Tootfinder

TIL that the behavior of the “sort” utility differs between MacOS and Debian Linux.
[UPDATE: See replies; the behavior depends on the LANG value in surprising and pernicious ways.]
/tmp> uname ; sort problem
Darwin
OS-X
OSCO
tbray.org /tmp/ 503> uname ; sort problem
Linux
OSCO
OS-X
Does anyone other than me find this surprising?
#Linux …

Moody Urbanity - Beings 🔶
情绪化城市 - 灵 🔶
📷 Nikon FE
🎞️ Lucky SHD 400
#filmphotography #Photography #blackandwhite

Unpacking Personal(?!) Health Informatics: An Investigation of Awareness, Understanding, And Leveraged Utility in India
Shyama Sastha Krishnamoorthy Srinivasan, Mohan Kumar, Pushpendra Singh
https://arxiv.org/abs/2509.01231

Unpacking Personal(?!) Health Informatics: An Investigation of Awareness, Understanding, And Leveraged Utility in India
Personal Health Informatics (PHI), which leverages digital tools and information systems to support health assessment and self-care, holds promise for empowering individuals and transforming healthcare delivery. However, barriers to its adoption remain underexplored in the Indian context. This study investigates PHI adoption among Indian users and stakeholders using a multi-method approach. An awareness survey (n = 87) examined the usage of wearables and general PHI engagement, followed by semi…

Poolformer: Recurrent Networks with Pooling for Long-Sequence Modeling
Daniel Gallo Fern\'andez
https://arxiv.org/abs/2510.02206 https://arxiv.org/pdf/…

Poolformer: Recurrent Networks with Pooling for Long-Sequence Modeling
Sequence-to-sequence models have become central in Artificial Intelligence, particularly following the introduction of the transformer architecture. While initially developed for Natural Language Processing, these models have demonstrated utility across domains, including Computer Vision. Such models require mechanisms to exchange information along the time dimension, typically using recurrent or self-attention layers. However, self-attention scales quadratically with sequence length, limiting …

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
Andr\'es Corrada-Emmanuel
https://arxiv.org/abs/2510.00821 https://arxiv.org/…

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
If two experts disagree on a test, we may conclude both cannot be 100 per cent correct. But if they completely agree, no possible evaluation can be excluded. This asymmetry in the utility of agreements versus disagreements is explored here by formalizing a logic of unsupervised evaluation for classifiers. Its core problem is computing the set of group evaluations that are logically consistent with how we observe them agreeing and disagreeing in their decisions. Statistical summaries of their al…

Towards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models
Gaurav Negi, Atul Kr. Ojha, Omnia Zayed, Paul Buitelaar
https://arxiv.org/abs/2509.02363

Towards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models
We propose a scalable method for constructing a temporal opinion knowledge base with large language models (LLMs) as automated annotators. Despite the demonstrated utility of time-series opinion analysis of text for downstream applications such as forecasting and trend analysis, existing methodologies underexploit this potential due to the absence of temporally grounded fine-grained annotations. Our approach addresses this gap by integrating well-established opinion mining formulations into a d…

Ouch, very familiar:
> I maintain the project alone, as over the years the community has not expressed a need for more active participation. This is typical for infrastructure-level solutions that users don’t interact with directly.
From https://www.theregister.com/2025/08/27/pop

Putin on the code: DoD reportedly relies on utility written by Russian dev
updated: Fast-glob is widely used in government, security lab says

A Review of Software for Designing and Operating Quantum Networks
Robert J. Hayek, Joaquin Chung, Rajkumar Kettimuthu
https://arxiv.org/abs/2510.00203 https://

A Review of Software for Designing and Operating Quantum Networks
Quantum network protocol development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around the three-p…

Statistics-Friendly Confidentiality Protection for Establishment Data, with Applications to the QCEW
Kaitlyn Webb, Prottay Protivash, John Durrell, Daniell Toth, Aleksandra Slavkovi\'c, Daniel Kifer
https://arxiv.org/abs/2509.01597

Statistics-Friendly Confidentiality Protection for Establishment Data, with Applications to the QCEW
Confidentiality for business data is an understudied area of disclosure avoidance, where legacy methods struggle to provide acceptable results. Modern formal privacy techniques designed for person-level data do not provide suitable confidentiality/utility trade-offs due to the highly skewed nature of business data and because extreme outlier records are often important contributors to query answers. In this paper, inspired by Gaussian Differential Privacy, we propose a novel confidentiality fra…

TREE:Token-Responsive Energy Efficiency Framework For Green AI-Integrated 6G Networks
Tao Yu, Kaixuan Huang, Tengsheng Wang, Jihong Li, Shunqing Zhang, Shuangfeng Han, Xiaoyun Wang, Qunsong Zeng, Kaibin Huang, Vincent K. N. Lau
https://arxiv.org/abs/2509.02250

TREE:Token-Responsive Energy Efficiency Framework For Green AI-Integrated 6G Networks
As wireless networks evolve toward AI-integrated intelligence, conventional energy-efficiency metrics fail to capture the value of AI tasks. In this paper, we propose a novel EE metric called Token-Responsive Energy Efficiency (TREE), which incorporates the token throughput of large models as network utility carriers into the system utility. Based on this metric, we analyze the design principles of AI-integrated 6G networks from the perspective of three critical AI elements, namely computing po…

Clarifying Semantics of In-Context Examples for Unit Test Generation
Chen Yang, Lin Yang, Ziqi Wang, Dong Wang, Jianyi Zhou, Junjie Chen
https://arxiv.org/abs/2510.01994 https:/…

Clarifying Semantics of In-Context Examples for Unit Test Generation
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context examples significantly influences the effectiveness of generated tests-poorly structured or semantically unclear test examples often lead to suboptimal outputs. In this paper, we propose CLAST, a novel technique that systematically refines unit tests to improve their semantic clarity, thereby enhancing their utility as i…

Modeling Product Ecosystems
Tridib Banerjee
https://arxiv.org/abs/2510.00036 https://arxiv.org/pdf/2510.00036

Modeling Product Ecosystems
This paper develops a dynamical-systems framework for modeling influence propagation in product adoption networks, formulated as a positive linear system with Metzler interaction matrices and utility-based decay. Exact solutions are derived for constant, piecewise-constant, and fully time-varying interaction structures using matrix exponentials and the Peano--Baker series. It establishes five results: (i) positive interactions guarantee nonnegative amplification, (ii) perceived utility saturate…

Predicting MacroB12: Data-Driven Assessment of Pre-PEG B12 Utility and Clinical Caveats
Carmen Fr\'ias-Ruiz (Hospital Universitario Nuestra Se\~nora de Candelaria), Jos\'e Mar\'ia G\'alvez-Navas (CIBERESP, Andalusian School of Public Health, Instituto de Investigaci\'on Biosanitaria ibs.GRANADA, University of Granada), Isabel Garc\'ia-Calcerrada (Hospital Universitario Nuestra Se\~nora de Candelaria), Silvia Heras Fl\'orez (Hospital Universitario Nuestra Se\…

Predicting MacroB12: Data-Driven Assessment of Pre-PEG B12 Utility and Clinical Caveats
MacroB12 interference presents a significant challenge in the diagnosis of Vitamin B12 status, potentially masking true deficiency. To establish robust predictors and quantify the utility of pre-polyethylene glycol (PEG) B12 levels, we conducted a retrospective analysis of 875 individuals with hypercobalaminaemia (greater than 1000 pg/mL), using multiple imputation to handle missing data. Multivariable regression modelling revealed that MacroB12 positivity (less than 30% PEG recovery) was indep…

Privacy, Informed Consent and the Demand for Anonymisation of Smart Meter Data
Saurab Chhachhi, Fei Teng
https://arxiv.org/abs/2509.00101 https://arxiv.org…

Privacy, Informed Consent and the Demand for Anonymisation of Smart Meter Data
Access to smart meter data offers system-wide benefits but raises significant privacy concerns due to the personal information it contains. Privacy-preserving techniques could facilitate wider access, though they introduce privacy-utility trade-offs. Understanding consumer valuations for anonymisation can help identify appropriate trade-offs. However, existing studies do not focus on anonymisation specifically or account for information asymmetries regarding privacy risks, raising questions abo…

Assortment Optimization and the Sample Average Approximation
Hassaan Khalid, Bradley Sturt
https://arxiv.org/abs/2510.00850 https://arxiv.org/pdf/2510.0085…

Assortment Optimization and the Sample Average Approximation
We consider a simple approach to solving assortment optimization under the random utility maximization model. The approach uses Monte-Carlo simulation to construct a ranking-based choice model that serves as a proxy for the true choice model, followed by finding an assortment that is optimal with respect to that proxy. In this paper, we make that approach more viable by developing faster algorithms for finding assortments that are optimal under ranking-based choice models. Our algorithms are ba…

"Google’s new plan to keep its data centers from stressing the grid"
#Google #Technology
https://www.

Google’s new plan to keep its data centers from stressing the grid
AI data centers are set to swamp U.S. power grids. Google’s new utility deals aim to flip the script — shifting workloads to ease strain and speed its…

A Linear Programming Approach to Estimate the Core in Cooperative Games
J Camacho, JC Gon\c{c}alves-Dosantos, J S\'anchez-Soriano
https://arxiv.org/abs/2510.01766 https://…

A Linear Programming Approach to Estimate the Core in Cooperative Games
This paper proposes a novel algorithm to approximate the core of transferable utility (TU) cooperative games via linear programming. Given the computational hardness of determining the full core, our approach provides a tractable approximation by sampling extreme points through randomized linear problems (LPs). We analyze its convergence and computational complexity, and validate its effectiveness through extensive simulations on various game models. Our results show that the method is scalable…

I've recently had a #dream. I dreamt that for some reason I put my supper into the utility building. And when I went there to get it, I've found some very old chocolates in the drawer. I've started rummaging through it to find them all, with the goal of photographing it and showing this precious treasure to y'all! And of course attempting to eat them afterwards, because what could possibly go wrong with a 30-year old chocolate?

Delay-Augmented Stacked Intelligent Surfaces: Potential, Challenges, and Opportunities
Hibatallah Alwazani, Omran Abbas, Loic Markley, Anas Chaaban
https://arxiv.org/abs/2510.01411

Delay-Augmented Stacked Intelligent Surfaces: Potential, Challenges, and Opportunities
Stacked intelligent surfaces (SIS)s have been proposed recently as an enabling technology for Holographic Multiple Input Multiple Output (HMIMO) and Ultra-massive MIMO (umMIMO) technologies. Their utility can extend beyond spatial wave-domain processing of signals if they are enhanced with strategically-tuned symbol-duration level delays to enable temporal processing as well. In this work, we introduce the idea of a delay-augmented SIS (DA-SIS). We shed light on the feasibility of realizing del…

New York-based Kaizen, which provides a commerce platform for government agencies to offer services like utility billing, raised a $21M Series A led by NEA (Chris Metinko/Axios)
https://www.axios.com/pro/enterprise-software-deals/202…

Exclusive: Govtech startup Kaizen raises $21M for commerce platform
NEA led the round.

Automatic Screening of Parkinson's Disease from Visual Explorations
Maria F. Alcala-Durand, J. Camilo Puerta-Acevedo, Juli\'an D. Arias-Londo\~no, Juan I. Godino-Llorente
https://arxiv.org/abs/2509.01326

Automatic Screening of Parkinson's Disease from Visual Explorations
Eye movements can reveal early signs of neurodegeneration, including those associated with Parkinson's Disease (PD). This work investigates the utility of a set of gaze-based features for the automatic screening of PD from different visual exploration tasks. For this purpose, a novel methodology is introduced, combining classic fixation/saccade oculomotor features (e.g., saccade count, fixation duration, scanned area) with features derived from gaze clusters (i.e., regions with a considerable a…

First-principles investigation of Sr-Ce-M-O perovskites for solar thermochemical water splitting
Sachin Kumar, Pritam Ghosh, Gopalakrishnan Sai Gautam
https://arxiv.org/abs/2509.00779

First-principles investigation of Sr-Ce-M-O perovskites for solar thermochemical water splitting
Using density functional theory based calculations, we systematically examine the utility of Sr-M-O and Sr-Ce-M-O perovskites for solar thermochemical water splitting, a promising route for sustainable hydrogen production. Importantly, we identify Sr$_{0.5}$Ce$_{0.5}$MnO$_3$ and Sr$_{0.5}$Ce$_{0.5}$CrO$_3$ to be promising candidates, exhibiting optimal oxygen vacancy formation energy and 0 K thermodynamic stability.

Cultural tightness and social cohesion under evolving norms
Filippo Zimmaro, Jacopo Grilli, Mirta Galesic, Alexander J. Stewart
https://arxiv.org/abs/2509.01848 https://

Cultural tightness and social cohesion under evolving norms
Successful collective action on issues from climate change to the maintenance of democracy depends on societal properties such as cultural tightness and social cohesion. How these properties evolve is not well understood because they emerge from a complex interplay between beliefs and behaviors that are usually modeled separately. Here we address this challenge by developing a game-theoretical framework incorporating norm-utility models to study the coevolutionary dynamics of cooperative action…

On the role of the design phase in a linear regression
Junho Choi
https://arxiv.org/abs/2509.01861 https://arxiv.org/pdf/2509.01861

On the role of the design phase in a linear regression
The "design phase" refers to a stage in observational studies, during which a researcher constructs a subsample that achieves a better balance in covariate distributions between the treated and untreated units. In this paper, we study the role of this preliminary phase in the context of linear regression, offering a justification for its utility. To that end, we first formalize the design phase as a process of estimand adjustment via selecting a subsample. Then, we show that covariate balance o…

OTMol: Robust Molecular Structure Comparison via Optimal Transport
Xiaoqi Wei, Xuhang Dai, Yaqi Wu, Yanxiang Zhao, Yingkai Zhang, Zixuan Cang
https://arxiv.org/abs/2509.01550 ht…

OTMol: Robust Molecular Structure Comparison via Optimal Transport
Root-mean-square deviation (RMSD) is widely used to assess structural similarity in systems ranging from flexible ligand conformers to complex molecular cluster configurations. Despite its wide utility, RMSD calculation is often challenged by inconsistent atom ordering, indistinguishable configurations in molecular clusters, and potential chirality inversion during alignment. These issues highlight the necessity of accurate atom-to-atom correspondence as a prerequisite for meaningful alignment.…

Erdos-Turan photonic Ising machines with record-high coupling resolution
Huaqiang Li, Guangfeng Wang, Erez Hasman, Bo Wang, Xianfeng Chen
https://arxiv.org/abs/2510.01998 https:…

Erdos-Turan photonic Ising machines with record-high coupling resolution
Ising machines have emerged as promising platforms for efficiently tackling a wide range of combinatorial optimization problems relevant to resource allocation, statistical inference and deep learning, yet their practical utility is fundamentally constrained by the coarse resolution of spin-spin couplings (Jij). Current implementations, relying on direct modulation of physical parameters, achieve at most 256 discrete coupling levels, which severely hinder the faithfully modeling of arbitrary re…

On The Road - To Xi’An 🏮
在路上 - 去西安 🏮
📷 Minolta Hi-Matic AF
🎞️Kentmere Pan 200
#filmphotography #Photography #blackandwhite

Soft inductive limits of operator systems and a noncommutative Lazar-Lindenstrauss theorem
Kristin Courtney, Niklas Galke, Lauritz van Luijk, Alexander Stottmeister
https://arxiv.org/abs/2510.02019

Soft inductive limits of operator systems and a noncommutative Lazar-Lindenstrauss theorem
We establish a flexible generalization of inductive systems of operator systems, which relaxes the usual transitivity (or coherence) condition to an asymptotic version thereof and allows for systems indexed over arbitrary nets. To illustrate the utility of this generalization, we highlight how such systems arise naturally from completely positive approximations of nuclear operator systems. Going further, we utilize an argument of Ding and Peterson to show that a separable operator system is nuc…

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
Andr\'es Corrada-Emmanuel
https://arxiv.org/abs/2510.00821 https://arxiv.org/…

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
If two experts disagree on a test, we may conclude both cannot be 100 per cent correct. But if they completely agree, no possible evaluation can be excluded. This asymmetry in the utility of agreements versus disagreements is explored here by formalizing a logic of unsupervised evaluation for classifiers. Its core problem is computing the set of group evaluations that are logically consistent with how we observe them agreeing and disagreeing in their decisions. Statistical summaries of their al…

Uncertainty-Aware Ankle Exoskeleton Control
Fatima Mumtaza Tourk, Bishoy Galoaa, Sanat Shajan, Aaron J. Young, Michael Everett, Max K. Shepherd
https://arxiv.org/abs/2508.21221 …

Uncertainty-Aware Ankle Exoskeleton Control
Lower limb exoskeletons show promise to assist human movement, but their utility is limited by controllers designed for discrete, predefined actions in controlled environments, restricting their real-world applicability. We present an uncertainty-aware control framework that enables ankle exoskeletons to operate safely across diverse scenarios by automatically disengaging when encountering unfamiliar movements. Our approach uses an uncertainty estimator to classify movements as similar (in-dist…

Exploiting Translational Symmetry for Quantum Computing with Squeezed Cat Qubits
Tomohiro Shitara, Gabriel Mintzer, Yuuki Tokunaga, Suguru Endo
https://arxiv.org/abs/2510.00497 …

Exploiting Translational Symmetry for Quantum Computing with Squeezed Cat Qubits
Squeezed cat quantum error correction (QEC) codes have garnered attention because of their robustness against photon-loss and excitation errors while maintaining the biased-noise property of cat codes. In this work, we reveal the utility of the unexplored translational symmetry of the squeezed cat codes, with applications to autonomous QEC, reliable logical operations, and readout in a non-orthogonal basis. Using the basis under subsystem decomposition spanned by squeezed displaced Fock states,…

A deep learning-driven iterative scheme for high-dimensional HJB equations in portfolio selection with exogenous and endogenous costs
Dong Yan, Nanyi Zhang, Junyi Guo
https://arxiv.org/abs/2509.02267

A deep learning-driven iterative scheme for high-dimensional HJB equations in portfolio selection with exogenous and endogenous costs
In this paper, we first conduct a study of the portfolio selection problem, incorporating both exogenous (proportional) and endogenous (resulting from liquidity risk, characterized by a stochastic process) transaction costs through the utility-based approach. We also consider the intrinsic relationship between these two types of costs. To address the associated nonlinear two-dimensional Hamilton-Jacobi-Bellman (HJB) equation, we propose an innovative deep learning-driven policy iteration scheme…

📉 Rooftop solar is in a slump. Are dark days ahead?
#solar …

Rooftop solar is in a slump. Are dark days ahead?
The popularity of residential solar is seeing a steep reversal due to shifting state and federal policies driven by powerful utility interests. And while some say the decline is simply a mild adjustment, others fear the market for residential solar may be on the brink of a long-term slide.   

Aspects of holographic entanglement using physics-informed-neural-networks
Anirudh Deb, Yaman Sanghavi
https://arxiv.org/abs/2509.25311 https://arxiv.org/p…

Aspects of holographic entanglement using physics-informed-neural-networks
We implement physics-informed-neural-networks (PINNs) to compute holographic entanglement entropy and entanglement wedge cross section. This technique allows us to compute these quantities for arbitrary shapes of the subregions in any asymptotically AdS metric. We test our computations against some known results and further demonstrate the utility of PINNs in examples, where it is not straightforward to perform such computations.

Attack Detection in Dynamic Games with Quadratic Measurements
Muyan Jiang, Anil Aswani
https://arxiv.org/abs/2510.00241 https://arxiv.org/pdf/2510.00241

Attack Detection in Dynamic Games with Quadratic Measurements
This paper studies attack detection for discrete-time linear systems with stochastic process noise that produce both a vulnerable (i.e., attackable) linear measurement and a secured (i.e., unattackable) quadratic measurement. The motivating application of this model is a dynamic-game setting where the quadratic measurement is interpreted as a system-level utility or reward, and control inputs into the linear system are interpreted as control policies that, once applied, are known to all game pa…

Harnessing Information in Incentive Design
Raj Kiriti Velicheti, Subhonmesh Bose, Tamer Ba\c{s}ar
https://arxiv.org/abs/2509.02493 https://arxiv.org/pdf/25…

Harnessing Information in Incentive Design
Incentive design deals with interaction between a principal and an agent where the former can shape the latter's utility through a policy commitment. It is well known that the principal faces an information rent when dealing with an agent that has informational advantage. In this work, we embark on a systematic study of the effect of information asymmetry in incentive design games. Specifically, we first demonstrate that it is in principal's interest to decrease this information asymmetry. To m…

Efficient Approximation Algorithms for Fair Influence Maximization under Maximin Constraint
Xiaobin Rui, Zhixiao Wang, Chen Peng, Qiangpeng Fang, Wei Chen
https://arxiv.org/abs/2509.26579

Efficient Approximation Algorithms for Fair Influence Maximization under Maximin Constraint
Aiming to reduce disparities of influence across different groups, Fair Influence Maximization (FIM) has recently garnered widespread attention. The maximin constraint, a common notion of fairness adopted in the FIM problem, imposes a direct and intuitive requirement that asks the utility (influenced ratio within a group) of the worst-off group should be maximized. Although the objective of FIM under maximin constraint is conceptually straightforward, the development of efficient algorithms wit…

Fundamental Limit of Discrete Distribution Estimation under Utility-Optimized Local Differential Privacy
Sun-Moon Yoon, Hyun-Young Park, Seung-Hyun Nam, Si-Hyeon Lee
https://arxiv.org/abs/2509.24173

Fundamental Limit of Discrete Distribution Estimation under Utility-Optimized Local Differential Privacy
We study the problem of discrete distribution estimation under utility-optimized local differential privacy (ULDP), which enforces local differential privacy (LDP) on sensitive data while allowing more accurate inference on non-sensitive data. In this setting, we completely characterize the fundamental privacy-utility trade-off. The converse proof builds on several key ideas, including a generalized uniform asymptotic Cramér-Rao lower bound, a reduction showing that it suffices to consider a n…

Well worth a read:
The icons in /Applications/Utilities/ in MacOS 26 Tahoe represent a folder full of dead canaries.
via @…
https://

MacOS 26 Tahoe’s Dead Canary Utility App Icons
These are the not the work of carpenters who care about the backs of the cabinets they’re building. These icons are so bad, they look like the work of untrained “How hard can it be?” dilettante carpenters who only last a few days on the job before sawing off one of their own fingers.

https://opensourcesecurity.io/2025/08-oss-one-person/
Great article.

Non-Take-Up of Unemployment Benefit II in Germany: A Longitudinal Perspective Using Administrative Data
J\"urgen Wiemers
https://arxiv.org/abs/2508.21535 https://

Non-Take-Up of Unemployment Benefit II in Germany: A Longitudinal Perspective Using Administrative Data
Extensive research demonstrates that many households eligible for means-tested benefits do not claim them, a phenomenon known as non-take-up. Empirical studies frequently conceptualise non-take-up as a rational decision, occurring when the perceived net utility of claiming is negative. Theoretically, long-term factors can substantially impact this decision. Despite the potential relevance of longitudinal aspects, evidence on their influence remains limited. This study addresses this gap by in…

Capital Games and Growth Equilibria
Ben Abramowitz
https://arxiv.org/abs/2510.00472 https://arxiv.org/pdf/2510.00472

Capital Games and Growth Equilibria
We examine formal games that we call "capital games" in which player payoffs are known, but their payoffs are not guaranteed to be von Neumann-Morgenstern utilities. In capital games, the dynamics of player payoffs determine their utility functions. Different players can have different payoff dynamics. We make no assumptions about where these dynamics come from, but implicitly assume that they come from the players' actions and interactions over time. We define an equilibrium concept called "gr…

QMill: Representative Quantum Data Generation for Quantum Machine Learning Utility
Jason Ludmir, Ian Martin, Nicholas S. DiBrita, Daniel Leeds, Tirthak Patel
https://arxiv.org/abs/2509.21622

QMill: Representative Quantum Data Generation for Quantum Machine Learning Utility
Quantum machine learning (QML) promises significant speedups, particularly when operating on quantum datasets. However, its progress is hindered by the scarcity of suitable training data. Existing synthetic data generation methods fall short in capturing essential entanglement properties, limiting their utility for QML. To address this, we introduce QMill, a low-depth quantum data generation framework that produces entangled, high-quality samples emulating diverse classical and quantum distribu…

Why utility bills are rapidly rising in some states (Tracy J./CBS News)
https://www.cbsnews.com/news/why-utility-bills-are-rapidly-rising-in-some-states/
http://www.memeorandum.com/250823/p15#a250823p15

Exponential Hedging for the Ornstein-Uhlenbeck Process in the Presence of Linear Price Impact
Yan Dolinsky
https://arxiv.org/abs/2509.25472 https://arxiv.o…

Exponential Hedging for the Ornstein-Uhlenbeck Process in the Presence of Linear Price Impact
In this work we study a continuous time exponential utility maximization problem in the presence of a linear temporary price impact. More precisely, for the case where the risky asset is given by the Ornstein-Uhlenbeck diffusion process we compute the optimal portfolio strategy and the corresponding value. Our method of solution relies on duality, and it is purely probabilistic.

Voting is under way in Georgia for two seats on the utilities regulatory commission. Current GOP members are totally in the pocket of the entities they're supposed to be regulating.
https://energyandpolicy.org/georgia-psc-in…

wow. https://bsky.app/profile/bobooten.bsky.social/post/3lxfnkm62p22b

Developer Insights into Designing AI-Based Computer Perception Tools
Maya Guhan (Center for Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA), Meghan E. Hurley (Center for Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA), Eric A. Storch (Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA), John Herrington (Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospita…

Developer Insights into Designing AI-Based Computer Perception Tools
Artificial intelligence (AI)-based computer perception (CP) technologies use mobile sensors to collect behavioral and physiological data for clinical decision-making. These tools can reshape how clinical knowledge is generated and interpreted. However, effective integration of these tools into clinical workflows depends on how developers balance clinical utility with user acceptability and trustworthiness. Our study presents findings from 20 in-depth interviews with developers of AI-based CP to…

Meta builds giant datacenter in rural Louisiana. Utility to add 2.3 GW of gas turbines to power it, if they can source the turbines in a sold-out global market.
And just to be sure, the Louisiana Legislature passed a new law that adds natural gas to the definition of green energy...
Climate anyone?
http…

Meta is sinking $10 billion into rural Louisiana to build the home of its wildest AI aspirations, setting the template for the nation’s grid buildout
The massive data center buildout is underway, requiring massive amounts of new power and, increasingly, more fossil fuels and gas plants.

You only hate on Gemini until you need it to write for you a PowerShell script that generates a Kodi .nfo file for each of the ~50 extras of 'Friends' that don't have entries on TheTVDB.
At least I reviewed the final script and understood / learned how things are done. Shout-out to the excellent Bulk Rename Utility, which made the prepping easier. It was a team effort.
God this was a humbling experience 😑

COMPASS: Robust Feature Conformal Prediction for Medical Segmentation Metrics
Matt Y. Cheung, Ashok Veeraraghavan, Guha Balakrishnan
https://arxiv.org/abs/2509.22240 https://

COMPASS: Robust Feature Conformal Prediction for Medical Segmentation Metrics
In clinical applications, the utility of segmentation models is often based on the accuracy of derived downstream metrics such as organ size, rather than by the pixel-level accuracy of the segmentation masks themselves. Thus, uncertainty quantification for such metrics is crucial for decision-making. Conformal prediction (CP) is a popular framework to derive such principled uncertainty guarantees, but applying CP naively to the final scalar metric is inefficient because it treats the complex, n…

Rhetorik und Realität klaffen auseinander: Axel Oppermann analysiert, wie Microsoft sich als digitale Grundversorgung positioniert – mit allen damit verbundenen Abhängigkeiten. Er warnt vor der Bequemlichkeit, sich zu früh und zu exklusiv in ein einziges Ökosystem zu integrieren. Strategische Mündigkeit ist kein Luxus, sondern Pflicht. @…

„Ich hab’s gesagt“ – Warum Axel Oppermann mit seiner Microsoft-Kritik recht behält - ichsagmal.com
Axel Oppermann, Analyst bei Avispador, wollte eigentlich nur einen fundierten Strategiekommentar schreiben – wurde aber prompt als Microsoft-Basher abgestempelt. Sein Fazit: „Die Positionierung Microsofts als Utility bzw. ‚Planet-Scale-System‘ und die faktische Rolle als digitaler Versorger sind zugleich eine riesige Chance und ein massives Risiko für Kunden und Partner.“ Und Du? Wenn Du im Mittelstand Verantwortung … „Ich hab’s gesagt“ – Warum Axel Oppermann mit seiner Mic…

Discovering Top-k Periodic and High-Utility Patterns
Qingfeng Zhou, Wensheng Gan, Guoting Chen
https://arxiv.org/abs/2509.15732 https://arxiv.org/pdf/2509.…

Discovering Top-k Periodic and High-Utility Patterns
With a user-specified minimum utility threshold (minutil), periodic high-utility pattern mining (PHUPM) aims to identify high-utility patterns that occur periodically in a transaction database. A pattern is deemed periodic if its period aligns with the periodicity constraint set by the user. However, users may not be interested in all periodic high-utility patterns (PHUPs). Moreover, setting minutil in advance is also a challenging issue. To address these issues, our research introduces an algo…

A number of U.S. Coast Guard in operational dress (essentially casual utility/working clothes), seen arriving in the #Chicago Loop (by GSA building on jackson) this morning.

Human-Centered Evaluation of RAG outputs: a framework and questionnaire for human-AI collaboration
Aline Mangold, Kiran Hoffmann
https://arxiv.org/abs/2509.26205 https://…

Human-Centered Evaluation of RAG outputs: a framework and questionnaire for human-AI collaboration
Retrieval-augmented generation (RAG) systems are increasingly deployed in user-facing applications, yet systematic, human-centered evaluation of their outputs remains underexplored. Building on Gienapp's utility-dimension framework, we designed a human-centred questionnaire that assesses RAG outputs across 12 dimensions. We iteratively refined the questionnaire through several rounds of ratings on a set of query-output pairs and semantic discussions. Ultimately, we incorporated feedback from bo…

Giddy up.
✅ PowerToys 0.95 is here: new Light Switch utility, faster Command Palette, and Peek with Spacebar - Windows Command Line
https://devblogs.microsoft.com/commandline/powertoys-0-95-is-her…

PowerToys 0.95 is here: new Light Switch utility, faster Command Palette, and Peek with Spacebar
New month, new release! This one’s packed with quality-of-life improvements, performance boosts, and a bunch of long-standing community requests finally checked off the list — all while keeping the focus on fundamentals like speed and reliability! Get the update by checking for updates in PowerToys or heading to the release page. Let’s dive in! 🆕 […]

Enhancing Differentially Private Linear Regression via Public Second-Moment
Zilong Cao (The School of Mathematics, Northwest University), Hai Zhang (The School of Mathematics, Northwest University)
https://arxiv.org/abs/2508.18037

Enhancing Differentially Private Linear Regression via Public Second-Moment
Leveraging information from public data has become increasingly crucial in enhancing the utility of differentially private (DP) methods. Traditional DP approaches often require adding noise based solely on private data, which can significantly degrade utility. In this paper, we address this limitation in the context of the ordinary least squares estimator (OLSE) of linear regression based on sufficient statistics perturbation (SSP) under the unbounded data assumption. We propose a novel method …

Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs?
Kai Sun, Yin Huang, Srishti Mehra, Mohammad Kachuee, Xilun Chen, Renjie Tao, Zhaojiang Lin, Andrea Jessee, Nirav Shah, Alex Betty, Yue Liu, Anuj Kumar, Wen-tau Yih, Xin Luna Dong
https://arxiv.org/abs/2509.25107

Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs?
The advent of Large Language Models (LLMs) has significantly advanced web-based Question Answering (QA) systems over semi-structured content, raising questions about the continued utility of knowledge extraction for question answering. This paper investigates the value of triple extraction in this new paradigm by extending an existing benchmark with knowledge extraction annotations and evaluating commercial and open-source LLMs of varying sizes. Our results show that web-scale knowledge extract…

Metric response of relative entropy: a universal indicator of quantum criticality
Pritam Sarkar, Diptiman Sen, Arnab Sen
https://arxiv.org/abs/2509.22515 https://

Metric response of relative entropy: a universal indicator of quantum criticality
The information-geometric origin of fidelity susceptibility and its utility as a universal probe of quantum criticality in many-body settings have been widely discussed. Here we explore the metric response of quantum relative entropy (QRE), by tracing out all but $n$ adjacent sites from the ground state of spin chains of finite length $N$, as a parameter of the corresponding Hamiltonian is varied. The diagonal component of this metric defines a susceptibility of the QRE that diverges at quantum…

hey does anyone have a copy of Windows 11 http.sys before and after build 26100.6899, or (since you probably don't want to roll back or install the update just for this purpose) can you run ApplyDeltaB* to materialize the file from WinSxS?
* https://github.com/whitequark/ApplyDeltaB…

GitHub - whitequark/ApplyDeltaB: An utility to apply Windows Update binary patches (i.e. call msdelta.dll!ApplyDeltaB)
An utility to apply Windows Update binary patches (i.e. call msdelta.dll!ApplyDeltaB) - whitequark/ApplyDeltaB

@… amazing, thank you so much for this!
fwiw, there is a way to add a custom timeout to Eleventy’s Fetch utility: https://www.11ty.dev/docs/plugins/fetch/#a

"This PR introduces a new utility, detect-fash, which scans a system for the presence of software and configurations known to be associated with fascist ideologies. This may help identify undesirable and/or malicious activity that may interfere with the intended operations of other systemd utilities."
It seems to detect the presence of Omarchy Linux, Ladybird browser, hyprland, and DHH's ssh public key.

CURE: Centroid-guided Unsupervised Representation Erasure for Facial Recognition Systems
Fnu Shivam, Nima Najafzadeh, Yenumula Reddy, Prashnna Gyawali
https://arxiv.org/abs/2509.19562

CURE: Centroid-guided Unsupervised Representation Erasure for Facial Recognition Systems
In the current digital era, facial recognition systems offer significant utility and have been widely integrated into modern technological infrastructures; however, their widespread use has also raised serious privacy concerns, prompting regulations that mandate data removal upon request. Machine unlearning has emerged as a powerful solution to address this issue by selectively removing the influence of specific user data from trained models while preserving overall model performance. However, …

{testthat} is great for automatic testing. Here are some tricks for the heavy user: #rstats

Series B, Episode 05 - Pressure Point
BLAKE: A church.
GAN: A church?
BLAKE: Place of religious assembly.
GAN: Must be ancient.
BLAKE: The Federation had them all destroyed at the beginning of the New Calendar.
GAN: There's no sign of Kasabi?
https://blake.torpidity.net/m/205/220

Transformer Classification of Breast Lesions: The BreastDCEDL_AMBL Benchmark Dataset and 0.92 AUC Baseline
Naomi Fridman (Ariel University), Anat Goldstein (Ariel University)
https://arxiv.org/abs/2509.26440

Transformer Classification of Breast Lesions: The BreastDCEDL_AMBL Benchmark Dataset and 0.92 AUC Baseline
The error is caused by special characters that arXiv's system doesn't recognize. Here's the cleaned version with all problematic characters replaced: Breast magnetic resonance imaging is a critical tool for cancer detection and treatment planning, but its clinical utility is hindered by poor specificity, leading to high false-positive rates and unnecessary biopsies. This study introduces a transformer-based framework for automated classification of breast lesions in dynamic contrast-enhanced MR…

"Technologies like LLMs have utility, but the absurd way they've been over-hyped, the fact they're being forced on everyone, and the insistence on ignoring the many valid critiques about them make it very difficult to focus on legitimate uses where they might add value."
@… on
The majority AI view: spot on I'd say given advances in my field.
https://www.anildash.com//2025/10/17/the-majority-ai-view/

#Google setzt auf #Kernenergie der nächsten Generation und schließt mit dem US-Versorger #TVA einen Stromabnahmevertrag für den geplanten

Google announced the next step in its nuclear energy plans 
Google is supporting the development of a next-generation nuclear reactor in a bid to get enough electricity for its AI data centers.

Replaced article(s) found for q-fin.PM. https://arxiv.org/list/q-fin.PM/new
[1/1]:
- Optimal Diversification and Leverage in a Utility-Based Portfolio Allocation Approach
Vladimir Markov

holy shit that disk utility icon looks like **I** made it 😳 https://mastodon.social/@BasicAppleGuy/115089810537348465

Diamonds in the rough: Transforming SPARCs of imagination into a game concept by leveraging medium sized LLMs
Julian Geheeb, Farhan Abid Ivan, Daniel Dyrda, Miriam Ansch\"utz, Georg Groh
https://arxiv.org/abs/2509.24730

Diamonds in the rough: Transforming SPARCs of imagination into a game concept by leveraging medium sized LLMs
Recent research has demonstrated that large language models (LLMs) can support experts across various domains, including game design. In this study, we examine the utility of medium-sized LLMs, models that operate on consumer-grade hardware typically available in small studios or home environments. We began by identifying ten key aspects that contribute to a strong game concept and used ChatGPT to generate thirty sample game ideas. Three medium-sized LLMs, LLaMA 3.1, Qwen 2.5, and DeepSeek-R1, …

How Big Data Dilutes Cognitive Resources, Interferes with Rational Decision-making and Affects Wealth Distribution ?
Yongheng Hu
https://arxiv.org/abs/2508.20435 https://…

How Big Data Dilutes Cognitive Resources, Interferes with Rational Decision-making and Affects Wealth Distribution ?
Big data has exponentially dilated consumption demand and speed, but can they all convert to utility? We argue about the measures of consumption and utility acquisition in CARR utility function under the condition of big data interaction, we indicate its weakness, i.e., irrational consumption does not lead to the acquisition of utility. We consider that big data, which is different from macro and micro economic signals, formed by general information entropy, affects agents' rational cognition, …

Electrically Tunable Excitonic-Hyperbolicity in Chirality-Pure Carbon Nanotubes
Jason Lynch, Pavel Shapturenka, Mohammad Mojtaba Sadafi, Zoey Liu, Tobia Ruth, Kritika Jha, Zahra Fakhraai, Hossein Mosallaei, Nader Engheta, Jeffrey A. Fagan, Deep Jariwala
https://arxiv.org/abs/2509.24848

Electrically Tunable Excitonic-Hyperbolicity in Chirality-Pure Carbon Nanotubes
Metamaterials exhibiting hyperbolic dispersion enable unprecedented control over light-matter interactions, from sub-diffraction imaging to enhanced spontaneous emission. However, conventional plasmonic hyperbolic metamaterials suffer from limited tunability and lack intrinsic emission capabilities, constraining their utility for active photonic devices. Here, we demonstrate the first room-temperature, electrically tunable, excitonic hyperbolic metamaterial using aligned films of chirality-pure…

SafeSteer: Adaptive Subspace Steering for Efficient Jailbreak Defense in Vision-Language Models
Xiyu Zeng, Siyuan Liang, Liming Lu, Haotian Zhu, Enguang Liu, Jisheng Dang, Yongbin Zhou, Shuchao Pang
https://arxiv.org/abs/2509.21400

SafeSteer: Adaptive Subspace Steering for Efficient Jailbreak Defense in Vision-Language Models
As the capabilities of Vision Language Models (VLMs) continue to improve, they are increasingly targeted by jailbreak attacks. Existing defense methods face two major limitations: (1) they struggle to ensure safety without compromising the model's utility; and (2) many defense mechanisms significantly reduce the model's inference efficiency. To address these challenges, we propose SafeSteer, a lightweight, inference-time steering framework that effectively defends against diverse jailbreak atta…

"Nearly half of solar capacity will be co-located with storage by 2060, says DNV"
#Batteries #Energy #SolarPower

Nearly half of solar capacity will be co-located with storage by 2060, says DNV
DNV's Energy Transition Outlook 2025 report also predicts that distributed generation solar should begin outpacing utility-scale installations in some parts of the world by 2060. It adds that the levelized cost of electricity for solar is beginning to plateau and is expected to slow to an annual drop below 1% by the 2050s.

When risk defies order: On the limits of fractional stochastic dominance
Christian Laudag\'e, Felix-Benedikt Liebrich
https://arxiv.org/abs/2509.24747 https://

When risk defies order: On the limits of fractional stochastic dominance
Motivated by recent work on monotone additive statistics and questions regarding optimal risk sharing for return-based risk measures, we investigate the existence, structure, and applications of Meyer risk measures. Those are monetary risk measures consistent with fractional stochastic orders suggested by Meyer (1977a,b) as refinement of second-order stochastic dominance (SSD). These so-called $v$-SD orders are based on a threshold utility function $v$. The test utilities defining the associate…

Uneven Lives VIII 👁️
不工整人生 VII 👁️
📷 Minolta Hi-Matic AF
🎞️ERA 100, expired 1994
#filmphotography #Photography #blackandwhite

TF-TransUNet1D: Time-Frequency Guided Transformer U-Net for Robust ECG Denoising in Digital Twin
Shijie Wang, Lei Li
https://arxiv.org/abs/2508.20398 https://

TF-TransUNet1D: Time-Frequency Guided Transformer U-Net for Robust ECG Denoising in Digital Twin
Electrocardiogram (ECG) signals serve as a foundational data source for cardiac digital twins, yet their diagnostic utility is frequently compromised by noise and artifacts. To address this issue, we propose TF-TransUNet1D, a novel one-dimensional deep neural network that integrates a U-Net-based encoder-decoder architecture with a Transformer encoder, guided by a hybrid time-frequency domain loss. The model is designed to simultaneously capture local morphological features and long-range tempo…

Optimal Consumption-Investment with Epstein-Zin Utility under Leverage Constraint
Dejian Tian, Weidong Tian, Jianjun Zhou, Zimu Zhu
https://arxiv.org/abs/2509.21929 https://

Optimal Consumption-Investment with Epstein-Zin Utility under Leverage Constraint
We study optimal portfolio choice under Epstein-Zin recursive utility in the presence of general leverage constraints. We first establish that the optimal value function is the unique viscosity solution to the associated Hamilton-Jacobi-Bellman (HJB) equation, by developing a new dynamic programming principle under constraints. We further demonstrate that the value function admits smoothness and characterize the optimal consumption and investment strategies. In addition, we derive explicit solu…

GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation
Yuanhao Ding, Esteban Garces Arias, Meimingwei Li, Julian Rodemann, Matthias A{\ss}enmacher, Danlu Chen, Gaojuan Fan, Christian Heumann, Chongsheng Zhang
https://arxiv.org/abs/2508.20757

GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation
Open-ended text generation faces a critical challenge: balancing coherence with diversity in LLM outputs. While contrastive search-based decoding strategies have emerged to address this trade-off, their practical utility is often limited by hyperparameter dependence and high computational costs. We introduce GUARD, a self-adaptive decoding method that effectively balances these competing objectives through a novel "Glocal" uncertainty-driven framework. GUARD combines global entropy estimates wi…

Predictive Quality Assessment for Mobile Secure Graphics
Cas Steigstra, Sergey Milyaev, Shaodi You
https://arxiv.org/abs/2509.20028 https://arxiv.org/pdf/2…

Predictive Quality Assessment for Mobile Secure Graphics
The reliability of secure graphic verification, a key anti-counterfeiting tool, is undermined by poor image acquisition on smartphones. Uncontrolled user captures of these high-entropy patterns cause high false rejection rates, creating a significant 'reliability gap'. To bridge this gap, we depart from traditional perceptual IQA and introduce a framework that predictively estimates a frame's utility for the downstream verification task. We propose a lightweight model to predict a quality score…

Utility-based Privacy Preserving Data Mining
Qingfeng Zhou, Wensheng Gan, Zhenlian Qi, Philip S. Yu
https://arxiv.org/abs/2509.15755 https://arxiv.org/pdf/…

Utility-based Privacy Preserving Data Mining
With the advent of big data, periodic pattern mining has demonstrated significant value in real-world applications, including smart home systems, healthcare systems, and the medical field. However, advances in network technology have enabled malicious actors to extract sensitive information from publicly available datasets, posing significant threats to data providers and, in severe cases, hindering societal development. To mitigate such risks, privacy-preserving utility mining (PPUM) has been …

Evaluating Differentially Private Generation of Domain-Specific Text
Yidan Sun, Viktor Schlegel, Srinivasan Nandakumar, Iqra Zahid, Yuping Wu, Warren Del-Pinto, Goran Nenadic, Siew-Kei Lam, Jie Zhang, Anil A Bharath
https://arxiv.org/abs/2508.20452

Evaluating Differentially Private Generation of Domain-Specific Text
Generative AI offers transformative potential for high-stakes domains such as healthcare and finance, yet privacy and regulatory barriers hinder the use of real-world data. To address this, differentially private synthetic data generation has emerged as a promising alternative. In this work, we introduce a unified benchmark to systematically evaluate the utility and fidelity of text datasets generated under formal Differential Privacy (DP) guarantees. Our benchmark addresses key challenges in d…

Relevance to Utility: Process-Supervised Rewrite for RAG
Jaeyoung Kim, Jongho Kim, Seung-won Hwang, Seoho Song, Young-In Song
https://arxiv.org/abs/2509.15577 https://

Relevance to Utility: Process-Supervised Rewrite for RAG
Retrieval-Augmented Generation systems often suffer from a gap between optimizing retrieval relevance and generative utility: retrieved documents may be topically relevant but still lack the content needed for effective reasoning during generation. While existing "bridge" modules attempt to rewrite the retrieved text for better generation, we show how they fail to capture true document utility. In this work, we propose R2U, with a key distinction of directly optimizing to maximize the probabili…

"South Africa court halts natural gas power plant project, cites climate commitments"
#SouthAfrica #FossilFuels #Energy

Private Hyperparameter Tuning with Ex-Post Guarantee
Badih Ghazi, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
https://arxiv.org/abs/2508.15183 ht…

Private Hyperparameter Tuning with Ex-Post Guarantee
The conventional approach in differential privacy (DP) literature formulates the privacy-utility trade-off with a "privacy-first" perspective: for a predetermined level of privacy, a certain utility is achievable. However, practitioners often operate under a "utility-first" paradigm, prioritizing a desired level of utility and then determining the corresponding privacy cost. Wu et al. [2019] initiated a formal study of this "utility-first" perspective by introducing ex-post DP. They demonstra…

Increasing Value of Information Implies Separable Utility
Michel de Lara (CERMICS)
https://arxiv.org/abs/2510.11102 https://arxiv.org/pdf/2510.11102…

Increasing Value of Information Implies Separable Utility
We consider decision-making under incomplete information about an unknown state of nature. Utility acts (that is, utility vectors indexed by states of nature) and beliefs (probability distributions over the states of nature) are naturally paired by bilinear duality, giving the expected utility. With this pairing, an expected utility maximizer (DM) is characterized by a continuous closed convex comprehensive set of utility acts (c-utility act set). We show that DM M values information more than …

Incentives in Federated Learning with Heterogeneous Agents
Ariel D. Procaccia, Han Shao, Itai Shapira
https://arxiv.org/abs/2509.21612 https://arxiv.org/pd…

Incentives in Federated Learning with Heterogeneous Agents
Federated learning promises significant sample-efficiency gains by pooling data across multiple agents, yet incentive misalignment is an obstacle: each update is costly to the contributor but boosts every participant. We introduce a game-theoretic framework that captures heterogeneous data: an agent's utility depends on who supplies each sample, not just how many. Agents aim to meet a PAC-style accuracy threshold at minimal personal cost. We show that uncoordinated play yields pathologies: pure…

IntentionReasoner: Facilitating Adaptive LLM Safeguards through Intent Reasoning and Selective Query Refinement
Yuanzhe Shen, Zisu Huang, Zhengkang Guo, Yide Liu, Guanxu Chen, Ruicheng Yin, Xiaoqing Zheng, Xuanjing Huang
https://arxiv.org/abs/2508.20151

IntentionReasoner: Facilitating Adaptive LLM Safeguards through Intent Reasoning and Selective Query Refinement
The rapid advancement of large language models (LLMs) has driven their adoption across diverse domains, yet their ability to generate harmful content poses significant safety challenges. While extensive research has focused on mitigating harmful outputs, such efforts often come at the cost of excessively rejecting harmless prompts. Striking a balance among safety, over-refusal, and utility remains a critical challenge. In this work, we introduce IntentionReasoner, a novel safeguard mechanism th…

"She was useful, but a bit too optimistic": Augmenting Design with Interactive Virtual Personas
Paluck Deep, Monica Bharadhidasan, A. Baki Kocaballi
https://arxiv.org/abs/2508.19463

"She was useful, but a bit too optimistic": Augmenting Design with Interactive Virtual Personas
Personas have been widely used to understand and communicate user needs in human-centred design. Despite their utility, they may fail to meet the demands of iterative workflows due to their static nature, limited engagement, and inability to adapt to evolving design needs. Recent advances in large language models (LLMs) pave the way for more engaging and adaptive approaches to user representation. This paper introduces Interactive Virtual Personas (IVPs): multimodal, LLM-driven, conversational …

Get Global Guarantees: On the Probabilistic Nature of Perturbation Robustness
Wenchuan Mu, Kwan Hui Lim
https://arxiv.org/abs/2508.19183 https://arxiv.org/…

Get Global Guarantees: On the Probabilistic Nature of Perturbation Robustness
In safety-critical deep learning applications, robustness measures the ability of neural models that handle imperceptible perturbations in input data, which may lead to potential safety hazards. Existing pre-deployment robustness assessment methods typically suffer from significant trade-offs between computational cost and measurement precision, limiting their practical utility. To address these limitations, this paper conducts a comprehensive comparative analysis of existing robustness definit…

Tool Calling for Arabic LLMs: Data Strategies and Instruction Tuning
Asim Ersoy, Enes Altinisik, Husrev Taha Sencar, Kareem Darwish
https://arxiv.org/abs/2509.20957 https://

Tool Calling for Arabic LLMs: Data Strategies and Instruction Tuning
Tool calling is a critical capability that allows Large Language Models (LLMs) to interact with external systems, significantly expanding their utility. However, research and resources for tool calling are predominantly English-centric, leaving a gap in our understanding of how to enable this functionality for other languages, such as Arabic. This paper investigates three key research questions: (1) the necessity of in-language (Arabic) tool-calling data versus relying on cross-lingual transfer…

Strategyproof Randomized Social Choice for Restricted Sets of Utility Functions
Patrick Lederer
https://arxiv.org/abs/2508.16195 https://arxiv.org/pdf/2508…

Strategyproof Randomized Social Choice for Restricted Sets of Utility Functions
Social decision schemes (SDSs) map the voters' preferences over multiple alternatives to a probability distribution over these alternatives. In a seminal result, Gibbard (1977) has characterized the set of SDSs that are strategyproof with respect to all utility functions and his result implies that all such SDSs are either unfair to the voters or alternatives, or they require a significant amount of randomization. To circumvent this negative result, we propose the notion of $U$-strategyproofnes…

PRISM: Robust VLM Alignment with Principled Reasoning for Integrated Safety in Multimodality
Nanxi Li, Zhengyue Zhao, Chaowei Xiao
https://arxiv.org/abs/2508.18649 https://

PRISM: Robust VLM Alignment with Principled Reasoning for Integrated Safety in Multimodality
Safeguarding vision-language models (VLMs) is a critical challenge, as existing methods often suffer from over-defense, which harms utility, or rely on shallow alignment, failing to detect complex threats that require deep reasoning. To this end, we introduce PRISM (Principled Reasoning for Integrated Safety in Multimodality), a system2-like framework that aligns VLMs by embedding a structured, safety-aware reasoning process. Our framework consists of two key components: PRISM-CoT, a dataset th…

LatentGuard: Controllable Latent Steering for Robust Refusal of Attacks and Reliable Response Generation
Huizhen Shu, Xuying Li, Zhuo Li
https://arxiv.org/abs/2509.19839 https:/…

LatentGuard: Controllable Latent Steering for Robust Refusal of Attacks and Reliable Response Generation
Achieving robust safety alignment in large language models (LLMs) while preserving their utility remains a fundamental challenge. Existing approaches often struggle to balance comprehensive safety with fine-grained controllability at the representation level. We introduce LATENTGUARD, a novel three-stage framework that combines behavioral alignment with supervised latent space control for interpretable and precise safety steering. Our approach begins by fine-tuning an LLM on rationalized datase…

Evaluating the Evaluators: Are readability metrics good measures of readability?
Isabel Cachola, Daniel Khashabi, Mark Dredze
https://arxiv.org/abs/2508.19221 https://

Evaluating the Evaluators: Are readability metrics good measures of readability?
Plain Language Summarization (PLS) aims to distill complex documents into accessible summaries for non-expert audiences. In this paper, we conduct a thorough survey of PLS literature, and identify that the current standard practice for readability evaluation is to use traditional readability metrics, such as Flesch-Kincaid Grade Level (FKGL). However, despite proven utility in other fields, these metrics have not been compared to human readability judgments in PLS. We evaluate 8 readability met…

A Collusion-Resistance Privacy-Preserving Smart Metering Protocol for Operational Utility
Farid Zaredar, Morteza Amini
https://arxiv.org/abs/2508.14744 https://

A Collusion-Resistance Privacy-Preserving Smart Metering Protocol for Operational Utility
Modern grids have adopted advanced metering infrastructure (AMI) to facilitate bidirectional communication between smart meters and control centers. This enables smart meters to report consumption values at predefined intervals to utility providers for purposes including demand balancing, load forecasting, dynamic billing, and operational efficiency. Compared to traditional power grids, smart grids offer advantages such as enhanced reliability, improved energy efficiency, and increased security…

LatentGuard: Controllable Latent Steering for Robust Refusal of Attacks and Reliable Response Generation
Huizhen Shu, Xuying Li, Zhuo Li
https://arxiv.org/abs/2509.19839 https:/…

LatentGuard: Controllable Latent Steering for Robust Refusal of Attacks and Reliable Response Generation
Achieving robust safety alignment in large language models (LLMs) while preserving their utility remains a fundamental challenge. Existing approaches often struggle to balance comprehensive safety with fine-grained controllability at the representation level. We introduce LATENTGUARD, a novel three-stage framework that combines behavioral alignment with supervised latent space control for interpretable and precise safety steering. Our approach begins by fine-tuning an LLM on rationalized datase…

Thinking Augmented Pre-training
Liang Wang, Nan Yang, Shaohan Huang, Li Dong, Furu Wei
https://arxiv.org/abs/2509.20186 https://arxiv.org/pdf/2509.20186

Thinking Augmented Pre-training
This paper introduces a simple and scalable approach to improve the data efficiency of large language model (LLM) training by augmenting existing text data with thinking trajectories. The compute for pre-training LLMs has been growing at an unprecedented rate, while the availability of high-quality data remains limited. Consequently, maximizing the utility of available data constitutes a significant research challenge. A primary impediment is that certain high-quality tokens are difficult to le…

Reliability, Embeddedness, and Agency: A Utility-Driven Mathematical Framework for Agent-Centric AI Adoption
Faruk Alpay, Taylan Alpay
https://arxiv.org/abs/2508.12896 https://

Reliability, Embeddedness, and Agency: A Utility-Driven Mathematical Framework for Agent-Centric AI Adoption
We formalize three design axioms for sustained adoption of agent-centric AI systems executing multi-step tasks: (A1) Reliability > Novelty; (A2) Embed > Destination; (A3) Agency > Chat. We model adoption as a sum of a decaying novelty term and a growing utility term and derive the phase conditions for troughs/overshoots with full proofs. We introduce: (i) an identifiability/confounding analysis for $(α,β,N_0,U_{\max})$ with delta-method gradients; (ii) a non-monotone comparator (logistic-with…