Tootfinder

Metacurity is pleased to offer our free and premium subscribers a weekly digest of the best long-form (and longish) infosec-related pieces we couldn't properly fit into our daily news crush.
This week's selection covers
--Bashar al-Assad was toppled by spyware,
--Facial recognition threatens us all with deportation,
--VC money fuels worker surveillance,
--Will Trump launch offensive cyber ops on US networks?,
--The Pall Mall Process and commercial c…

Best infosec-related long reads for the week of 5/31/25
Bashar al-Assad was toppled by spyware, Facial recognition threatens us all with deportation, VC money fuels worker surveillance, Will Trump launch offensive cyber ops on US networks?, The Pall Mall Process and commercial cyber intrusions, Self-confidence leads to GenAI skepticism, more

Distributional encoding for Gaussian process regression with qualitative inputs
S\'ebastien Da Veiga (ENSAI, CREST, RT-UQ)
https://arxiv.org/abs/2506.04813

Distributional encoding for Gaussian process regression with qualitative inputs
Gaussian Process (GP) regression is a popular and sample-efficient approach for many engineering applications, where observations are expensive to acquire, and is also a central ingredient of Bayesian optimization (BO), a highly prevailing method for the optimization of black-box functions. However, when all or some input variables are categorical, building a predictive and computationally efficient GP remains challenging. Starting from the naive target encoding idea, where the original categor…

This https://arxiv.org/abs/2412.20925 has been replaced.
link: https://scholar.google.com/scholar?q=a

Active Learning with Variational Quantum Circuits for Quantum Process Tomography
Quantum process tomography (QPT) is a fundamental tool for fully characterizing quantum systems. It relies on querying a set of quantum states as input to the quantum process. Previous QPT methods typically employ a straightforward strategy for randomly selecting quantum states, overlooking differences in informativeness among them. In this work, we propose a general active learning (AL) framework that adaptively selects the most informative subset of quantum states for reconstruction. We desig…

"The process of coding with an “agentic” LLM appears to be the process of carefully distilling all the worst parts of code review, and removing and discarding all of its benefits."
Very insightful post on #GenAI by Glyph
(Original title: I Think I’m Done Thinking About genAI For Now)

From Theory to Practice: Real-World Use Cases on Trustworthy LLM-Driven Process Modeling, Prediction and Automation
Peter Pfeiffer, Alexander Rombach, Maxim Majlatow, Nijat Mehdiyev
https://arxiv.org/abs/2506.03801

From Theory to Practice: Real-World Use Cases on Trustworthy LLM-Driven Process Modeling, Prediction and Automation
Traditional Business Process Management (BPM) struggles with rigidity, opacity, and scalability in dynamic environments while emerging Large Language Models (LLMs) present transformative opportunities alongside risks. This paper explores four real-world use cases that demonstrate how LLMs, augmented with trustworthy process intelligence, redefine process modeling, prediction, and automation. Grounded in early-stage research projects with industrial partners, the work spans manufacturing, modeli…

CapVest-owned Datasite, which offers workflow automation tech for dealmaking, acquires Grata, which helps users with all aspects of the deal process, for $200M (Maria Armental/Wall Street Journal)
https://www.wsj.com/articles/private-equi…

The National Oceanic and Atmospheric Administration, contracts must first go through an approval process led in part by a young man who worked as a Temple University food hall monitor last year.
A few weeks earlier, Politico reported on a different young man, just four years removed from high school, who was appointed to serve as the acting chief AI officer at the Department of Health and Human Services, while on leave from pursuing his undergraduate degree.
The problem is made w…

Despite talk of ‘meritocracy,’ a Team of Amateurs holds sway on Team Trump
One of the things that people outside of Washington, D.C., might not fully appreciate about how the city works is the outsize influence of young adults.

Total progeny for spectrally negative branching L{\'e}vy processes with absorption
Christophe Profeta (LaMME)
https://arxiv.org/abs/2506.04783 https://…

Total progeny for spectrally negative branching L{é}vy processes with absorption
We consider a spectrally negative branching L{é}vy process in which particles are killed upon crossing below zero. It is known that such a process becomes extinct almost surely if the drift toward -$\infty$ is sufficiently strong to counterbalance the reproduction rate. In this note, we study the tail asymptotics of the number of particles absorbed at the boundary during the lifetime of the process, in both the subcritical and critical regimes.

"As I've mentioned before, I'm working (with a group of other volunteers) on producing a Local Place Plan for Auchencairn, and, in the process of doing that, we're using the Place Standard Tool. Data from the Place Standard Tool is delivered as an unwieldy CSV file with 53 columns, most of which contain narrative data.
This is pretty hard to analyse... so I've written a tool to automate summarising the data. And, actually, I'm quite pleased with it." -- m…

Place Standard Tool Summariser: Full Test Run

Trust the process: mapping data-driven reconstructions to informed models using stochastic processes
Stefano Rinaldi, Alexandre Toubiana, Jonathan R. Gair
https://arxiv.org/abs/2506.05153

Trust the process: mapping data-driven reconstructions to informed models using stochastic processes
Gravitational-wave astronomy has entered a regime where it can extract information about the population properties of the observed binary black holes. The steep increase in the number of detections will offer deeper insights, but it will also significantly raise the computational cost of testing multiple models. To address this challenge, we propose a procedure that first performs a non-parametric (data-driven) reconstruction of the underlying distribution, and then remaps these results onto a …

I finally got rid of the old bed I’d kept since moving in, so the room feels pretty empty right now.
I’m in the process of reorganizing everything and plan to turn this space into my own anarchist sanctuary.
Soon, I’ll add a bookshelf and more anarchist art to the wall, right next to the communist hammer and sickle symbol.
#Declutter

Was Residual Penalty and Neural Operators All We Needed for Solving Optimal Control Problems?
Oliver G. S. Lundqvist, Fabricio Oliveira
https://arxiv.org/abs/2506.04742

Was Residual Penalty and Neural Operators All We Needed for Solving Optimal Control Problems?
Neural networks have been used to solve optimal control problems, typically by training neural networks using a combined loss function that considers data, differential equation residuals, and objective costs. We show that including cost functions in the training process is unnecessary, advocating for a simpler architecture and streamlined approach by decoupling the optimal control problem from the training process. Thus, our work shows that a simple neural operator architecture, such as DeepON…

Europium, we have a problem. Modelling r-process enrichment across Local Group galaxies
Marco Palla, Marta Molero, Donatella Romano, Alessio Mucciarelli
https://arxiv.org/abs/2506.04066

Europium, we have a problem. Modelling r-process enrichment across Local Group galaxies
Context: Europium (Eu) serves as a crucial tracer to understand the origin of rapid neutron-capture process (r-process) elements. An extensive effort was made in the last decade to model the chemical evolution of this element in the Galaxy. However, less attention was reserved to Eu in different galaxies of the Local Group (LG). Aims: By employing detailed and well-tested chemical evolution models, we investigate Eu enrichment across LG dwarf spheroidal galaxies, allowing for a direct compariso…

"Good process improvement practices include:
- standardized improvement process (pdsa, or whatever)

- Going to the gemba – improvement is done where the work is done. You must go to the where the action is. Sitting in meeting rooms, or offices, reading reports and making decisions is not the way to improve effectively.
- evidence based decision making..."

That a judge makes a comment like this so early in the process gives me hope that there will be a favorable outcome for writers whose work was pirated. Like me.
https://arstechnica.com/tech-policy/2025/05/jud…

Judge on Meta’s AI training: “I just don’t understand how that can be fair use”
Judge downplayed Meta’s “messed up” torrenting in lawsuit over AI training.

This https://arxiv.org/abs/2409.14202 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Mining Causality: AI-Assisted Search for Instrumental Variables
The instrumental variables (IVs) method is a leading empirical strategy for causal inference. Finding IVs is a heuristic and creative process, and justifying its validity -- especially exclusion restrictions -- is largely rhetorical. We propose using large language models (LLMs) to search for new IVs through narratives and counterfactual reasoning, similar to how a human researcher would. The stark difference, however, is that LLMs can dramatically accelerate this process and explore an extreme…

This https://arxiv.org/abs/2401.00510 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Smoothness Estimation for Whittle-Matérn Processes on Closed Riemannian Manifolds
The family of Matérn kernels are often used in spatial statistics, function approximation and Gaussian process methods in machine learning. One reason for their popularity is the presence of a smoothness parameter that controls, for example, optimal error bounds for kriging and posterior contraction rates in Gaussian process regression. On closed Riemannian manifolds, we show that the smoothness parameter can be consistently estimated from the maximizer(s) of the Gaussian likelihood when the u…

This https://arxiv.org/abs/2503.19136 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes
Poisson Surface Reconstruction is a widely-used algorithm for reconstructing a surface from an oriented point cloud. To facilitate applications where only partial surface information is available, or scanning is performed sequentially, a recent line of work proposes to incorporate uncertainty into the reconstructed surface via Gaussian process models. The resulting algorithms first perform Gaussian process interpolation, then solve a set of volumetric partial differential equations globally in …

This https://arxiv.org/abs/2504.17934 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Toward a Human-Centered Evaluation Framework for Trustworthy LLM-Powered GUI Agents
The rise of Large Language Models (LLMs) has revolutionized Graphical User Interface (GUI) automation through LLM-powered GUI agents, yet their ability to process sensitive data with limited human oversight raises significant privacy and security risks. This position paper identifies three key risks of GUI agents and examines how they differ from traditional GUI automation and general autonomous agents. Despite these risks, existing evaluations focus primarily on performance, leaving privacy an…

A Gaussian process approach for rapid evaluation of skin tension
Matt Nagle, Hannah Conroy Broderick, Christelle Vedel, Michel Destrade, Michael Fop, Aisling Ni Annaidh
https://arxiv.org/abs/2506.05118

A Gaussian process approach for rapid evaluation of skin tension
Skin tension plays a pivotal role in clinical settings, it affects scarring, wound healing and skin necrosis. Despite its importance, there is no widely accepted method for assessing in vivo skin tension or its natural pre-stretch. This study aims to utilise modern machine learning (ML) methods to develop a model that uses non-invasive measurements of surface wave speed to predict clinically useful skin properties such as stress and natural pre-stretch. A large dataset consisting of simulated w…

BREAKING: Judge Boasberg GRANTS class certification for the people held at CECOT
and gives the government ONE WEEK to explain how they're going to facilitate due process
for EVERYONE sent there under the Alien Enemies Act.
https://storage.court…

GP-Recipe: Gaussian Process approximation to linear operations in numerical methods
Christopher DeGrendele, Dongwook Lee
https://arxiv.org/abs/2506.03471 h…

GP-Recipe: Gaussian Process approximation to linear operations in numerical methods
We introduce new Gaussian Process (GP) high-order approximations to linear operations that are frequently used in various numerical methods. Our method employs the kernel-based GP regression modeling, a non-parametric Bayesian approach to regression that operates on the probability distribution over all admissible functions that fit observed data. We begin in the first part with discrete data approximations to various linear operators applied to smooth data using the most popular squared expone…

An interview with Runway CEO Cris Valenzuela on expediting the movie-making process, copyright cases, why using Runway is like using a camera, and more (Nilay Patel/The Verge)
https://www.theverge.com/decoder-podcast-w

Runway CEO Cris Valenzuela wants Hollywood to embrace AI video
The head of the AI video generation platform on copyright and the future of filmmaking.

Evaluating the Impact of Privacy-Preserving Federated Learning on CAN Intrusion Detection
Gabriele Digregorio, Elisabetta Cainazzo, Stefano Longari, Michele Carminati, Stefano Zanero
https://arxiv.org/abs/2506.04978

Evaluating the Impact of Privacy-Preserving Federated Learning on CAN Intrusion Detection
The challenges derived from the data-intensive nature of machine learning in conjunction with technologies that enable novel paradigms such as V2X and the potential offered by 5G communication, allow and justify the deployment of Federated Learning (FL) solutions in the vehicular intrusion detection domain. In this paper, we investigate the effects of integrating FL strategies into the machine learning-based intrusion detection process for on-board vehicular networks. Accordingly, we propose a …

SkimROOT: Accelerating LHC Data Filtering with Near-Storage Processing
Narangerelt Batsoyol, Jonathan Guiang, Diego Davila, Aashay Arora, Philip Chang, Frank W\"urthwein, Steven Swanson
https://arxiv.org/abs/2506.04507

SkimROOT: Accelerating LHC Data Filtering with Near-Storage Processing
Data analysis in high-energy physics (HEP) begins with data reduction, where vast datasets are filtered to extract relevant events. At the Large Hadron Collider (LHC), this process is bottlenecked by slow data transfers between storage and compute nodes. To address this, we introduce SkimROOT, a near-data filtering system leveraging Data Processing Units (DPUs) to accelerate LHC data analysis. By performing filtering directly on storage servers and returning only the relevant data, SkimROOT min…

This https://arxiv.org/abs/2408.03218 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Limit theorems for the number of crossings and stress in projections of the random geometric graph
We consider the number of edge crossings in a random graph drawing generated by projecting a random geometric graph on some compact convex set $W\subset \mathbb{R}^d$, $d\geq 3$, onto a plane. The positions of these crossings form the support of a point process. We show that if the expected number of crossings converges to a positive but finite value, this point process converges to a Poisson point process in the Kantorovich-Rubinstein distance. We further show a multivariate central limit theo…

Getting spam from companies like Newark or even smaller players like Win-Source is always weird to me.
Like, nothing you send me is going to change what parts I need for a design. And for a given part I'm going to pick from whatever distributor offers me the balance of (best price, shortest lead time, in stock, fastest shipping) that is appropriate for my needs.
Advertising changes nothing in that decision process.

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…

BVLSM: Write-Efficient LSM-Tree Storage via WAL-Time Key-Value Separation
Ming Li, Wendi Cheng, Jiahe Wei, Xueqiang Shan, Liu Weikai, Xiaonan Zhao, Xiao Zhang
https://arxiv.org/abs/2506.04678

BVLSM: Write-Efficient LSM-Tree Storage via WAL-Time Key-Value Separation
Modern data-intensive applications increasingly store and process big-value items, such as multimedia objects and machine learning embeddings, which exacerbate storage inefficiencies in Log-Structured Merge-Tree (LSM)-based key-value stores. This paper presents BVLSM, a Write-Ahead Log (WAL)-time key-value separation mechanism designed to address three key challenges in LSM-Tree storage systems: write amplification, poor memory utilization, and I/O jitter under big-value workloads. Unlike state…

A pictures says more than 1000 words. How much more can an audio representation of your data tell you? #rstats

sonify: Data Sonification - Turning Data into Sound
Sonification (or audification) is the process of representing data by sounds in the audible range. This package provides the R function sonify() that transforms univariate data, sampled at regular or irregular intervals, into a continuous sound with time-varying frequency. The ups and downs in frequency represent the ups and downs in the data. Sonify provides a substitute for R's plot function to simplify data analysis for the visually impaired.

Neural Networks for Parameter Estimation of the Discretely Observed Hawkes Process
Jason J. Lambe, Feng Chen, Tom Stindl, Tsz-Kit Jeffrey Kwan
https://arxiv.org/abs/2506.01258

Neural Networks for Parameter Estimation of the Discretely Observed Hawkes Process
When the sample path of a Hawkes process is observed discretely, such that only the total event counts in disjoint time intervals are known, the likelihood function becomes intractable. To overcome the challenge of likelihood-based inference in this setting, we propose to use a likelihood-free approach to parameter estimation, where a fully connected neural network (NN) is trained using simulated data to estimate the parameters of the Hawkes process from a summary statistic of the count data. A…

Rumors on evolving graphs through stationary times
Vicenzo Bonasorte
https://arxiv.org/abs/2506.04386 https://arxiv.org/pdf/2506.0438…

Rumors on evolving graphs through stationary times
We study rumor spreading in dynamic random graphs. Starting with a single informed vertex, the information flows until it reaches all the vertices of the graph (completion), according to the following process. At each step $k$, the information is propagated to neighbors of the informed vertices, in the $k$-th generated random graph. The way this information propagates from vertex to vertex at each step will depend on the ``protocol". We provide a method based on strong stationary times to study…

This https://arxiv.org/abs/2407.13257 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Predictive control for nonlinear stochastic systems: Closed-loop guarantees with unbounded noise
We present a stochastic model predictive control framework for nonlinear systems subject to unbounded process noise with closed-loop guarantees. First, we provide a conceptual shrinking-horizon framework that utilizes general probabilistic reachable sets and minimizes the expected cost. Then, we provide a tractable receding-horizon formulation that uses a nominal state to minimize a deterministic quadratic cost and satisfy tightened constraints. Our theoretical analysis demonstrates recursive f…

Hydrodynamic noise in one dimension: projected Kubo formula and its vanishing in integrable models
Benjamin Doyon
https://arxiv.org/abs/2506.05279 https://…

Hydrodynamic noise in one dimension: projected Kubo formula and its vanishing in integrable models
Hydrodynamic noise is the Gaussian process that emerges at larges scales of space and time in many-body systems. It arises by the central limit theorem applied to local microcanonical averages, representing the degrees of freedom that have been forgotten when projecting coarse-grained observables onto conserved quantities. It comes with "bare" diffusion terms. In one dimension of space, nonlinearities of the hydrodynamic equation are relevant (from a renormalisation perspective), usually giving…

The GAIN Model: A Nature-Inspired Neural Network Framework Based on an Adaptation of the Izhikevich Model
Gage K. R. Hooper
https://arxiv.org/abs/2506.04247

The GAIN Model: A Nature-Inspired Neural Network Framework Based on an Adaptation of the Izhikevich Model
While many neural networks focus on layers to process information, the GAIN model uses a grid-based structure to improve biological plausibility and the dynamics of the model. The grid structure helps neurons to interact with their closest neighbors and improve their connections with one another, which is seen in biological neurons. While also being implemented with the Izhikevich model this approach allows for a computationally efficient and biologically accurate simulation that can aid in the…

Exciton-Exciton Annihilation Mediated by Many-Body Coulomb and Phonon Interactions: An Ab Initio Study
Guy Vosco, Sivan Refaely-Abramson
https://arxiv.org/abs/2506.05223

Exciton-Exciton Annihilation Mediated by Many-Body Coulomb and Phonon Interactions: An Ab Initio Study
Exciton-exciton annihilation (EEA), in which two excitons interact to generate high-energy excitations, is an important non-radiative channel in light-induced excited-state relaxation. When efficient, this process offers an alternative route to exciton emission, potentially allowing extended energetically excited particles' lifetime and coherence. These properties are significant in designing and understanding materials-based quantum devices, particularly for low-dimensional semiconductors. Her…

NEAT and HyperNEAT based Design for Soft Actuator Controllers
Hugo Alcaraz-Herrera, Michail-Antisthenis Tsompanas, Igor Balaz, Andrew Adamatzky
https://arxiv.org/abs/2506.04698

NEAT and HyperNEAT based Design for Soft Actuator Controllers
Since soft robotics are composed of compliant materials, they perform better than conventional rigid robotics in specific fields, such as medical applications. However, the field of soft robotics is fairly new, and the design process of their morphology and their controller strategies has not yet been thoroughly studied. Consequently, here, an automated design method for the controller of soft actuators based on Neuroevolution is proposed. Specifically, the suggested techniques employ Neuroevol…

This https://arxiv.org/abs/2501.08301 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

A Disintegrating Rocky World Shrouded in Dust and Gas: Mid-IR Observations of K2-22b using JWST
The disintegrating ultra-short period rocky exoplanet K2-22b periodically emits dusty clouds in a dynamically chaotic process resulting in a variable transit depth from 0-1.3%. The effluents that sublimate off the surface and condense out in space are probably representative of the formerly interior layers convectively transported to the molten surface. Transmission spectroscopy of these transiting clouds reveal spectral fingerprints of the interior composition of this rocky world. We used JWST…

This https://arxiv.org/abs/2411.14622 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Learning Autonomous Surgical Irrigation and Suction with the da Vinci Research Kit Using Reinforcement Learning
The irrigation-suction process is a common procedure to rinse and clean up the surgical field in minimally invasive surgery (MIS). In this process, surgeons first irrigate liquid, typically saline, into the surgical scene for rinsing and diluting the contaminant, and then suction the liquid out of the surgical field. While recent advances have shown promising results in the application of reinforcement learning (RL) for automating surgical subtasks, fewer studies have explored the automation of…

Detailed Time Resolved Spectral and Temporal Investigations of SGR J1550-5418 Bursts Detected with Fermi/Gamma-ray Burst Monitor
Mustafa Demirer, Ersin G\"o\u{g}\"u\c{s}, Yuki Kaneko, \"Ozge Keskin, Sinem \c{S}a\c{s}maz, Shotaro Yamasaki
https://arxiv.org/abs/2506.04414

Detailed Time Resolved Spectral and Temporal Investigations of SGR J1550-5418 Bursts Detected with Fermi/Gamma-ray Burst Monitor
We have conducted a time-resolved spectral analysis of magnetar bursts originating from SGR J1550-5418. Our analysis utilizes a two-step methodology for temporal segmentation of the data. We first generated and fitted overlapping time segments. Subsequently, we obtained non-overlapping time segments with varying lengths based on their spectral evolution patterns, employing a machine learning algorithm called k-means clustering. For the fitting process, we employed three distinct models, namely …

This https://arxiv.org/abs/2409.09421 has been replaced.
initial toot: https://mastoxiv.page/@arXi…

One-way catalysis in a solvable lattice model
Catalysts speed up chemical reactions with no energy input and without being transformed in the process, therefore leaving equilibrium constants unchanged. Some catalysts, however, are much more efficient at accelerating one direction of a reaction. Is it possible for catalysis to be strictly unidirectional, accelerating only one direction of a reaction? Can we observe directional catalysis by analyzing the microscopic trajectory of a single reactant undergoing conversions between a substrate a…

Music writer, producer, and podcaster Dylan Tupper Rupert on envisioning alternatives
https://thecreativeindependent.com/peo

Music writer, producer, and podcaster Dylan Tupper Rupert on envisioning alternatives – The Creative Independent
Music writer, producer, and podcaster Dylan Tupper Rupert discusses growing up in the Seattle arts scene, dealing with music industry hierarchy, and imagining the ideal conditions for creativity.

systemd definitely does get many things right. My current favorite is how it sets the system resolver to loopback and provides an own DNS server.
Common Linux tradition was to tell processes to use getaddrinfo, where nsswitch then provides configurable backends. That means that every process goes through loading /etc/nsswitch.conf, but worse, it reduces DNS to a terrible subset. Query SVCB records? tough luck, you're on your own.

This https://arxiv.org/abs/2506.01222 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Learning collective variables that preserve transition rates
Collective variables (CVs) play a crucial role in capturing rare events in high-dimensional systems, motivating the continual search for principled approaches to their design. In this work, we revisit the framework of quantitative coarse graining and identify the orthogonality condition from Legoll and Lelievre (2010) as a key criterion for constructing CVs that accurately preserve the statistical properties of the original process. We establish that satisfaction of the orthogonality condition …

This https://arxiv.org/abs/2505.14613 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Virtual Cells: Predict, Explain, Discover
Drug discovery is fundamentally a process of inferring the effects of treatments on patients, and would therefore benefit immensely from computational models that can reliably simulate patient responses, enabling researchers to generate and test large numbers of therapeutic hypotheses safely and economically before initiating costly clinical trials. Even a more specific model that predicts the functional response of cells to a wide range of perturbations would be tremendously valuable for disco…

Process Mining on Distributed Data Sources
Maximilian Weisenseel, Julia Andersen, Samira Akili, Christian Imenkamp, Hendrik Reiter, Christoffer Rubensson, Wilhelm Hasselbring, Olaf Landsiedel, Xixi Lu, Jan Mendling, Florian Tschorsch, Matthias Weidlich, Agnes Koschmider
https://arxiv.org/abs/2506.02830

Process Mining on Distributed Data Sources
Major domains such as logistics, healthcare, and smart cities increasingly rely on sensor technologies and distributed infrastructures to monitor complex processes in real time. These developments are transforming the data landscape from discrete, structured records stored in centralized systems to continuous, fine-grained, and heterogeneous event streams collected across distributed environments. As a result, traditional process mining techniques, which assume centralized event logs from enter…

Large language models can learn and generalize steganographic chain-of-thought under process supervision
Joey Skaf, Luis Ibanez-Lissen, Robert McCarthy, Connor Watts, Vasil Georgiv, Hannes Whittingham, Lorena Gonzalez-Manzano, David Lindner, Cameron Tice, Edward James Young, Puria Radmard
https://arxiv.org/abs/2506.01926

Large language models can learn and generalize steganographic chain-of-thought under process supervision
Chain-of-thought (CoT) reasoning not only enhances large language model performance but also provides critical insights into decision-making processes, marking it as a useful tool for monitoring model intent and planning. By proactively preventing models from acting on CoT indicating misaligned or harmful intent, CoT monitoring can be used to reduce risks associated with deploying models. However, developers may be incentivized to train away the appearance of harmful intent from CoT traces, by …

High-linearity power amplifier based on GaAs HBT
Jiwei Huang, Yi Zhang
https://arxiv.org/abs/2506.04893 https://arxiv.org/pdf/2506.04…

High-linearity power amplifier based on GaAs HBT
This paper presents a power amplifier designed for Wi-Fi 6E using the 2 um gallium arsenide (GaAs) heterojunction bipolar transistor (HBT) process. By employing third-order inter-modulation signal cancellation, harmonic suppression, and an adaptive biasing scheme, the linearity performance of the circuit is improved. To achieve broadband performance, the power amplifier also incorporates gain distribution and multi-stage LC matching techniques. The measurement results indicate that, under a 5V …

An interview with Runway CEO Cris Valenzuela on expediting the movie-making process, copyright cases, why using Runway is like using a camera, and more (Nilay Patel/The Verge)
https://www.theverge.com/decoder-podcast-w

Runway CEO Cris Valenzuela wants Hollywood to embrace AI video
The head of the AI video generation platform on copyright and the future of filmmaking.

Biological Processes as Exploratory Dynamics
Jane Kondev, Marc Kirschner, Hernan G. Garcia, Gabriel L. Salmon, Rob Phillips
https://arxiv.org/abs/2506.04104

Biological Processes as Exploratory Dynamics
Many biological processes can be thought of as the result of an underlying dynamics in which the system repeatedly undergoes distinct and abortive trajectories with the dynamical process only ending when some specific process, purpose, structure or function is achieved. A classic example is the way in which microtubules attach to kinetochores as a prerequisite for chromosome segregation and cell division. In this example, the dynamics is characterized by apparently futile time histories in whic…

This https://arxiv.org/abs/2412.09429 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

From Intention To Implementation: Automating Biomedical Research via LLMs
Conventional biomedical research is increasingly labor-intensive due to the exponential growth of scientific literature and datasets. Artificial intelligence (AI), particularly Large Language Models (LLMs), has the potential to revolutionize this process by automating various steps. Still, significant challenges remain, including the need for multidisciplinary expertise, logicality of experimental design, and performance measurements. This paper introduces BioResearcher, the first end-to-end au…

This https://arxiv.org/abs/2308.12005 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Delay Update in determinant quantum Monte Carlo
Determinant quantum Monte Carlo (DQMC) is a widely used unbiased numerical method for simulating strongly correlated electron systems. However, the update process in DQMC is often a bottleneck for its efficiency. To address this issue, we propose a generalized delay update scheme that can handle both onsite and extended interactions. Our delay update scheme can be implemented in both zero-temperature and finite-temperature versions of DQMC. We apply the delay update scheme to various strongly c…

This https://arxiv.org/abs/2502.03498 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Controllable Satellite-to-Street-View Synthesis with Precise Pose Alignment and Zero-Shot Environmental Control
Generating street-view images from satellite imagery is a challenging task, particularly in maintaining accurate pose alignment and incorporating diverse environmental conditions. While diffusion models have shown promise in generative tasks, their ability to maintain strict pose alignment throughout the diffusion process is limited. In this paper, we propose a novel Iterative Homography Adjustment (IHA) scheme applied during the denoising process, which effectively addresses pose misalignment …

Never too many walkthroughs for a release. It may be a bit of overkill, but it works for us...
1. Pre-release the day before to go over the schedule of activities and assignments.
2. Schedule release and related backups.
3. Day of release and after schedule created for run another walkthrough to verify that the backups are where they need to be, checkpoints are there, start of the process is on manual hold.
4. Schedule an open teams call for the leads, devs and supp…

The neurological basis for non-visual illustration https://intellectdiscover.com/content/journals/10.1386/jill_00117_7 "this article poses the question of whether there is a theoretical precedent for creating visual imagery in the minds of blind peopl…

This https://arxiv.org/abs/2405.08965 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Meaning-Typed Programming: Language Abstraction and Runtime for Model-Integrated Applications
Software development is shifting from traditional logical programming to model-integrated applications that leverage generative AI and large language models (LLMs) during runtime. However, integrating LLMs remains complex, requiring developers to manually craft prompts and process outputs. Existing tools attempt to assist with prompt engineering, but often introduce additional complexity. This paper presents Meaning-Typed Programming (MTP) model, a novel paradigm that abstracts LLM integratio…

Mind the Gap: A Formal Investigation of the Relationship Between Log and Model Complexity -- Extended Version
Patrizia Schalk, Artem Polyvyanyy
https://arxiv.org/abs/2505.23233

Mind the Gap: A Formal Investigation of the Relationship Between Log and Model Complexity -- Extended Version
Simple process models are key for effectively communicating the outcomes of process mining. An important question in this context is whether the complexity of event logs used as inputs to process discovery algorithms can serve as a reliable indicator of the complexity of the resulting process models. Although various complexity measures for both event logs and process models have been proposed in the literature, the relationship between input and output complexity remains largely unexplored. In…

Maybe some Linux Kernel expert could help me with this:
Due to the nature of my work, I regularily run a very memory intensive process and my system runs out of memory during very few peak moments.
The system can't swap out memory fast enough and freezes. If I disable swap, the process gets killed instead.
Is there any way I can keep the system responsive? Ideally, only the offending process would get slowed down, but not other applications.

This https://arxiv.org/abs/2505.20863 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Leveraging Diffusion Models for Parameterized Quantum Circuit Generation
Quantum computing holds immense potential, yet its practical success depends on multiple factors, including advances in quantum circuit design. In this paper, we introduce a generative approach based on denoising diffusion models (DMs) to synthesize parameterized quantum circuits (PQCs). Extending the recent diffusion model pipeline of Fürrutter et al. [1], our model effectively conditions the synthesis process, enabling the simultaneous generation of circuit architectures and their continuous…

Automated Mechanism to Support Trade Transactions in Smart Contracts with Upgrade and Repair
Christian Gang Liu, Peter Bodorik, Dawn Jutla
https://arxiv.org/abs/2506.03877

Automated Mechanism to Support Trade Transactions in Smart Contracts with Upgrade and Repair
In our previous research, we addressed the problem of automated transformation of models, represented using the business process model and notation (BPMN) standard, into the methods of a smart contract. The transformation supports BPMN models that contain complex multi-step activities that are supported using our concept of multi-step nested trade transactions, wherein the transactional properties are enforced by a mechanism generated automatically by the transformation process from a BPMN mode…

Neural Jumps for Option Pricing
Duosi Zheng, Hanzhong Guo, Yanchu Liu, Wei Huang
https://arxiv.org/abs/2506.05137 https://arxiv.org/p…

Neural Jumps for Option Pricing
Recognizing the importance of jump risk in option pricing, we propose a neural jump stochastic differential equation model in this paper, which integrates neural networks as parameter estimators in the conventional jump diffusion model. To overcome the problem that the backpropagation algorithm is not compatible with the jump process, we use the Gumbel-Softmax method to make the jump parameter gradient learnable. We examine the proposed model using both simulated data and S&P 500 index options.…

BREAKING: Trump admin must process education grants "without delay" (Adam Klasfeld/All Rise News)
https://www.allrisenews.com/p/linda-mcmahon-grants
http://www.memeorandum.com/250603/p138#a250603p138

This https://arxiv.org/abs/2503.16920 has been replaced.
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Assessing AI Explainability: A Usability Study Using a Novel Framework Involving Clinicians
An AI design framework was developed based on three core principles, namely understandability, trust, and usability. The framework was conceptualized by synthesizing evidence from the literature and by consulting with experts. The initial version of the AI Explainability Framework was validated based on an in-depth expert engagement and review process. For evaluation purposes, an AI-anchored prototype, incorporating novel explainability features, was built and deployed online. The primary funct…

Reactive Transport Simulation of Silicate-Rich Shale Rocks when Exposed to CO2 Saturated Brine Under High Pressure and High Temperature
Shaziya A. Banu, Venkata R. S. B. Varanasi, Arash Noshadravan, Sara Abedi
https://arxiv.org/abs/2506.05122

Reactive Transport Simulation of Silicate-Rich Shale Rocks when Exposed to CO2 Saturated Brine Under High Pressure and High Temperature
This study examines the feasibility of carbon dioxide storage in shale rocks and the reliability of reactive transport models in achieving accurate replication of the chemo-mechanical interactions and transport processes transpiring in these rocks when subjected to CO2 saturated brine. Owing to the heterogeneity of rocks, experimental testing for adequate deductions and findings, could be an expensive and time-intensive process. Therefore, this study proposes utilization of reactive transport m…

This https://arxiv.org/abs/2505.09999 has been replaced.
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ServeGen: Workload Characterization and Generation of Large Language Model Serving in Production
With the widespread adoption of Large Language Models (LLMs), serving LLM inference requests has become an increasingly important task, attracting active research advancements. Practical workloads play an essential role in this process: they are critical for motivating and benchmarking serving techniques and systems. However, the existing understanding of real-world LLM serving workloads is limited due to the lack of a comprehensive workload characterization. Prior analyses remain insufficient …

Cohomology of hypersurfaces of weighted projective space and the intersection form on $H^2$
Anna-Maria Raukh
https://arxiv.org/abs/2506.04094 https://

Cohomology of hypersurfaces of weighted projective space and the intersection form on $H^2$
Given a hypersurface $i \colon X \hookrightarrow \widetilde{P}^n$ in a weighted projective space, we compute the intersection form on the second cohomology $H^2(X, \mathbb{Z})^{\otimes n-1} \to \mathbb{Z}$ for the purpose of identifying Fano manifolds obtained from smoothing singular Fanos. In the process, we describe the integer cohomology groups $H^k(X, \mathbb{Z})$ for $k

Influence of photon inverse emission on forward-backward asymmetry in dilepton production at LHC
Vladimir Zykunov
https://arxiv.org/abs/2506.03736 https://…

Influence of photon inverse emission on forward-backward asymmetry in dilepton production at LHC
Contribution of photon inverse emission to the dilepton production process in hadron collisions for Large Hadron Collider (LHC) experimental program is calculated in details. Numerical analysis of inverse emission effects on observable quantities (cross sections and forward-backward asymmetry) is performed in a wide kinematical region including the CMS LHC experiment in Run3/HL regime which corresponds to ultra-high energies and dilepton invariant masses. Effective technics of additive relative…

This https://arxiv.org/abs/2308.03734 has been replaced.
link: https://scholar.google.com/scholar?q=a

Labeling without Seeing? Blind Annotation for Privacy-Preserving Entity Resolution
The entity resolution problem requires finding pairs across datasets that belong to different owners but refer to the same entity in the real world. To train and evaluate solutions (either rule-based or machine-learning-based) to the entity resolution problem, generating a ground truth dataset with entity pairs or clusters is needed. However, such a data annotation process involves humans as domain oracles to review the plaintext data for all candidate record pairs from different parties, which…

This https://arxiv.org/abs/2412.20113 has been replaced.
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Intrinsic noise in structured replicator dynamics modelling time delays
We construct and analyze structured replicator dynamics of the Snowdrift game. In our model, the offspring is put in juvenile compartments and then mature and join adult compartments with strategy-dependent rates. This is augmented by death rates and hence the population size is bounded. In the corresponding birth-death Markov jump process, rates of leaving juvenile compartments may be interpreted as inverses of averages of exponentially distributed time delays. We observe a novel behavior: for…

Estimating dynamic transmission rates with a Black-Karasinski process in stochastic SIHR models using particle MCMC
Avery Drennan, Jeffrey Covington, Dan Han, Andrew Attilio, Jaechoul Lee, Richard Posner, Eck Doerry, Joseph Mihaljevic, Ye Chen
https://arxiv.org/abs/2505.24127

Estimating dynamic transmission rates with a Black-Karasinski process in stochastic SIHR models using particle MCMC
Compartmental models are effective in modeling the spread of infectious pathogens, but have remaining weaknesses in fitting to real datasets exhibiting stochastic effects. We propose a stochastic SIHR model with a dynamic transmission rate, where the rate is modeled by the Black-Karasinski (BK) process - a mean-reverting stochastic process with a stable equilibrium distribution, making it well-suited for modeling long-term epidemic dynamics. To generate sample paths of the BK process and estima…

From this year on, ESWC will be under the umbrella of SWSA, the Semantic Web Science Association, to secure financial sustainability for the upcoming years after its previous supporting organisation STI was dissolved in 2023. Basics about the transition are given by Elena Simperl, president of SWSA.
https://swsa.semanticweb.org/

This https://arxiv.org/abs/2504.01483 has been replaced.
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GarmageNet: A Multimodal Generative Framework for Sewing Pattern Design and Generic Garment Modeling
Realistic digital garment modeling remains a labor-intensive task due to the intricate process of translating 2D sewing patterns into high-fidelity, simulation-ready 3D garments. We introduce GarmageNet, a unified generative framework that automates the creation of 2D sewing patterns, the construction of sewing relationships, and the synthesis of 3D garment initializations compatible with physics-based simulation. Central to our approach is Garmage, a novel garment representation that encodes e…

Rate constants and product yields for the C CH3CHO reaction at low temperatures
Kevin M. Hickson, Jean-Christophe Loison, Valentine Wakelam
https://arxiv.org/abs/2506.04794

Rate constants and product yields for the C + CH3CHO reaction at low temperatures
Reactions involving atomic carbon in its ground electronic state, C(3P), play an important role in astrochemistry due to high C-atom abundance levels. Here we performed a kinetic investigation of the reaction between C(3P) and acetaldehyde, CH3CHO, determining rate constants for this process over the 50-296 K range. Measurements of the formation of atomic hydrogen, H(2S), were also performed to provide insight into product formation. Experiments were conducted using a supersonic flow reactor co…

Modelling the evolution of flow-induced anisotropy of concentrated suspensions
Pappu Acharya, Romain Mari
https://arxiv.org/abs/2506.05222 https://

Modelling the evolution of flow-induced anisotropy of concentrated suspensions
Suspensions, which exhibit complex behaviors such as shear thickening, thinning, and jamming, are prevalent in nature and industry. However, predicting the mechanical properties of concentrated suspensions, in both steady state and the transient regime, remains a significant challenge, impacting product quality and process efficiency. In this study, we focus on developing a robust theoretical framework to explain how flow history governs the anisotropy of mechanical responses in suspensions of …

Leveraging Reward Models for Guiding Code Review Comment Generation
Oussama Ben Sghaier, Rosalia Tufano, Gabriele Bavota, Houari Sahraoui
https://arxiv.org/abs/2506.04464

Leveraging Reward Models for Guiding Code Review Comment Generation
Code review is a crucial component of modern software development, involving the evaluation of code quality, providing feedback on potential issues, and refining the code to address identified problems. Despite these benefits, code review can be rather time consuming, and influenced by subjectivity and human factors. For these reasons, techniques to (partially) automate the code review process have been proposed in the literature. Among those, the ones exploiting deep learning (DL) are able to …

This https://arxiv.org/abs/2502.11753 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

HintsOfTruth: A Multimodal Checkworthiness Detection Dataset with Real and Synthetic Claims
Misinformation can be countered with fact-checking, but the process is costly and slow. Identifying checkworthy claims is the first step, where automation can help scale fact-checkers' efforts. However, detection methods struggle with content that is (1) multimodal, (2) from diverse domains, and (3) synthetic. We introduce HintsOfTruth, a public dataset for multimodal checkworthiness detection with 27K real-world and synthetic image/claim pairs. The mix of real and synthetic data makes this dat…

This https://arxiv.org/abs/2503.09117 has been replaced.
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GRU: Mitigating the Trade-off between Unlearning and Retention for Large Language Models
Large language model (LLM) unlearning has demonstrated its essential role in removing privacy and copyright-related responses, crucial for their legal and safe applications. However, the pursuit of complete unlearning often comes with substantial costs due to its compromises in their general functionality, leading to a notorious trade-off between unlearning and retention. In examining the update process for unlearning dynamically, we find gradients hold essential information for revealing this …

This https://arxiv.org/abs/2410.05740 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Learning to Drift in Extreme Turning with Active Exploration and Gaussian Process Based MPC
Extreme cornering in racing often leads to large sideslip angles, presenting a significant challenge for vehicle control. Conventional vehicle controllers struggle to manage this scenario, necessitating the use of a drifting controller. However, the large sideslip angle in drift conditions introduces model mismatch, which in turn affects control precision. To address this issue, we propose a model correction drift controller that integrates Model Predictive Control (MPC) with Gaussian Process R…

This https://arxiv.org/abs/2404.05836 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Hiden Topics in Robotic Process Automation -- an Approach based on AI
Robotic Process Automation (RPA) has rapidly evolved into a widely recognized and influential software technology. Its growing relevance has sparked diverse research efforts across various disciplines. This study aims to map the scientific landscape of RPA by identifying key thematic areas, tracking their development over time, and assessing their academic impact. To achieve this, we apply an unsupervised machine learning technique Latent Dirichlet Allocation (LDA) to analyze the abstracts of o…

2D PZT MEMS Resonant Scanner Using a Three-Mask Process
Mehrdad Khodapanahandeh, Parviz Zolfaghari, Hakan Urey
https://arxiv.org/abs/2505.24566 https://

2D PZT MEMS Resonant Scanner Using a Three-Mask Process
This work presents the design, simulation, fabrication, and characterization of a novel architectural compact two-dimensional (2D) resonant MEMS scanning mirror actuated by thin-film lead zirconate titanate (PZT). The device employs an innovative mechanically coupled dual-axis architecture fabricated using a three-mask process on an SOI-PZT deposited wafer, significantly reducing system complexity while achieving high performance. The scanner integrates a 1 $\times$ 1.4 mm oval mirror within a …

Clues for Solar System Formation from Meteorites and their Parent Bodies
Bernard Marty, Katherine R. Bermingham, Larry R. Nittler, Sean N. Raymond
https://arxiv.org/abs/2506.02721

Clues for Solar System Formation from Meteorites and their Parent Bodies
Understanding the origin of comets requires knowledge of how the Solar System formed from a cloud of dust and gas 4.567 Gyr ago. Here, a review is presented of how the remnants of this formation process, meteorites and to a lesser extent comets, shed light on Solar System evolution. The planets formed by a process of collisional agglomeration during the first hundred million years of Solar System history. The vast majority of the original population of planetary building blocks (~100 km-scale p…

This https://arxiv.org/abs/2412.15969 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On cutoff via rigidity for high dimensional curved diffusions
We consider overdamped Lanvegin diffusions in Euclidean space, with curvature equal to the spectral gap. This includes the Ornstein-Uhlenbeck process as well as non Gaussian and non product extensions with convex interaction, such as the Dyson process from random matrix theory. We show that a cutoff phenomenon or abrupt convergence to equilibrium occurs in high-dimension, at a critical time equal to the logarithm of the dimension divided by twice the spectral gap. This cutoff holds for Wasserst…

This https://arxiv.org/abs/2502.03498 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Controllable Satellite-to-Street-View Synthesis with Precise Pose Alignment and Zero-Shot Environmental Control
Generating street-view images from satellite imagery is a challenging task, particularly in maintaining accurate pose alignment and incorporating diverse environmental conditions. While diffusion models have shown promise in generative tasks, their ability to maintain strict pose alignment throughout the diffusion process is limited. In this paper, we propose a novel Iterative Homography Adjustment (IHA) scheme applied during the denoising process, which effectively addresses pose misalignment …

Heavy Neutral Lepton Decay Searches using Solar Neutrinos
Patrick Huber, Yulun Li
https://arxiv.org/abs/2506.04099 https://arxiv.org/…

Heavy Neutral Lepton Decay Searches using Solar Neutrinos
We study the sensitivity to the decay of a heavy neutral lepton into $e^+e^-$-pairs using the solar boron-8 neutrino flux as source. We provide a fully differential cross section for this process including the interference of neutral and charged current amplitudes. We revisit a previous bound from Borexino and make predicitions for the expected sensitivity in future large liquid noble gas detectors, like XLZD, Argo and DUNE, as well as high-resolution scintillator detectors based on the LiquidO…

This https://arxiv.org/abs/2411.15983 has been replaced.
initial toot: https://mastoxiv.page/@a…

Why Grain Growth is Not Curvature Flow
Grain growth in polycrystals is traditionally considered a capillarity-driven process, where grain boundaries (GBs) migrate toward their centers of curvature (i.e., mean curvature flow) with a velocity proportional to the local curvature (including extensions to account for anisotropic GB energy and mobility). Experimental and simulation evidence shows that this simplistic view is untrue. We demonstrate that the failure of the classical mean curvature flow description of grain growth mainly ori…

This https://arxiv.org/abs/2405.14492 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Iterative Methods for Full-Scale Gaussian Process Approximations for Large Spatial Data
Gaussian processes are flexible probabilistic regression models which are widely used in statistics and machine learning. However, a drawback is their limited scalability to large data sets. To alleviate this, full-scale approximations (FSAs) combine predictive process methods and covariance tapering, thus approximating both global and local structures. We show how iterative methods can be used to reduce computational costs in calculating likelihoods, gradients, and predictive distributions wit…

This https://arxiv.org/abs/2505.00237 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Future-Oriented Navigation: Dynamic Obstacle Avoidance with One-Shot Energy-Based Multimodal Motion Prediction
This paper proposes an integrated approach for the safe and efficient control of mobile robots in dynamic and uncertain environments. The approach consists of two key steps: one-shot multimodal motion prediction to anticipate motions of dynamic obstacles and model predictive control to incorporate these predictions into the motion planning process. Motion prediction is driven by an energy-based neural network that generates high-resolution, multi-step predictions in a single operation. The pred…

Apple says it is appealing the EU's iOS interoperability order under the DMA that creates "a process that is unreasonable, costly, and stifles innovation" (Edith Hancock/Wall Street Journal)
https://www.

Supporting Long-term Transactions in Smart Contracts Generated from Business Process Model and Notation (BPMN) Models
Christian Gang Liu
https://arxiv.org/abs/2505.24309

Supporting Long-term Transactions in Smart Contracts Generated from Business Process Model and Notation (BPMN) Models
To alleviate difficulties in writing smart contracts for distributed blockchain applications, as other research, we propose transformation of Business Process Model and Notation (BPMN) models into blockchain smart contracts. Unlike other research, we use Discrete Event Hierarchical State Machine (DE-HSM) multi-modal modeling to identify collaborative trade transactions that need to be supported by the smart contract and describe how the trade transactions, that may be nested, are supported by a…

Analysis of Server Throughput For Managed Big Data Analytics Frameworks
Emmanouil Anagnostakis, Polyvios Pratikakis
https://arxiv.org/abs/2506.03854 https:…

Analysis of Server Throughput For Managed Big Data Analytics Frameworks
Managed big data frameworks, such as Apache Spark and Giraph demand a large amount of memory per core to process massive volume datasets effectively. The memory pressure that arises from the big data processing leads to high garbage collection (GC) overhead. Big data analytics frameworks attempt to remove this overhead by offloading objects to storage devices. At the same time, infrastructure providers, trying to address the same problem, attribute more memory to increase memory per instance le…

Design of a visual environment for programming by direct data manipulation
Michel Adam (UBS, IRISA), Patrice Frison (UBS, IRISA), Moncef Daoud (UBS), Sabine Letellier Zarshenas (UBS)
https://arxiv.org/abs/2506.03720

Design of a visual environment for programming by direct data manipulation
The use of applications on computers, smartphones, and tablets has been considerably simplified thanks to interactive and dynamic graphical interfaces coupled with the mouse and touch screens. It is no longer necessary to be a computer specialist to use them. Paradoxically, the development of computer programs generally requires writing lines of code in a programming language whose syntax is particularly strict. This process poses many difficulties for programmers. We propose an original tool i…

Finitary codings and stochastic domination for Poisson representable processes
Yinon Spinka
https://arxiv.org/abs/2506.04797 https://…

Finitary codings and stochastic domination for Poisson representable processes
Construct a random set by independently selecting each finite subset of the integers with some probability depending on the set up to translations and taking the union of the selected sets. We show that when the only sets selected with positive probability are pairs, such a random set is a finitary factor of an IID process, answering a question of Forsström, Gantert and Steif. More generally, we show that this is the case whenever the distribution induced by the size of the selected sets has s…

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…

Enhancing Spatio-Temporal Resolution of Process-Based Life Cycle Analysis with Model-Based Systems Engineering \& Hetero-functional Graph Theory
Niraj Gohil, Nawshad Haque, Amgad Elgowainy, Amro M. Farid
https://arxiv.org/abs/2506.00230

Enhancing Spatio-Temporal Resolution of Process-Based Life Cycle Analysis with Model-Based Systems Engineering \& Hetero-functional Graph Theory
Life cycle analysis (LCA) has emerged as a vital tool for assessing the environmental impacts of products, processes, and systems throughout their entire lifecycle. It provides a systematic approach to quantifying resource consumption, emissions, and waste, enabling industries, researchers, and policymakers to identify hotspots for sustainability improvements. By providing a comprehensive assessment of systems, from raw material extraction to end-of-life disposal, LCA facilitates the developmen…

This https://arxiv.org/abs/2411.16967 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

A Review of Design Concerns in Superconducting Quantum Circuits
In this short review we describe the process of designing a superconducting circuit device for quantum information applications. We discuss the factors that must be considered to implement a desired effective Hamiltonian on a device. We describe the translation between a device's physical layout, the circuit graph, and the effective Hamiltonian. We go over the process of electromagnetic simulation of a device layout to predict its behavior. We also discuss concerns such as connectivity, crossta…

This https://arxiv.org/abs/2505.20573 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Collision- and Reachability-Aware Multi-Robot Control with Grounded LLM Planners
Large language models (LLMs) have demonstrated strong performance in various robot control tasks. However, their deployment in real-world applications remains constrained. Even state-ofthe-art LLMs, such as GPT-o4mini, frequently produce invalid action plans that violate physical constraints, such as directing a robot to an unreachable location or causing collisions between robots. This issue primarily arises from a lack of awareness of these physical constraints during the reasoning process. T…

Interpretable Spatio-Temporal Features Extraction based Industrial Process Modeling and Monitoring by Soft Sensor
Qianchao Wang, Peng Sha, Leena Heistrene, Yuxuan Ding, Yaping Du
https://arxiv.org/abs/2506.00858

Interpretable Spatio-Temporal Features Extraction based Industrial Process Modeling and Monitoring by Soft Sensor
Data-driven soft sensors have been widely applied in complex industrial processes. However, the interpretable spatio-temporal features extraction by soft sensors remains a challenge. In this light, this work introduces a novel method termed spatio-temporal consistent and interpretable model (STCIM). First, temporal and spatial features are captured and aligned by a far topological spatio-temporal consistency extraction block. Then, the features are mapped into an interpretable latent space for …

Improving LLM-Based Fault Localization with External Memory and Project Context
Inseok Yeo, Duksan Ryu, Jongmoon Baik
https://arxiv.org/abs/2506.03585 http…

Improving LLM-Based Fault Localization with External Memory and Project Context
Fault localization, the process of identifying the software components responsible for failures, is essential but often time-consuming. Recent advances in Large Language Models (LLMs) have enabled fault localization without extensive defect datasets or model fine-tuning. However, existing LLM-based methods rely only on general LLM capabilities and lack integration of project-specific knowledge, resulting in limited effectiveness, especially for complex software. We introduce MemFL, a novel ap…

An Integrated Platform for LEED Certification Automation Using Computer Vision and LLM-RAG
Jooyeol Lee
https://arxiv.org/abs/2506.00888 https://

An Integrated Platform for LEED Certification Automation Using Computer Vision and LLM-RAG
The Leadership in Energy and Environmental Design (LEED) certification process is characterized by labor-intensive requirements for data handling, simulation, and documentation. This paper presents an automated platform designed to streamline key aspects of LEED certification. The platform integrates a PySide6-based user interface, a review Manager for process orchestration, and multiple analysis engines for credit compliance, energy modeling via EnergyPlus, and location-based evaluation. Key c…

This https://arxiv.org/abs/2503.04149 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination
The rapid evolution of code largelanguage models underscores the need for effective and transparent benchmarking of their reasoning capabilities. However, the current benchmarking approach heavily depends on publicly available, human-created datasets. The widespread use of these fixed benchmark datasets makes the benchmarking process to be static and thus particularly susceptible to data contamination, an unavoidable consequence of the extensive data collection processes used to train Code LLMs…