, training-free NAS has been proposed to expedite network evaluation with minimal search time. However, state-of-the-art training-free NAS algorithms struggle to precisely distinguish well-performing networks f…

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 …

This https://arxiv.org/abs/2505.19641 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
Recent advances such as OpenAI-o1 and DeepSeek R1 have demonstrated the potential of Reinforcement Learning (RL) to enhance reasoning abilities in Large Language Models (LLMs). While open-source replication efforts have primarily focused on mathematical and coding domains, methods and resources for developing general reasoning capabilities remain underexplored. This gap is partly due to the challenge of collecting diverse and verifiable reasoning data suitable for RL. We hypothesize that logica…

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…

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

This https://arxiv.org/abs/2505.24200 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Improving Multilingual Speech Models on ML-SUPERB 2.0: Fine-tuning with Data Augmentation and LID-Aware CTC
Multilingual speech processing with self-supervised or supervised pre-trained Speech Foundation Models (SFM) has achieved strong performance on tasks like Language Identification (LID) and Automatic Speech Recognition (ASR). However, these models struggle with limited resources during fine-tuning. This paper enhances multilingual LID and ASR on ML-SUPERB 2.0 by exploring multiple strategies for adapting SFMs, including frozen upstream training, partial fine-tuning, and low-rank adaptation. Furt…

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…

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/

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

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

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

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

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}, …

This https://arxiv.org/abs/2506.02965 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Memory-Efficient and Privacy-Preserving Collaborative Training for Mixture-of-Experts LLMs
Mixture-of-Experts (MoE) has been gaining popularity due to its successful adaptation to large language models (LLMs). In this work, we introduce Privacy-preserving Collaborative Mixture-of-Experts (PC-MoE), which leverages the sparsity of the MoE architecture for memory-efficient decentralized collaborative LLM training, enabling multiple parties with limited GPU-memory and data resources to collectively train more capable LLMs than they could achieve individually. At the same time, this appro…

🚀 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…

Rethinking Broken Object Level Authorization Attacks Under Zero Trust Principle
Anbin Wu (The College of Intelligence and Computing, Tianjin University), Zhiyong Feng (The College of Intelligence and Computing, Tianjin University), Ruitao Feng (The Southern Cross University)
https://arxiv.org/abs/2507.02309

Rethinking Broken Object Level Authorization Attacks Under Zero Trust Principle
RESTful APIs facilitate data exchange between applications, but they also expose sensitive resources to potential exploitation. Broken Object Level Authorization (BOLA) is the top vulnerability in the OWASP API Security Top 10, exemplifies a critical access control flaw where attackers manipulate API parameters to gain unauthorized access. To address this, we propose BOLAZ, a defense framework grounded in zero trust principles. BOLAZ analyzes the data flow of resource IDs, pinpointing BOLA atta…

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

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…

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,...

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…

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…

Nonlinear Optimal Control of DC Microgrids with Safety and Stability Guarantees
Muratkhan Abdirash, Xiaofan Cui
https://arxiv.org/abs/2506.03454 https://…

Nonlinear Optimal Control of DC Microgrids with Safety and Stability Guarantees
A DC microgrid is a promising alternative to the traditional AC power grid, since it can efficiently integrate distributed and renewable energy resources. However, as an emerging framework, it lacks the rigorous theoretical guarantees of its AC counterpart. In particular, safe stabilization of the DC microgrid has been a non-trivial task in power electronics. To address that, we take a control theoretic perspective in designing the feedback controller with provable guarantees. We present a syst…

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 …

Access Control Threatened by Quantum Entanglement
Zhicheng Zhang, Mingsheng Ying
https://arxiv.org/abs/2507.02622 https://arxiv.org/p…

Access Control Threatened by Quantum Entanglement
Access control is a cornerstone of computer security that prevents unauthorised access to resources. In this paper, we study access control in quantum computer systems. We present the first explicit scenario of a security breach when a classically secure access control system is straightforwardly adapted to the quantum setting. The breach is ultimately due to that quantum mechanics allows the phenomenon of entanglement and violates Mermin inequality, a multi-party variant of the celebrated Bell…

Control at Stake: Evaluating the Security Landscape of LLM-Driven Email Agents
Jiangrong Wu, Yuhong Nan, Jianliang Wu, Zitong Yao, Zibin Zheng
https://arxiv.org/abs/2507.02699

Control at Stake: Evaluating the Security Landscape of LLM-Driven Email Agents
The increasing capabilities of LLMs have led to the rapid proliferation of LLM agent apps, where developers enhance LLMs with access to external resources to support complex task execution. Among these, LLM email agent apps represent one of the widely used categories, as email remains a critical communication medium for users. LLM email agents are capable of managing and responding to email using LLM-driven reasoning and autonomously executing user instructions via external email APIs (e.g., se…

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.

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 …

Two-Stage Bidirectional Inverter Equivalent Circuit Model for Distribution Grid Steady-State Analysis and Optimization
Emmanuel O. Badmus, Amritanshu Pandey
https://arxiv.org/abs/2506.03430

Two-Stage Bidirectional Inverter Equivalent Circuit Model for Distribution Grid Steady-State Analysis and Optimization
This paper presents a \textit{physics-based} steady-state equivalent circuit model of a two-stage bidirectional inverter. These inverters connect distributed energy resources (DERs), such as photovoltaic (PV) and battery systems, to distribution grids. Existing inverter models have technical gaps on three fronts: i) inadequate modeling of inverter losses, ii) use of mathematical abstractions for bidirectional flow of power, and iii) inability to integrate different control modes into nonlinear …

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…

Enhancing Noisy Quantum Sensing by GHZ State Partitioning
Allen Zang, Tian-Xing Zheng, Peter C. Maurer, Frederic T. Chong, Martin Suchara, Tian Zhong
https://arxiv.org/abs/2507.02829

Enhancing Noisy Quantum Sensing by GHZ State Partitioning
Presence of harmful noise is inevitable in entanglement-enhanced sensing systems, requiring careful allocation of resources to optimize sensing performance in practical scenarios. We advocate a simple but effective strategy to improve sensing performance in the presence of noise. Given a fixed number of quantum sensors, we partition the preparation of GHZ states by preparing smaller, independent sub-ensembles of GHZ states instead of a GHZ state across all sensors. We perform extensive analytic…

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…

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/2505.23337 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…

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…

This https://arxiv.org/abs/2506.00377 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Systematic Review of Metaheuristics-Based and Machine Learning-Driven Intrusion Detection Systems in IoT
The widespread adoption of the Internet of Things (IoT) has raised a new challenge for developers since it is prone to known and unknown cyberattacks due to its heterogeneity, flexibility, and close connectivity. To defend against such security breaches, researchers have focused on building sophisticated intrusion detection systems (IDSs) using machine learning (ML) techniques. Although these algorithms notably improve detection performance, they require excessive computing power and resources,…

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…

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…

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…

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…

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…

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…

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…