Tootfinder

Microsoft and the NFL extend their partnership to bring real-time game data and analysis to coaches and players using Microsoft Copilot and Azure AI (Ali McCadden/CNBC)
https://www.cnbc.com/2025/08/20/microsoft-nfl-ai-analysis.html

Microsoft and NFL announce multiyear partnership to use AI to enhance game day analysis
Microsoft and the NFL announced a multiyear extension of their partnership to bring real-time analysis to the sidelines using Microsoft Copilot and Azure AI.

Fantasy football draft rankings 2025: Quarterback tiers and analysis https://www.nfl.com/news/fantasy-football-draft-rankings-2025-quarterback-tiers-and-analysis

Sequential analysis in a continuous spin-noise quantum sensor
Elisabet Roda-Salichs, Giulio Gasbarri, Antoni Alou, Michalis Skotiniotis, Aleksandra Sierant, Diana M\'endez-Avalos, Morgan W. Mitchell, John Calsamiglia
https://arxiv.org/abs/2509.16177

Sequential analysis in a continuous spin-noise quantum sensor
Many control and detection applications require real-time analysis of signals from sensors, in order to quickly and accurately act upon events revealed by the sensors. Such signal analysis benefits from statistical models of signal and sensor behavior. This creates a need for data analysis methods that are simultaneously model-based, computationally efficient and causal, in the sense that they employ only sensor data available prior to a specific point in time. In this work, we implement sequen…

Oh no it happened - client for a research project I’m working on got upset that we’re doing manual data analysis of survey responses, and complained about why we are so slow when their internal team working on a different report got “everything done in a couple of days with #AI tools”
And then they told us that waiting for proper human analysis is a “waste of time” and that we need to just chuck our dataset into AI and “get it over with”
I really don’t know what to do right now 🥲
Trying to do this properly on their expected timeline will mean very little sleep for multiple days, but giving up on the project quality and dumping it into AI is will make this entire project a waste of time. (As I wouldn’t be able to trust the output of the analysis, or be proud of it to showcase the final report as an example of our work, and not to mention that I don’t want to support this expectation to rush everything at work with these AI models)

Breezy Analysis: Drew Brees, Charles Woodson Break Down the Best Journeymen QBs https://www.foxsports.com/stories/nfl/breezy-analysis-what-drew-brees-charles-woodson-make-journeymen-qbs

ETrace:Event-Driven Vulnerability Detection in Smart Contracts via LLM-Based Trace Analysis
Chenyang Peng, Haijun Wang, Yin Wu, Hao Wu, Ming Fan, Yitao Zhao, Ting Liu
https://arxiv.org/abs/2506.15790

ETrace:Event-Driven Vulnerability Detection in Smart Contracts via LLM-Based Trace Analysis
With the advance application of blockchain technology in various fields, ensuring the security and stability of smart contracts has emerged as a critical challenge. Current security analysis methodologies in vulnerability detection can be categorized into static analysis and dynamic analysis methods.However, these existing traditional vulnerability detection methods predominantly rely on analyzing original contract code, not all smart contracts provide accessible code.We present ETrace, a novel…

FCC to eliminate gigabit speed goal and scrap analysis of broadband prices (Jon Brodkin/Ars Technica)
https://arstechnica.com/tech-policy/2025/07/fcc-to-eliminate-gigabit-speed-goal-and-scrap-analysis-of-broadband-prices/
http://www.memeorandum.com/250722/p3#a250722p3

A simulated attack that exploits Claude's inability to verify the true origin of a message received through iMessage allowed General Analysis LLM researchers to create a $50,000 Stripe coupon.
https://www.generalanalysis.com/blog/imessage-stripe-exploit

Foundation Models for Cross-Domain EEG Analysis Application: A Survey
Hongqi Li, Yitong Chen, Yujuan Wang, Weihang Ni, Haodong Zhang
https://arxiv.org/abs/2508.15716 https://

Foundation Models for Cross-Domain EEG Analysis Application: A Survey
Electroencephalography (EEG) analysis stands at the forefront of neuroscience and artificial intelligence research, where foundation models are reshaping the traditional EEG analysis paradigm by leveraging their powerful representational capacity and cross-modal generalization. However, the rapid proliferation of these techniques has led to a fragmented research landscape, characterized by diverse model roles, inconsistent architectures, and a lack of systematic categorization. To bridge this g…

Graphical Analysis of Nonlinear Multivariable Feedback Systems
Julius P. J. Krebbekx, Roland T\'oth, Amritam Das
https://arxiv.org/abs/2507.16513 https…

Graphical Analysis of Nonlinear Multivariable Feedback Systems
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. There have been recent efforts to generalize SRG analysis to Multiple-Input Multiple-Output (MIMO) systems. However, these attempts yielded only results for square systems, and in some cases, only methods applicable for Linear Time-Invariant (LTI) systems. In this paper, we develop a complete SRG framework for the analysis of MIMO systems, which may be nonlinear and non-square.…

DESI DR1 Ly$\alpha$ forest: 3D full-shape analysis and cosmological constraints
Andrei Cuceu, Hiram K. Herrera-Alcantar, Calum Gordon, C\'esar Ram\'irez-P\'erez, E. Armengaud, A. Font-Ribera, J. Guy, B. Joachimi, P. Martini, S. Nadathur, I. P\'erez-R\`afols, J. Rich, J. Aguilar, S. Ahlen, A. Anand, S. Bailey, A. Bault, D. Bianchi, A. Brodzeller, D. Brooks, J. Chaves-Montero, T. Claybaugh, K. S. Dawson, A. de la Macorra, J. Della Costa, P. Doel, S. Ferraro, J. E. Forero-…

DESI DR1 Ly$α$ forest: 3D full-shape analysis and cosmological constraints
We perform an analysis of the full shapes of Lyman-$α$ (Ly$α$) forest correlation functions measured from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). Our analysis focuses on measuring the Alcock-Paczynski (AP) effect and the cosmic growth rate times the amplitude of matter fluctuations in spheres of $8$ $h^{-1}\text{Mpc}$, $fσ_8$. We validate our measurements using two different sets of mocks, a series of data splits, and a large set of analysis variation…

MicroRCA-Agent: Microservice Root Cause Analysis Method Based on Large Language Model Agents
Pan Tang, Shixiang Tang, Huanqi Pu, Zhiqing Miao, Zhixing Wang
https://arxiv.org/abs/2509.15635

MicroRCA-Agent: Microservice Root Cause Analysis Method Based on Large Language Model Agents
This paper presents MicroRCA-Agent, an innovative solution for microservice root cause analysis based on large language model agents, which constructs an intelligent fault root cause localization system with multimodal data fusion. The technical innovations are embodied in three key aspects: First, we combine the pre-trained Drain log parsing algorithm with multi-level data filtering mechanism to efficiently compress massive logs into high-quality fault features. Second, we employ a dual anomal…

"Google contends these [artificial intelligence]-based answers don't take traffic away from websites, but a new analysis from the Pew Research Center says otherwise. Its analysis shows that searches with AI summaries reduce clicks, and their prevalence is increasing."
https://

Surprising no one, new research says AI Overviews cause massive drop in search clicks
The Pew Research Center analysis shows how hard AI is hitting web traffic.

GALE: Leveraging Heterogeneous Systems for Efficient Unstructured Mesh Data Analysis
Guoxi Liu, Thomas Randall, Rong Ge, Federico Iuricich
https://arxiv.org/abs/2507.15230

GALE: Leveraging Heterogeneous Systems for Efficient Unstructured Mesh Data Analysis
Unstructured meshes present challenges in scientific data analysis due to irregular distribution and complex connectivity. Computing and storing connectivity information is a major bottleneck for visualization algorithms, affecting both time and memory performance. Recent task-parallel data structures address this by precomputing connectivity information at runtime while the analysis algorithm executes, effectively hiding computation costs and improving performance. However, existing approaches…

Let's Measure the Elephant in the Room: Facilitating Personalized Automated Analysis of Privacy Policies at Scale
Rui Zhao, Vladyslav Melnychuk, Jun Zhao, Jesse Wright, Nigel Shadbolt
https://arxiv.org/abs/2507.14214

Let's Measure the Elephant in the Room: Facilitating Personalized Automated Analysis of Privacy Policies at Scale
In modern times, people have numerous online accounts, but they rarely read the Terms of Service or Privacy Policy of those sites despite claiming otherwise. This paper introduces PoliAnalyzer, a neuro-symbolic system that assists users with personalized privacy policy analysis. PoliAnalyzer uses Natural Language Processing (NLP) to extract formal representations of data usage practices from policy texts. In favor of deterministic, logical inference is applied to compare user preferences with t…

Large-dimensional Factor Analysis with Weighted PCA
Zhongyuan Lyu, Ming Yuan
https://arxiv.org/abs/2508.15675 https://arxiv.org/pdf/2508.15675

Large-dimensional Factor Analysis with Weighted PCA
Principal component analysis (PCA) is arguably the most widely used approach for large-dimensional factor analysis. While it is effective when the factors are sufficiently strong, it can be inconsistent when the factors are weak and/or the noise has complex dependence structure. We argue that the inconsistency often stems from bias and introduce a general approach to restore consistency. Specifically, we propose a general weighting scheme for PCA and show that with a suitable choice of weightin…

Time-Optimal Directed q-Analysis
Felix Windisch, Florian Unger
https://arxiv.org/abs/2508.15583 https://arxiv.org/pdf/2508.15583

Time-Optimal Directed q-Analysis
Directed q-analysis is a recent extension of q-analysis, an established method for extracting structure from networks, to directed graphs. Until recently, a lack of efficient algorithms heavily restricted the application of this technique: Previous approaches scale with the square of the input size, which is also the maximal size of the output, rendering such approaches worst-case optimal. In practice, output sizes of relevant networks are usually far from the worst case, a fact that could be e…

XAI-Driven Spectral Analysis of Cough Sounds for Respiratory Disease Characterization
Patricia Amado-Caballero, Luis Miguel San-Jos\'e-Revuelta, Mar\'ia Dolores Aguilar-Garc\'ia, Jos\'e Ram\'on Garmendia-Leiza, Carlos Alberola-L\'opez, Pablo Casaseca-de-la-Higuera
https://arxiv.org/abs/2508.14949

XAI-Driven Spectral Analysis of Cough Sounds for Respiratory Disease Characterization
This paper proposes an eXplainable Artificial Intelligence (XAI)-driven methodology to enhance the understanding of cough sound analysis for respiratory disease management. We employ occlusion maps to highlight relevant spectral regions in cough spectrograms processed by a Convolutional Neural Network (CNN). Subsequently, spectral analysis of spectrograms weighted by these occlusion maps reveals significant differences between disease groups, particularly in patients with COPD, where cough patt…

A Fast Iterative Robust Principal Component Analysis Method
Timbwaoga Aime Judicael Ouermi, Jixian Li, Chris R. Johnson
https://arxiv.org/abs/2506.16013 ht…

A Fast Iterative Robust Principal Component Analysis Method
Principal Component Analysis (PCA) is widely used for dimensionality reduction and data analysis. However, PCA results are adversely affected by outliers often observed in real-world data. Existing robust PCA methods are often computationally expensive or exhibit limited robustness. In this work, we introduce a Fast Iterative Robust (FIR) PCA method by efficiently estimating the inliers center location and covariance. Our approach leverages Incremental PCA (IPCA) to iteratively construct a subs…

Failure Modes and Effects Analysis: An Experience from the E-Bike Domain
Andrea Bombarda, Federico Conti, Marcello Minervini, Aurora Zanenga, Claudio Menghi
https://arxiv.org/abs/2509.15893

Failure Modes and Effects Analysis: An Experience from the E-Bike Domain
Software failures can have catastrophic and costly consequences. Functional Failure Mode and Effects Analysis (FMEA) is a standard technique used within Cyber-Physical Systems (CPS) to identify software failures and assess their consequences. Simulation-driven approaches have recently been shown to be effective in supporting FMEA. However, industries need evidence of the effectiveness of these approaches to increase practical adoption. This industrial paper presents our experience with using FM…

Study of 2.4 million children:
"Acetaminophen [#paracetamol] use during pregnancy was not associated with children’s risk of #autism, ADHD, or intellectual disability in sibling control analysis. This suggests that associations observed in other models may have been attributable to familial c…

Structural Effect and Spectral Enhancement of High-Dimensional Regularized Linear Discriminant Analysis
Yonghan Zhang, Zhangni Pu, Lu Yan, Jiang Hu
https://arxiv.org/abs/2507.16682

Structural Effect and Spectral Enhancement of High-Dimensional Regularized Linear Discriminant Analysis
Regularized linear discriminant analysis (RLDA) is a widely used tool for classification and dimensionality reduction, but its performance in high-dimensional scenarios is inconsistent. Existing theoretical analyses of RLDA often lack clear insight into how data structure affects classification performance. To address this issue, we derive a non-asymptotic approximation of the misclassification rate and thus analyze the structural effect and structural adjustment strategies of RLDA. Based on th…

Spectral Analysis of Node- and Cell-Centered Higher-Order Compact Schemes for Fully Discrete One and Two-Dimensional Convection-Dispersion Equation
Lavanya V Salian, Vivek S Yadav, Rathan Samala, Rakesh Kumar
https://arxiv.org/abs/2507.14692

Spectral Analysis of Node- and Cell-Centered Higher-Order Compact Schemes for Fully Discrete One and Two-Dimensional Convection-Dispersion Equation
In this study, we present a comprehensive global spectral analysis of the convection dispersion equation, which is also referred to in specific contexts as the Korteweg de Vries (KdV) equation, to investigate the behaviour of high order numerical schemes across a wide range of nondimensional parameters. The motivation for this analysis stems from the equation's importance in modeling wave propagation and transport phenomena, where accurate resolution of dispersive effects is critical, and tradi…

Analysis Plug-and-Play Methods for Imaging Inverse Problems
Edward P. Chandler, Shirin Shoushtari, Brendt Wohlberg, Ulugbek S. Kamilov
https://arxiv.org/abs/2509.15422 https://

Analysis Plug-and-Play Methods for Imaging Inverse Problems
Plug-and-Play Priors (PnP) is a popular framework for solving imaging inverse problems by integrating learned priors in the form of denoisers trained to remove Gaussian noise from images. In standard PnP methods, the denoiser is applied directly in the image domain, serving as an implicit prior on natural images. This paper considers an alternative analysis formulation of PnP, in which the prior is imposed on a transformed representation of the image, such as its gradient. Specifically, we trai…

Mining Voter Behaviour and Confidence: A Rule-Based Analysis of the 2022 U.S. Elections
Md Al Jubair, Mohammad Shamsul Arefin, Ahmed Wasif Reza
https://arxiv.org/abs/2507.14236

Mining Voter Behaviour and Confidence: A Rule-Based Analysis of the 2022 U.S. Elections
This study explores the relationship between voter trust and their experiences during elections by applying a rule-based data mining technique to the 2022 Survey of the Performance of American Elections (SPAE). Using the Apriori algorithm and setting parameters to capture meaningful associations (support >= 3%, confidence >= 60%, and lift > 1.5), the analysis revealed a strong connection between demographic attributes and voting-related challenges, such as registration hurdles, accessibility is…

Simphony: A full tight-binding package for lattice vibrations and topological phonon analysis
Francesc Ballester, Ion Errea, Maia G. Vergniory
https://arxiv.org/abs/2507.15413

Simphony: A full tight-binding package for lattice vibrations and topological phonon analysis
Simphony is an open-source software package designed for the topological analysis of lattice vibrations based on Wannier tight-binding models. Its primary function is to classify the topology of novel materials by computing bulk and slab phonon band structures, extracting phonon surface spectra, and providing analysis tools such as Wilson loop calculations and Weyl node detection. The workflow is analogous to that of established electronic topology codes like Wannier90 and WannierTools. It also…

A Comprehensive Analysis of Rovibrational CO in the Era of JWST
D. Annie Dickson-Vandervelde, Colette Salyk, Geoffrey A. Blake, Clara Ross, Adwin Boogert, Klaus Pontoppidan
https://arxiv.org/abs/2507.16127

A Comprehensive Analysis of Rovibrational CO in the Era of JWST
We present an analysis of CO rovibrational emission lines in the 183 infrared spectra of nearby Class II objects obtained with the NIRSPEC instrument on the Keck II telescope over the past two decades. The sample includes a broad range of stellar mass (both T Tauri and Herbig Ae/Be) and disk evolutionary states (from full to debris disks). We find that 53% of the sample has CO rovibrational emission lines present in their spectrum with disk/stellar subtype detection rates of 82% for transition …

Information Theoretic Analysis of a Dual-Band MIMO Cellphone Antenna with ANSYS HFSS SBR
Volodymyr Shyianov, Bamelak Tadele, Vladimir I. Okhmatovski, Amine Mezghani
https://arxiv.org/abs/2507.14704

Information Theoretic Analysis of a Dual-Band MIMO Cellphone Antenna with ANSYS HFSS SBR+
Historically, the design of antenna arrays has evolved separately from Shannon theory. Shannon theory adopts a probabilistic approach in the design of communication systems, while antenna design approaches have relied on the deterministic Maxwell theory alone. In this paper, we investigate an information-theoretic analysis approach which we apply to evaluate the design of a dual-band, dual-polarized multiple-input multiple-output (MIMO) array on a cellphone. To this end, we use ANSYS HFSS, a co…

X-ray and Radio Analysis of Abell 1644: Constraints on Cluster Dynamics
Humaira Bashir, R. Kale, Asif Iqbal, Manzoor A. Malik
https://arxiv.org/abs/2506.16197

X-ray and Radio Analysis of Abell 1644: Constraints on Cluster Dynamics
We present the first band-2 (120 - 250 MHz) uGMRT (upgraded Giant Metrewave Radio Telescope) observations of the bimodal galaxy cluster Abell 1644 (z = 0.0471), complemented by Chandra X-ray data. While weak lensing measurements reveal a third substructure in Abell 1644, our radio analysis reveals only two compact sources coinciding with the respective brightest cluster galaxies (BCGs) of the northern (A1644N) and southern (A1644S) substructures, seen in the X-ray observations. Radio analysis y…

Spurion Analysis for Non-Invertible Selection Rules from Near-Group Fusions
Motoo Suzuki, Ling-Xiao Xu, Hao Y. Zhang
https://arxiv.org/abs/2508.14970 https://

Spurion Analysis for Non-Invertible Selection Rules from Near-Group Fusions
We generalize the framework of spurion analysis to a class of selection rules arising from non-invertible fusion algebras in perturbation theory. As a first step toward systematic applications to particle physics, we analyze the near-group fusion algebras, defined by fusion rules built from a finite Abelian group $G$ extended by a single non-invertible element. Notable examples include the Fibonacci and Ising fusion rules. We introduce a systematic scheme for labeling coupling constants at the …

An Optimization-Based Framework for Solving Forward-Backward Stochastic Differential Equations: Convergence Analysis and Error Bounds
Yutian Wang, Yuan-Hua Ni, Xun Li
https://arxiv.org/abs/2507.15234

An Optimization-Based Framework for Solving Forward-Backward Stochastic Differential Equations: Convergence Analysis and Error Bounds
In this paper, we develop an optimization-based framework for solving coupled forward-backward stochastic differential equations. We introduce an integral-form objective function and prove its equivalence to the error between consecutive Picard iterates. Our convergence analysis establishes that minimizing this objective generates sequences that converge to the true solution. We provide explicit upper and lower bounds that relate the objective value to the error between trial and exact solution…

Analysis on fibred cusp spaces
Daniel Grieser, \'Alvaro S\'anchez-Hern\'andez, Boris Vertman
https://arxiv.org/abs/2507.15467 https://

Analysis on fibred cusp spaces
We give a survey of a number of analytic and geometric results on `fibred cusp spaces'. These results cover topics in spectral geometry, in particular analytic torsion and index theory, and boundary value problems. The underlying tools include a careful microlocal analysis of the resolvent and the heat kernel. We include an exposition of the geometric and analytic foundations and sketch the ideas of the proofs of the main theorems.

Theoretical Analysis of Near-Field MIMO Channel Capacity and Mid-Band Experimental Validation
Haiyang Miao, Jianhua Zhang, Pan Tang, Heng Wang, Lei Tian, Guangyi Liu
https://arxiv.org/abs/2506.15972

Theoretical Analysis of Near-Field MIMO Channel Capacity and Mid-Band Experimental Validation
With the increase of multiple-input-multiple-output (MIMO) array size and carrier frequency, near-field MIMO communications will become crucial in 6G wireless networks. Due to the increase of MIMO near-field range, the research of near-field MIMO capacity has aroused wide interest. In this paper, we focus on the theoretical analysis and empirical study of near-field MIMO capacity. First, the near-field channel model is characterized from the electromagnetic information perspective. Second, with…

Formal Analysis of Networked PLC Controllers Interacting with Physical Environments
Jaeseo Lee, Kyungmin Bae
https://arxiv.org/abs/2507.15596 https://

Formal Analysis of Networked PLC Controllers Interacting with Physical Environments
Programmable Logic Controllers (PLCs) are widely used in industrial automation to control physical systems. As PLC applications become increasingly complex, ensuring their correctness is crucial. Existing formal verification techniques focus on individual PLC programs in isolation, often neglecting interactions with physical environments and network communication between controllers. This limitation poses significant challenges in analyzing real-world industrial systems, where continuous dynami…

TrajLens: Visual Analysis for Constructing Cell Developmental Trajectories in Cross-Sample Exploration
Qipeng Wang, Shaolun Ruan, Rui Sheng, Yong Wang, Min Zhu, Huamin Qu
https://arxiv.org/abs/2507.15620

TrajLens: Visual Analysis for Constructing Cell Developmental Trajectories in Cross-Sample Exploration
Constructing cell developmental trajectories is a critical task in single-cell RNA sequencing (scRNA-seq) analysis, enabling the inference of potential cellular progression paths. However, current automated methods are limited to establishing cell developmental trajectories within individual samples, necessitating biologists to manually link cells across samples to construct complete cross-sample evolutionary trajectories that consider cellular spatial dynamics. This process demands substantial…

#SpringBoot 4 Released: A Full Analysis of 11 Major Changes!
https://medium.com/@haiou-a/spring-boo

A Comparative Analysis of Statistical and Machine Learning Models for Outlier Detection in Bitcoin Limit Order Books
Ivan Letteri
https://arxiv.org/abs/2507.14960 https://

A Comparative Analysis of Statistical and Machine Learning Models for Outlier Detection in Bitcoin Limit Order Books
The detection of outliers within cryptocurrency limit order books (LOBs) is of paramount importance for comprehending market dynamics, particularly in highly volatile and nascent regulatory environments. This study conducts a comprehensive comparative analysis of robust statistical methods and advanced machine learning techniques for real-time anomaly identification in cryptocurrency LOBs. Within a unified testing environment, named AITA Order Book Signal (AITA-OBS), we evaluate the efficacy of…

Dynamical Analysis of the HD 169142 Planet-Forming Disk: Twelve Years of High-Contrast Polarimetry
Miles Lucas, Michael Bottom, Ruobing Dong, Myriam Benisty, Mario Flock, Maria Vincent, Jonathan Williams, Kyohoon Ahn, Thayne Currie, Vincent Deo, Olivier Guyon, Tomoyuki Kudo, Lucinda Lilley, Julien Lozi, Maxwell Millar-Blanchaer, Barnaby Norris, Sebasti\'an P\'erez, Boris Safonov, Peter Tuthill, Taichi Uyama, S\'ebastien Vievard, Manxuan Zhang

Dynamical Analysis of the HD 169142 Planet-Forming Disk: Twelve Years of High-Contrast Polarimetry
We present a dynamical analysis of the HD 169142 planet-forming disk based on high-contrast polarimetric imaging over a twelve-year observational period, offering insights into its disk evolution and planet-disk interactions. This study explores the evolution of scattered-light features and their relationship with millimeter continuum emission. Archival visible-to-near-infrared scattered-light observations from NACO, SPHERE, and GPI combined with new observations from SCExAO reveal persistent n…

WiFiSim: Simulating WiFi Probe Requests via AOSP Analysis and Device Behavior Modeling
Lifei Hao, Yue Cheng, Min Wang, Bing Jia, Baoqi Huang
https://arxiv.org/abs/2509.15501 htt…

WiFiSim: Simulating WiFi Probe Requests via AOSP Analysis and Device Behavior Modeling
WiFi probe request (PR) frames encode fine-grained device interactions and serve as a critical basis for mobility and crowd analytics. However, pervasive MAC address randomization and the scarcity of labeled datasets hinder progress in PR-based studies. We introduce WiFiSim, a simulation framework that reconstructs PR generation through Android Open Source Project (AOSP) protocol analysis and finite-state device behavior modeling. WiFiSim identifies the key determinants of PR structure and timi…

Comprehensive Privacy Risk Assessment in Social Networks Using User Attributes Social Graphs and Text Analysis
Md Jahangir Alam, Ismail Hossain, Sai Puppala, Sajedul Talukder
https://arxiv.org/abs/2507.15124

Comprehensive Privacy Risk Assessment in Social Networks Using User Attributes Social Graphs and Text Analysis
The rise of social networking platforms has amplified privacy threats as users increasingly share sensitive information across profiles, content, and social connections. We present a Comprehensive Privacy Risk Scoring (CPRS) framework that quantifies privacy risk by integrating user attributes, social graph structures, and user-generated content. Our framework computes risk scores across these dimensions using sensitivity, visibility, structural similarity, and entity-level analysis, then aggre…

Analysis of a three-dimensional rapidly rotating convection model without thermal diffusion
Chongsheng Cao, Yanqiu Guo, Edriss S. Titi
https://arxiv.org/abs/2507.16143

Analysis of a three-dimensional rapidly rotating convection model without thermal diffusion
We study a three-dimensional rapidly rotating convection model featuring tall columnar structures, in the absence of thermal diffusion. We establish the global existence and uniqueness of weak solutions, as well as the Hadamard well-posedness of global strong solutions to this model. The lack of thermal diffusion introduces significant challenges in the analysis. To overcome these challenges, we first investigate the regularized model with thermal diffusion and establish delicate estimates that…

A new study found that there's a universal rhythm to how people speak: in 0.6Hz (1.667s) units. I find this fascinating because that's pretty close (though obviously only coincidentally) to 20 μdays (0.579Hz = 1.728s) and this feeds my fantasy about decimal time (standardize on days, 1 milliday = 1.44min, 10 microdays = 0.864s, we'd probably make use of centidays, which are just shy of quarter hours).

A universal rhythm guides how we speak: Global analysis reveals 1.6-second 'intonation units'
Have you ever noticed that a natural conversation flows like a dance—pauses, emphases, and turns arriving just in time? A new study has discovered that this isn't just intuition; there is a biological rhythm embedded in our speech.

Signless Laplacian spectral analysis of a class of graph joins
Jiachang Ye, Zoran Stani\' c, Jianguo Qian
https://arxiv.org/abs/2507.15276 https://

Signless Laplacian spectral analysis of a class of graph joins
A graph is said to be determined by its signless Laplacian spectrum (abbreviated as DQS) if no other non-isomorphic graph shares the same signless Laplacian spectrum. In this paper, we establish the following results: (1). Every graph of the form $K_1 \vee (C_s \cup qK_2)$, where $q \ge 0$, $s \ge 3$, and the number of vertices is at least $16$, is DQS; (2). Every graph of the form $K_1 \vee (C_{s_1} \cup C_{s_2} \cup \cdots \cup C_{s_t} \cup qK_2)$, where $t \ge 2$, $q \ge 0$, $s_i \ge 3$,…

OpenAI details how its tools have boosted US worker productivity and says its chief economist is leading a 12-month study to assess AI's impact on productivity (OpenAI)
https://openai.com/global-affairs/new-economic-analysis

A senior CIA officer who oversaw Russia analysis
has been stripped of her security clearance,
part of a sweeping removal of
37 serving and former officials accused of "betray[ing] their oath to the Constitution," the Economist reported on Aug. 21.
The officer, who served as the CIA’s top Russia and Eurasia analyst during the 2016 election
and helped produce the report detailing Moscow’s interference on behalf of Donald Trump,
was among the most s…

Trump administration escalates purge of senior US intelligence officials, Economist reports
The officer, who served as the CIA’s top Russia and Eurasia analyst during the 2016 election and helped produce the report detailing Moscow’s interference on behalf of Donald Trump, was among the most senior career officials targeted.

drosophila_flybi: Fruit fly protein interactions (Drosophila melanogaster)
Binary protein-protein interactions (PPIs) for Drosophila melanogaster, containing 8723 PPIs among 2939 proteins. The iteractions were identified using a yeast two-hybrid (Y2H) analysis.
This network has 2939 nodes and 8723 edges.
Tags: Biological, Protein interactions, Unweighted

The effect of fiber plasticity on domain formation in soft biological composites -- Part II: An imperfection analysis
Dimitris Iordanidis, Fernanda F. Fontenele, Konstantinos Poulios, Michalis Agoras, Nikolaos Bouklas
https://arxiv.org/abs/2507.14764

The effect of fiber plasticity on domain formation in soft biological composites -- Part II: An imperfection analysis
The main objective of this work is to numerically investigate the effect of geometric imperfections on the macroscopic response and domain formation in soft biological composites that exhibit plasticity in the stiff (fiber) phase.This work builds on the corresponding bifurcation analysis in Part I of this study for simple laminates with perfectly flat layers under plane strain, nonmonotonic loading conditions, aligned with the layer direction. The post-bifurcation solution obtained in Part I fo…

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
Shanghai AI Lab, :, Xiaoyang Chen, Yunhao Chen, Zeren Chen, Zhiyun Chen, Hanyun Cui, Yawen Duan, Jiaxuan Guo, Qi Guo, Xuhao Hu, Hong Huang, Lige Huang, Chunxiao Li, Juncheng Li, Qihao Lin, Dongrui Liu, Xinmin Liu, Zicheng Liu, Chaochao Lu, Xiaoya Lu, Jingjing Qu, Qibing Ren, Jing Shao, Jingwei Shi, Jingwei Sun, Peng Wang, Weibing Wang, Jia Xu, Lewen Yan, Xiao Yu, Yi Yu, Boxuan Zhang, Jie Zhang, Weichen…

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, this report presents a comprehensive assessment of their frontier risks. Drawing on the E-T-C analysis (deployment environment, threat source, enabling capability) from the Frontier AI Risk Management Framework (v1.0) (SafeWork-F1-Framework), we identify critical risks in seven areas: cyber offense, biological and chemical risks, persuasion and manipulation, uncontrolled autonomous…

Early-game fantasy headlines: Daniel Jones delivers again; Pats can't hold onto ball https://www.espn.com/fantasy/football/story/_/id/40699880/fantasy-football-injuries-position-battles-nfl-news-analysis

Tighter Privacy Analysis for Truncated Poisson Sampling
Arun Ganesh
https://arxiv.org/abs/2508.15089 https://arxiv.org/pdf/2508.15089

Tighter Privacy Analysis for Truncated Poisson Sampling
We give a new privacy amplification analysis for truncated Poisson sampling, a Poisson sampling variant that truncates a batch if it exceeds a given maximum batch size.

Causal Mediation Analysis for Zero-inflated Mixture Mediators
Meilin Jiang, Seonjoo Lee, A. James O'Malley, Pengfei Li, Zhigang Li
https://arxiv.org/abs/2507.15164

Causal Mediation Analysis for Zero-inflated Mixture Mediators
Causal mediation analysis is an important statistical tool to quantify effects transmitted by intermediate variables from a cause to an outcome. There is a gap in mediation analysis methods to handle mixture mediator data that are zero-inflated with multi-modality and atypical behaviors. We propose an innovative way to model zero-inflated mixture mediators from the perspective of finite mixture distributions to flexibly capture such mediator data. Multiple data types are considered for modeling…

Scaled Relative Graph Analysis of General Interconnections of SISO Nonlinear Systems
Julius P. J. Krebbekx, Roland T\'oth, Amritam Das
https://arxiv.org/abs/2507.15564

Scaled Relative Graph Analysis of General Interconnections of SISO Nonlinear Systems
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. However, we show that the current SRG analysis suffers from a pitfall that limits its applicability in analyzing practical nonlinear systems. We overcome this pitfall by introducing a novel reformulation of the SRG of a linear time-invariant operator and combining the SRG with the Nyquist criterion. The result is a theorem that can be used to assess stability and $L_2$-gain per…

Estimating Treatment Effects with Independent Component Analysis
Patrik Reizinger, Lester Mackey, Wieland Brendel, Rahul Krishnan
https://arxiv.org/abs/2507.16467

Estimating Treatment Effects with Independent Component Analysis
The field of causal inference has developed a variety of methods to accurately estimate treatment effects in the presence of nuisance. Meanwhile, the field of identifiability theory has developed methods like Independent Component Analysis (ICA) to identify latent sources and mixing weights from data. While these two research communities have developed largely independently, they aim to achieve similar goals: the accurate and sample-efficient estimation of model parameters. In the partially lin…

Planned coal production through to 2035 and planned fossil gas production through to 2050 are not only set to breach Paris Agreement targets to keep temperature increases 'well below' 2C while pursuing efforts to limit them to 1.5C, they have increased since the last time the analysis was carried out in 2023.
'Alarming': Fossil fuel production plans far exceed global climate targets | BusinessGreen News

'Alarming': Fossil fuel production plans far exceed global climate targets
Planned coal, oil, and gas production through to 2030 is double the level that would be consistent with limiting global warming to 2C, analysis shows

'A Little Bubble of Friends': An Analysis of LGBTQ Pandemic Experiences Using Reddit Data
Dhruvee Birla, Nazia Akhtar
https://arxiv.org/abs/2507.15033

'A Little Bubble of Friends': An Analysis of LGBTQ+ Pandemic Experiences Using Reddit Data
Social media was one of the most popular forms of communication among young people with digital access during the pandemic. Consequently, crucial debates and discussions about the pandemic crisis have also developed on social media platforms, making them a great primary source to study the experiences of specific groups and communities during the pandemic. This study involved research using LDA topic modeling and sentiment analysis on data obtained from the social media platform Reddit to under…

$\textit{A Priori}$ Error Analysis for the $p$-Stokes Equations with Slip Boundary Conditions: A Discrete Leray Projection Framework
Alex Kaltenbach, J\"orn Wichmann
https://arxiv.org/abs/2507.15016

$\textit{A Priori}$ Error Analysis for the $p$-Stokes Equations with Slip Boundary Conditions: A Discrete Leray Projection Framework
We present an $\textit{a priori}$ error analysis for the kinematic pressure in a fully-discrete finite-differences/-elements discretization of the unsteady $p$-Stokes equations, modelling non-Newtonian fluids. This system is subject to both impermeability and perfect Navier slip boundary conditions, which are incorporated either weakly via Lagrange multipliers or strongly in the discrete velocity space. A central aspect of the $\textit{a priori}$ error analysis is the discrete Leray projection,…

Binary Analysis and Period Study of the Long-Period, High Mass Ratio Contact Binary KIC 7766185
Conor M Larsen, Andrej Prsa
https://arxiv.org/abs/2507.14979

Binary Analysis and Period Study of the Long-Period, High Mass Ratio Contact Binary KIC 7766185
We present an in-depth photometric and spectroscopic study of the contact binary KIC 7766185. Spectroscopic observations were conducted on the Mayall 4-m telescope at Kitt Peak National Observatory and used to extract radial velocities. Using the radial velocity measurements, Kepler photometry, and Gaia multi-color photometry, binary analysis was performed in PHOEBE to determine orbital and stellar parameters. The results classify KIC 7766185 as an A-type W UMa system and reveal one of the larg…

Retention analysis of edited knowledge after fine-tuning
Fufang Wen, Shichang Zhang
https://arxiv.org/abs/2507.14198 https://arxiv.or…

Retention analysis of edited knowledge after fine-tuning
Large language models (LLMs) store vast amounts of knowledge, which often requires updates to correct factual errors, incorporate newly acquired information, or adapt model behavior. Model editing methods have emerged as efficient solutions for such updates, offering localized and precise knowledge modification at significantly lower computational cost than continual training. In parallel, LLMs are frequently fine-tuned for a wide range of downstream tasks. However, the effect of fine-tuning on…

Integrating Traditional Technical Analysis with AI: A Multi-Agent LLM-Based Approach to Stock Market Forecasting
Micha{\l} Wawer, Jaros{\l}aw A. Chudziak
https://arxiv.org/abs/2506.16813

Integrating Traditional Technical Analysis with AI: A Multi-Agent LLM-Based Approach to Stock Market Forecasting
Traditional technical analysis methods face limitations in accurately predicting trends in today's complex financial markets. This paper introduces ElliottAgents, an multi-agent system that integrates the Elliott Wave Principle with AI for stock market forecasting. The inherent complexity of financial markets, characterized by non-linear dynamics, noise, and susceptibility to unpredictable external factors, poses significant challenges for accurate prediction. To address these challenges, the s…

The GJMS operators in geometry, analysis, and physics
Jeffrey S. Case, A. Rod Gover
https://arxiv.org/abs/2509.16047 https://arxiv.org/pdf/2509.16047

The GJMS operators in geometry, analysis, and physics
The GJMS operators, introduced by Graham, Jenne, Mason, and Sparling, are a family of conformally invariant linear differential operators with leading term a power of the Laplacian. These operators and their method of construction have had a major impact in geometry, analysis, and physics. We describe the GJMS operators and their construction, and briefly survey their importance and impact.

Universal parameters of the $\Lambda(1380)$, the $\Lambda(1405)$ and their isospin partners from a combined analysis of Lattice QCD and experimental results
Ferenc Pittler, Maxim Mai, Ulf-G. Mei{\ss}ner, Ryan F. Ferguson, Peter Hurck, David G. Ireland, Bryan McKinnon
https://arxiv.org/abs/2507.14283

Universal parameters of the $Λ(1380)$, the $Λ(1405)$ and their isospin partners from a combined analysis of Lattice QCD and experimental results
We perform a global analysis of lattice and experimental data on negative-strangeness meson-baryon scattering using a large set of variations of the theoretical framework based on the Chiral Unitary Approach. For the former, the Lüscher formalism is utilized taking into account all pertinent coupled-channel effects. Through this, systematic uncertainties related to data scarcity, potential ambiguities, and possible framework dependence are quantified for the first time. The implementation of i…

How Far Are We? An Empirical Analysis of Current Vulnerability Localization Approaches
Haoran Xu, Zhi Chen, Junxiao Han, Xinkui Zhao, Jianwei Yin, Shuiguang Deng
https://arxiv.org/abs/2509.15777

How Far Are We? An Empirical Analysis of Current Vulnerability Localization Approaches
Open-source software vulnerability patch detection is a critical component for maintaining software security and ensuring software supply chain integrity. Traditional manual detection methods face significant scalability challenges when processing large volumes of commit histories, while being prone to human errors and omissions. Existing automated approaches, including heuristic-based methods and pre-trained model solutions, suffer from limited accuracy, poor generalization capabilities, and i…

Bayesian unanchored additive models for component network meta-analysis
Augustine Wigle, Audrey B\'eliveau
https://arxiv.org/abs/2507.16047 https://

Bayesian unanchored additive models for component network meta-analysis
Component network meta-analysis (CNMA) models are an extension of standard network meta-analysis (NMA) models which account for the use of multicomponent treatments in the network. This article contributes innovatively to several statistical aspects of CNMA. First, by introducing a unified notation, we establish that currently available methods differ in the way they assume additivity, an important distinction that has been overlooked so far in the literature. In particular, one model uses a mo…

Cosmological Preference for a Positive Neutrino Mass at 2.7$\sigma$: A Joint Analysis of DESI DR2, DESY5, and DESY1 Data
Guo-Hong Du, Tian-Nuo Li, Peng-Ju Wu, Jing-Fei Zhang, Xin Zhang
https://arxiv.org/abs/2507.16589

Cosmological Preference for a Positive Neutrino Mass at 2.7$σ$: A Joint Analysis of DESI DR2, DESY5, and DESY1 Data
Neutrinos and dark energy (DE) have entered a new era of investigation, as the latest DESI baryon acoustic oscillation measurements tighten the constraints on the neutrino mass and suggest that DE may be dynamical rather than a cosmological constant. In this work, we investigate the cosmological implications of simultaneously incorporating $\sum m_ν$ and $N_{\rm eff}$ within the framework of dynamical DE. A joint analysis of DESI DR2, cosmic microwave background, DESY5 supernova, and DESY1 wea…

Synergizing Static Analysis with Large Language Models for Vulnerability Discovery and beyond
Vaibhav Agrawal, Kiarash Ahi
https://arxiv.org/abs/2509.15433 https://

Synergizing Static Analysis with Large Language Models for Vulnerability Discovery and beyond
This report examines the synergy between Large Language Models (LLMs) and Static Application Security Testing (SAST) to improve vulnerability discovery. Traditional SAST tools, while effective for proactive security, are limited by high false-positive rates and a lack of contextual understanding. Conversely, LLMs excel at code analysis and pattern recognition but can be prone to inconsistencies and hallucinations. By integrating these two technologies, a more intelligent and efficient system is…

Enhanced Predictive Modeling for Hazardous Near-Earth Object Detection: A Comparative Analysis of Advanced Resampling Strategies and Machine Learning Algorithms in Planetary Risk Assessment
Sunkalp Chandra
https://arxiv.org/abs/2508.15106

Enhanced Predictive Modeling for Hazardous Near-Earth Object Detection: A Comparative Analysis of Advanced Resampling Strategies and Machine Learning Algorithms in Planetary Risk Assessment
This study evaluates the performance of several machine learning models for predicting hazardous near-Earth objects (NEOs) through a binary classification framework, including data scaling, power transformation, and cross-validation. Six classifiers were compared, namely Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), Support Vector Classifier (SVC), Linear Discriminant Analysis (LDA), Logistic Regression (LR), and K-Nearest Neighbors (KNN). RFC and GBC performed the best, b…

Modified security analysis of device-independent quantum key distribution with random key basis
Sawan Bhattacharyya, Turbasu Chatterjee, Pankaj Agrawal, Prasenjit Deb
https://arxiv.org/abs/2508.12938

Modified security analysis of device-independent quantum key distribution with random key basis
Security analysis is a critical part in any cryptographic protocol, may it be classical or quantum. Without security analysis, one cannot ensure the secrecy of the distributed keys. To perform a conclusive security analysis, it is very often necessary to frame the problem as an optimization problem. However, solving such optimization problems is quite challenging. In this article, we focus on the security analysis of device-independent quantum key distribution (DIQKD) with random key basis prot…

Software Model Checking via Summary-Guided Search (Extended Version)
Ruijie Fang, Zachary Kincaid, Thomas Reps
https://arxiv.org/abs/2508.15137 https://arx…

Software Model Checking via Summary-Guided Search (Extended Version)
In this work, we describe a new software model-checking algorithm called GPS. GPS treats the task of model checking a program as a directed search of the program states, guided by a compositional, summary-based static analysis. The summaries produced by static analysis are used both to prune away infeasible paths and to drive test generation to reach new, unexplored program states. GPS can find both proofs of safety and counter-examples to safety (i.e., inputs that trigger bugs), and features a…

drosophila_flybi: Fruit fly protein interactions (Drosophila melanogaster)
Binary protein-protein interactions (PPIs) for Drosophila melanogaster, containing 8723 PPIs among 2939 proteins. The iteractions were identified using a yeast two-hybrid (Y2H) analysis.
This network has 2939 nodes and 8723 edges.
Tags: Biological, Protein interactions, Unweighted

Great piece from Canada debunking the new nuclear craze. Unaffordable, slow, unsustainable.
@…
The New Nuclear Fever, Debunked | The Tyee
https://thetyee.ca/Analysis/2025…

Performance Analysis of Post-Training Quantization for CNN-based Conjunctival Pallor Anemia Detection
Sebastian A. Cruz Romero, Wilfredo E. Lugo Beauchamp
https://arxiv.org/abs/2507.15151

Performance Analysis of Post-Training Quantization for CNN-based Conjunctival Pallor Anemia Detection
Anemia is a widespread global health issue, particularly among young children in low-resource settings. Traditional methods for anemia detection often require expensive equipment and expert knowledge, creating barriers to early and accurate diagnosis. To address these challenges, we explore the use of deep learning models for detecting anemia through conjunctival pallor, focusing on the CP-AnemiC dataset, which includes 710 images from children aged 6-59 months. The dataset is annotated with he…

TrajSceneLLM: A Multimodal Perspective on Semantic GPS Trajectory Analysis
Chunhou Ji, Qiumeng Li
https://arxiv.org/abs/2506.16401 https://

TrajSceneLLM: A Multimodal Perspective on Semantic GPS Trajectory Analysis
GPS trajectory data reveals valuable patterns of human mobility and urban dynamics, supporting a variety of spatial applications. However, traditional methods often struggle to extract deep semantic representations and incorporate contextual map information. We propose TrajSceneLLM, a multimodal perspective for enhancing semantic understanding of GPS trajectories. The framework integrates visualized map images (encoding spatial context) and textual descriptions generated through LLM reasoning (…

Analysis: in H1 2025, 500 orgs lobbied the White House and Congress on AI, on par with H1 2024 but up ~2x since 2023; OpenAI spent $1.8M, up from $380K in 2023 (Financial Times)
https://www.ft.com/content/df01dcf8-dbc4-4b56-8d8b-67b7e6a83eef

Sequential Confirmatory Factor Analysis: A Novel Approach to Latent Variable Measurement
Zachary Esses Johnson
https://arxiv.org/abs/2508.15611 https://arx…

Sequential Confirmatory Factor Analysis: A Novel Approach to Latent Variable Measurement
Factor score estimation in small sample sizes often encounters parameter bias and convergence failures when constructing hierarchical national/sub-national indices. This paper proposes a novel method for hierarchical factor analysis called "sequential Confirmatory Factor Analysis". Instead of estimating multiple levels of factors at the same time, this approach calculates factor scores sequentially from the lowest to highest levels. This sequential estimation keeps the original sample size in e…

Dissecting Tool-Integrated Reasoning: An Empirical Study and Analysis
Yufeng Zhao, Junnan Liu, Hongwei Liu, Dongsheng Zhu, Yuan Shen, Songyang Zhang, Kai Chen
https://arxiv.org/abs/2508.15754

Dissecting Tool-Integrated Reasoning: An Empirical Study and Analysis
Large Language Models (LLMs) have made significant strides in reasoning tasks through methods like chain-of-thought (CoT) reasoning. However, they often fall short in tasks requiring precise computations. Tool-Integrated Reasoning (TIR) has emerged as a solution by incorporating external tools into the reasoning process. Nevertheless, the generalization of TIR in improving the reasoning ability of LLM is still unclear. Additionally, whether TIR has improved the model's reasoning behavior and he…

AFC West betting preview: Chargers and Broncos will surpass expectations https://www.espn.com/espn/betting/story/_/id/46036791/2025-afc-west-division-betting-nfl-preview-favorites-odds-standings-ranki…

Towards Scalable and Interpretable Mobile App Risk Analysis via Large Language Models
Yu Yang, Zhenyuan Li, Xiandong Ran, Jiahao Liu, Jiahui Wang, Bo Yu, Shouling Ji
https://arxiv.org/abs/2508.15606

Towards Scalable and Interpretable Mobile App Risk Analysis via Large Language Models
Mobile application marketplaces are responsible for vetting apps to identify and mitigate security risks. Current vetting processes are labor-intensive, relying on manual analysis by security professionals aided by semi-automated tools. To address this inefficiency, we propose Mars, a system that leverages Large Language Models (LLMs) for automated risk identification and profiling. Mars is designed to concurrently analyze multiple applications across diverse risk categories with minimal human …

Numerical Analysis of Simultaneous Reconstruction of Initial Condition and Potential in Subdiffusion
Xu Wu, Jiang Yang, Zhi Zhou
https://arxiv.org/abs/2509.15633 https://…

Numerical Analysis of Simultaneous Reconstruction of Initial Condition and Potential in Subdiffusion
This paper investigates the simultaneous identification of a spatially dependent potential and the initial condition in a subdiffusion model based on two terminal observations. The existence, uniqueness, and conditional stability of the inverse problem are established under weak regularity assumptions through a constructive fixed-point iteration approach. The theoretical analysis further inspires the development of an easy-to-implement iterative algorithm. A fully discrete scheme is then propos…

Process-Driven Visual Analysis of Cybersecurity Capture the Flag Exercises
Radek O\v{s}lej\v{s}ek, Radoslav Chudovsk\'y, Martin Macak
https://arxiv.org/abs/2509.15589 https:…

Process-Driven Visual Analysis of Cybersecurity Capture the Flag Exercises
Hands-on training sessions become a standard way to develop and increase knowledge in cybersecurity. As practical cybersecurity exercises are strongly process-oriented with knowledge-intensive processes, process mining techniques and models can help enhance learning analytics tools. The design of our open-source analytical dashboard is backed by guidelines for visualizing multivariate networks complemented with temporal views and clustering. The design aligns with the requirements for post-trai…

Butterfly Effects in Toolchains: A Comprehensive Analysis of Failed Parameter Filling in LLM Tool-Agent Systems
Qian Xiong, Yuekai Huang, Ziyou Jiang, Zhiyuan Chang, Yujia Zheng, Tianhao Li, Mingyang Li
https://arxiv.org/abs/2507.15296

Butterfly Effects in Toolchains: A Comprehensive Analysis of Failed Parameter Filling in LLM Tool-Agent Systems
The emergence of the tool agent paradigm has broadened the capability boundaries of the Large Language Model (LLM), enabling it to complete more complex tasks. However, the effectiveness of this paradigm is limited due to the issue of parameter failure during its execution. To explore this phenomenon and propose corresponding suggestions, we first construct a parameter failure taxonomy in this paper. We derive five failure categories from the invocation chain of a mainstream tool agent. Then, w…

Unveiling Entanglement's Metrological Power: Empirical Modeling of Optimal States in Quantum Metrics
Volkan Erol
https://arxiv.org/abs/2509.15954 https://

Unveiling Entanglement's Metrological Power: Empirical Modeling of Optimal States in Quantum Metrics
Using extensive numerical analysis of 20,000 randomly generated two-qubit states, we provide a quantitative analysis of the connection between entanglement measures and Maximized Quantum Fisher Information (MQFI). Our systematic study shows strong empirical relationships between the metrological capacity of quantum states and three different entanglement measures: concurrence, negativity, and relative entropy of entanglement. We show that optimization over local unitary transformations produces…

Hypergraphs on high dimensional time series sets using signature transform
R\'emi Vaucher, Paul Minchella
https://arxiv.org/abs/2507.15802 https://

Hypergraphs on high dimensional time series sets using signature transform
In recent decades, hypergraphs and their analysis through Topological Data Analysis (TDA) have emerged as powerful tools for understanding complex data structures. Various methods have been developed to construct hypergraphs -- referred to as simplicial complexes in the TDA framework -- over datasets, enabling the formation of edges between more than two vertices. This paper addresses the challenge of constructing hypergraphs from collections of multivariate time series. While prior work has fo…

drosophila_flybi: Fruit fly protein interactions (Drosophila melanogaster)
Binary protein-protein interactions (PPIs) for Drosophila melanogaster, containing 8723 PPIs among 2939 proteins. The iteractions were identified using a yeast two-hybrid (Y2H) analysis.
This network has 2939 nodes and 8723 edges.
Tags: Biological, Protein interactions, Unweighted

Strategic Integration of AI Chatbots in Physics Teacher Preparation: A TPACK-SWOT Analysis of Pedagogical, Epistemic, and Cybersecurity Dimensions
N. Mohammadipour
https://arxiv.org/abs/2507.14860

Strategic Integration of AI Chatbots in Physics Teacher Preparation: A TPACK-SWOT Analysis of Pedagogical, Epistemic, and Cybersecurity Dimensions
This study investigates the strategic and epistemically responsible integration of AI-powered chatbots into physics teacher education by employing a TPACK-guided SWOT framework across three structured learning activities. Conducted within a university-level capstone course on innovative tools for physics instruction, the activities targeted key intersections of technological, pedagogical, and content knowledge (TPACK) through chatbot-assisted tasks: simplifying abstract physics concepts, constr…

Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation
Yichi Zhang, Yao Huang, Yifan Wang, Yitong Sun, Chang Liu, Zhe Zhao, Zhengwei Fang, Huanran Chen, Xiao Yang, Xingxing Wei, Hang Su, Yinpeng Dong, Jun Zhu
https://arxiv.org/abs/2508.15370

Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation
The trustworthiness of Multimodal Large Language Models (MLLMs) remains an intense concern despite the significant progress in their capabilities. Existing evaluation and mitigation approaches often focus on narrow aspects and overlook risks introduced by the multimodality. To tackle these challenges, we propose MultiTrust-X, a comprehensive benchmark for evaluating, analyzing, and mitigating the trustworthiness issues of MLLMs. We define a three-dimensional framework, encompassing five trustwo…

NFC South betting preview: Bucs favored, but can Falcons or Panthers make noise? https://www.espn.com/espn/betting/story/_/id/46030891/2025-nfc-south-division-betting-nfl-preview-favorites-odds-stand…

On the convergence analysis of MsFEM with oversampling: Interpolation error
Guanglian Li
https://arxiv.org/abs/2507.14548 https://arx…

On the convergence analysis of MsFEM with oversampling: Interpolation error
In this paper, we investigate the approximation properties of two types of multiscale finite element methods with oversampling as proposed in [Hou \& Wu, {\textit{J. Comput. Phys.}}, 1997] and [Efendiev, Hou \& Wu, \textit{SIAM J. Numer. Anal.}, 2000] without scale separation. We develop a general interpolation error analysis for elliptic problems with highly oscillatory rough coefficients, under the assumption of the existence of a macroscopic problem with suitable $L^2$-accuracy. The distinct…

Mistral releases a study on the environmental impact of its LLMs, conducting what it claims is the first comprehensive lifecycle analysis of an AI model (Mistral AI)
https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai…

Our contribution to a global environmental standard for AI | Mistral AI

Impact of Single Rotations and Entanglement Topologies in Quantum Neural Networks
Marco Mordacci, Michele Amoretti
https://arxiv.org/abs/2509.15722 https://

Impact of Single Rotations and Entanglement Topologies in Quantum Neural Networks
In this work, an analysis of the performance of different Variational Quantum Circuits is presented, investigating how it changes with respect to entanglement topology, adopted gates, and Quantum Machine Learning tasks to be performed. The objective of the analysis is to identify the optimal way to construct circuits for Quantum Neural Networks. In the presented experiments, two types of circuits are used: one with alternating layers of rotations and entanglement, and the other, similar to the …

Subgroup comparisons within and across studies in meta-analysis
Renato Panaro, Christian R\"over, Tim Friede
https://arxiv.org/abs/2508.15531 https://…

Subgroup comparisons within and across studies in meta-analysis
Subgroup-specific meta-analysis synthesizes treatment effects for patient subgroups across randomized trials. Methods include joint or separate modeling of subgroup effects and treatment-by-subgroup interactions, but inconsistencies arise when subgroup prevalence differs between studies (e.g., proportion of non-smokers). A key distinction is between study-generated evidence within trials and synthesis-generated evidence obtained by contrasting results across trials. This distinction matters for…

NFC West betting preview: 49ers and Rams top odds, but don't count out Seahawks and Cards https://www.espn.com/espn/betting/story/_/id/46036810/2025-nfc-west-division-betting-nfl-preview-favorites…

Inference Attacks on Encrypted Online Voting via Traffic Analysis
Anastasiia Belousova, Francesco Marchiori, Mauro Conti
https://arxiv.org/abs/2509.15694 https://

Inference Attacks on Encrypted Online Voting via Traffic Analysis
Online voting enables individuals to participate in elections remotely, offering greater efficiency and accessibility in both governmental and organizational settings. As this method gains popularity, ensuring the security of online voting systems becomes increasingly vital, as the systems supporting it must satisfy a demanding set of security requirements. Most research in this area emphasizes the design and verification of cryptographic protocols to protect voter integrity and system confiden…

AFC South betting preview: Texans favored; will Colts, Jags, Titans beat expectations? https://www.espn.com/espn/betting/story/_/id/46029958/2025-afc-south-division-betting-nfl-preview-favorites-odds…

Application-Driven Benchmarking of the Traveling Salesperson Problem: a Quantum Hardware Deep-Dive
Amine Bentellis, Benedikt Poggel, Jeanette Miriam Lorenz
https://arxiv.org/abs/2507.16471

Application-Driven Benchmarking of the Traveling Salesperson Problem: a Quantum Hardware Deep-Dive
The potential analysis of the capabilities of quantum computing, especially before fault tolerance at scale, is difficult due to the variety of existing hardware technologies with a wide spread of maturity. Not only the result of computations, but also the very process of running quantum-enhanced algorithms differ from provider to provider. The study includes a comparative analysis of various hardware architectures with the example of the Traveling Salesperson Problem, a central class of combin…

Mean Shift for Functional Data: A Scalable Algorithm and Convergence Analysis
Ting-Li Chen, Toshinari Morimoto, Su-Yun Huang, Ruey S. Tsay
https://arxiv.org/abs/2507.14457

Mean Shift for Functional Data: A Scalable Algorithm and Convergence Analysis
This paper extends the mean shift algorithm from vector-valued data to functional data, enabling effective clustering in infinite-dimensional settings. To address the computational challenges posed by large-scale datasets, we introduce a fast stochastic variant that significantly reduces computational complexity. We provide a rigorous analysis of convergence and stability for the full functional mean shift procedure, establishing theoretical guarantees for its behavior. For the stochastic varia…

FARFETCH'D: A Side-Channel Analysis Framework for Privacy Applications on Confidential Virtual Machines
Ruiyi Zhang, Albert Cheu, Adria Gascon, Daniel Moghimi, Phillipp Schoppmann, Michael Schwarz, Octavian Suciu
https://arxiv.org/abs/2506.15924

FARFETCH'D: A Side-Channel Analysis Framework for Privacy Applications on Confidential Virtual Machines
Confidential virtual machines (CVMs) based on trusted execution environments (TEEs) enable new privacy-preserving solutions. Yet, they leave side-channel leakage outside their threat model, shifting the responsibility of mitigating such attacks to developers. However, mitigations are either not generic or too slow for practical use, and developers currently lack a systematic, efficient way to measure and compare leakage across real-world deployments. In this paper, we present FARFETCH'D, an ope…

The Win Ratio at the Design Stage of Clinical Trials
David Kronthaler, Matthias Schwenkglenks, Felix Beuschlein, Ulrike Held
https://arxiv.org/abs/2507.15685

The Win Ratio at the Design Stage of Clinical Trials
The win ratio offers a flexible approach to incorporate the hierarchy of clinical outcomes into the analysis of a composite endpoint, enabling simultaneous consideration of multiple outcome types, unlike traditional time-to-first-event (TTFE) analysis or focus on a single outcome. We examined the statistical power of the win ratio compared to single-endpoint analyses and TTFE analysis through a case study and simulation studies. Furthermore, we provide a novel formula to estimate the required s…

A Guide to Stakeholder Analysis for Cybersecurity Researchers
James C Davis, Sophie Chen, Huiyun Peng, Paschal C Amusuo, Kelechi G Kalu
https://arxiv.org/abs/2508.14796 https://…

A Guide to Stakeholder Analysis for Cybersecurity Researchers
Stakeholder-based ethics analysis is now a formal requirement for submissions to top cybersecurity research venues. This requirement reflects a growing consensus that cybersecurity researchers must go beyond providing capabilities to anticipating and mitigating the potential harms thereof. However, many cybersecurity researchers may be uncertain about how to proceed in an ethics analysis. In this guide, we provide practical support for that requirement by enumerating stakeholder types and mappi…

Weighted Parameter Estimators of the Generalized Extreme Value Distribution in the Presence of Missing Observations
James H. McVittie, Orla A. Murphy
https://arxiv.org/abs/2506.15964

Weighted Parameter Estimators of the Generalized Extreme Value Distribution in the Presence of Missing Observations
Missing data occur in a variety of applications of extreme value analysis. In the block maxima approach to an extreme value analysis, missingness is often handled by either ignoring missing observations or dropping a block of observations from the analysis. However, in some cases, missingness may occur due to equipment failure during an extreme event, which can lead to bias in estimation. In this work, we propose weighted maximum likelihood and weighted moment-based estimators for the generaliz…

SaMOSA: Sandbox for Malware Orchestration and Side-Channel Analysis
Meet Udeshi, Venkata Sai Charan Putrevu, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami
https://arxiv.org/abs/2508.14261

SaMOSA: Sandbox for Malware Orchestration and Side-Channel Analysis
Cyber-attacks on operational technology (OT) and cyber-physical systems (CPS) have increased tremendously in recent years with the proliferation of malware targeting Linux-based embedded devices of OT and CPS systems. Comprehensive malware detection requires dynamic analysis of execution behavior in addition to static analysis of binaries. Safe execution of malware in a manner that captures relevant behaviors via side-channels requires a sandbox environment. Existing Linux sandboxes are built f…