Tootfinder

»Wild Wild Web:
Wild Wild Web erzählt Geschichten aus dem Internet. Mal Wissenschaft, mal Tech, mal Investigativ-Recherche und mal Tier-Doku. Janne Knödler und André Dér-Hörmeyer nehmen euch mit zum Headquarter von Spotify und hinter die Great Firewall.«
So alt ist das Web schon und auch deshalb eine eigene BR Podcast Reihe darüber.
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The Sun appoints Jack Elsom as political editor, replacing Harry Cole, who is relocating to the US to become editor at large, and drops its business page (Dominic Ponsford/Press Gazette)
https://pressgazette.co.uk/the-wire/me

Sun names new political editor and drops business page
Jack Elsom replaces Harry Cole who has new US-based role on TV and Youtube.

This https://arxiv.org/abs/2502.18284 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Nested Expectations with Kernel Quadrature
This paper considers the challenging computational task of estimating nested expectations. Existing algorithms, such as nested Monte Carlo or multilevel Monte Carlo, are known to be consistent but require a large number of samples at both inner and outer levels to converge. Instead, we propose a novel estimator consisting of nested kernel quadrature estimators and we prove that it has a faster convergence rate than all baseline methods when the integrands have sufficient smoothness. We then dem…

This https://arxiv.org/abs/2505.24584 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

AutoChemSchematic AI: A Closed-Loop, Physics-Aware Agentic Framework for Auto-Generating Chemical Process and Instrumentation Diagrams
Recent advancements in generative AI have accelerated the discovery of novel chemicals and materials; however, transitioning these discoveries to industrial-scale production remains a critical bottleneck, as it requires the development of entirely new chemical manufacturing processes. Current AI methods cannot auto-generate PFDs or PIDs, despite their critical role in scaling chemical processes, while adhering to engineering constraints. We present a closed loop, physics aware framework for the…

This https://arxiv.org/abs/2505.24380 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

SASP: Strip-Aware Spatial Perception for Fine-Grained Bird Image Classification
Fine-grained bird image classification (FBIC) is not only of great significance for ecological monitoring and species identification, but also holds broad research value in the fields of image recognition and fine-grained visual modeling. Compared with general image classification tasks, FBIC poses more formidable challenges: 1) the differences in species size and imaging distance result in the varying sizes of birds presented in the images; 2) complex natural habitats often introduce strong ba…

This https://arxiv.org/abs/2503.05231 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Kaiwu: A Multimodal Manipulation Dataset and Framework for Robot Learning and Human-Robot Interaction
Cutting-edge robot learning techniques including foundation models and imitation learning from humans all pose huge demands on large-scale and high-quality datasets which constitute one of the bottleneck in the general intelligent robot fields. This paper presents the Kaiwu multimodal dataset to address the missing real-world synchronized multimodal data problems in the sophisticated assembling scenario,especially with dynamics information and its fine-grained labelling. The dataset first provi…

This https://arxiv.org/abs/2505.00849 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

TherMod Communication: Low Power or Hot Air?
The Kirchhoff-Law-Johnson-Noise (KLJN) secure key exchange scheme leverages statistical physics to enable secure communication with zero average power flow in a wired channel. While the original KLJN scheme requires significant power for operation, a recent wireless modification, TherMod, proposed by Basar claims a "low power" implementation. This paper critically examines this claim. We explain that the additional components inherent in Basar's wireless adaptation substantially increase power …

This https://arxiv.org/abs/2506.01982 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Music interpretation and emotion perception: A computational and neurophysiological investigation
This study investigates emotional expression and perception in music performance using computational and neurophysiological methods. The influence of different performance settings, such as repertoire, diatonic modal etudes, and improvisation, as well as levels of expressiveness, on performers' emotional communication and listeners' reactions is explored. Professional musicians performed various tasks, and emotional annotations were provided by both performers and the audience. Audio analysis r…

This https://arxiv.org/abs/2505.16946 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

NY Real Estate Racial Equity Analysis via Applied Machine Learning
This study analyzes tract-level real estate ownership patterns in New York State (NYS) and New York City (NYC) to uncover racial disparities. We use an advanced race/ethnicity imputation model (LSTM+Geo with XGBoost filtering, validated at 89.2% accuracy) to compare the predicted racial composition of property owners to the resident population from census data. We examine both a Full Model (statewide) and a Name-Only LSTM Model (NYC) to assess how incorporating geospatial context affects our pr…

This https://arxiv.org/abs/2506.02197 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution
This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. The goal of this challenge is two fold, (i) restore RAW images with blur and noise degradations, (ii) upscale RAW Bayer images by 2x, considering unknown noise and blur. In the…

This https://arxiv.org/abs/2505.20078 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Notes on Rindler wave packets in Minkowski spacetime
We consider wave packets of a massless scalar field that have well-localized Rindler energy, and examine how their energy appears to a Minkowski observer to see how the classical gravitational blue-shift formula is modified quantum mechanically. We derive, by using the saddle point approximation, an analytic expression for the Minkowski momentum distribution of such Rindler wave packets. We find a universal lower bound on the uncertainty of Minkowski momentum; the momentum distribution can neve…

This https://arxiv.org/abs/2506.02916 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

MMM4Rec: An Transfer-Efficient Framework for Multi-modal Sequential Recommendation
Sequential Recommendation (SR) systems model user preferences by analyzing interaction histories. Although transferable multi-modal SR architectures demonstrate superior performance compared to traditional ID-based approaches, current methods incur substantial fine-tuning costs when adapting to new domains due to complex optimization requirements and negative transfer effects - a significant deployment bottleneck that hinders engineers from efficiently repurposing pre-trained models for novel a…

Baues-Wirsching Cohomology and Svarc Genus in Small Categories
Isaac Carcac\'ia-Campos, Enrique Mac\'ias-Virg\'os, David Mosquera-Lois
https://arxiv.org/abs/2508.00727

Baues-Wirsching Cohomology and Svarc Genus in Small Categories
We prove that for a bifibration P between small categories, the lenght of the cup product in the kernel of the induced morphism in the Baues-Wirsching cohomology with coefficients in any natural system is a lower bound for the homotopic sectional category (also called Svarc genus). Our results extend classical Svarc type inequalties to the categorical setting and introduce a computationally efficient method via a reduced cochain complex for Baues-Wirching cohomology.

This https://arxiv.org/abs/2506.02551 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Impact of convective overshooting on the single-degenerate model of Type Ia supernovae
The single-degenerate (SD) model is one of the principal models for the progenitors of Type Ia supernovae (SNe Ia). However, it faces some challenges, the primary being its inability to account for the observed SN Ia birth rate. Many studies have attempted to address this issue by expanding the parameter space, defined by the initial donor star mass and orbital period, that can lead to SNe Ia, as well as by improving binary population synthesis. While these efforts have led to significant progr…

This https://arxiv.org/abs/2411.17098 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Determination of the binding and $DK$ probability of the $D^{*}_{s0}(2317)$ from the $(\bar{D}\bar K)^-$ mass distributions in $Λ_{b}\to Λ_{c} (\bar{D}\bar K)^-$ decays
We study the $Λ_{b}\toΛ_{c}\bar{D}^{0}K^{-}$ and $Λ_{b}\to Λ_{c}D^{-}\bar{K}^{0}$ decays which proceed via a Cabibbo and $N_c$ favored process of external emission, and we determine the $\bar{D}^{0}K^{-}$ and $D^{-}\bar{K}^{0}$ mass distributions close to the $\bar{D} \bar{K}$ threshold. For this, we use the tree level contribution plus the rescattering of the meson-meson components, using the extension of the local hidden gauge approach to the charm sector that produces the $D^*_{s0}(2317)…

Fourteen House and Senate Democrats warned Harvard on Thursday that they would consider launching a congressional investigation into any major settlement between the University and the Trump administration.
In a two-page letter sent to Harvard President Alan M. Garber ’76, the lawmakers expressed “deep concern” over recent reports that Harvard is weighing a financial settlement with the White House — potentially as much as $500 million — to win back billions of dollars in federal resear…

Congressional Democrats Threaten To Investigate If Harvard Settles With Trump Administration | News | The Harvard Crimson
Fourteen House and Senate Democrats warned Harvard on Thursday that they would consider launching a congressional investigation into any major settlement between the University and the Trump administration.

This https://arxiv.org/abs/2505.08880 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Properties of general stationary axisymmetric spacetimes: circularity and beyond
We analyse properties of general stationary and axisymmetric spacetimes, with a particular focus on circularity -- an accidental symmetry enjoyed by the Kerr metric, and therefore widely assumed when searching for rotating black hole solutions in alternative theories of gravity as well as when constructing models of Kerr mimickers. Within a gauge specified by seven (or six) free functions, the local existence of which we prove, we solve the differential circularity conditions and translate them…

Entanglement Management in Space-Based Quantum Information Networks
Luca Paccard, Agathe Blaise, Fabrice Arnal, Laurent de Forges de Parny
https://arxiv.org/abs/2508.00793 https…

Entanglement Management in Space-Based Quantum Information Networks
With the evolution of quantum computing, quantum sensing and secure quantum communication protocols, the demand for global development of Quantum Information Networks (QIN) has become crucial. Satellites play an indispensable role in enabling connectivity across vast distances, transcending terrestrial limitations. In this article, we explore various ways in which satellites may be involved in the deployment of these novel networks from their integration into the network architecture to the cha…

This https://arxiv.org/abs/2503.10569 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Low-Rank Matrix Regression via Least-Angle Regression
Low-rank matrix regression is a fundamental problem in data science with various applications in systems and control. Nuclear norm regularization has been widely applied to solve this problem due to its convexity. However, it suffers from high computational complexity and the inability to directly specify the rank. This work introduces a novel framework for low-rank matrix regression that addresses both unstructured and Hankel matrices. By decomposing the low-rank matrix into rank-1 bases, the …

This https://arxiv.org/abs/2409.08429 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The Atacama Cosmology Telescope: Systematic Transient Search of Single Observation Maps
We conduct a systematic search for astrophysical transients using data from the Atacama Cosmology Telescope (ACT). The data were taken from 2017 to 2022 in three frequency bands spanning 77 GHz to 277 GHz. In this paper we present a pipeline for transient detection using single observation maps where each pixel of a map contains one observation with an integration time of approximately four minutes. We detect 34 transient events at 27 unique locations. All but two of the transients are associat…

This https://arxiv.org/abs/2506.01402 has been replaced.
initial toot: https://mastoxiv.page/@a…

Sliding Ferroelectrics Induced Hybrid-Order Topological Phase Transitions
We propose ferroelectric layer sliding as a new approach to realize and manipulate topological quantum states in two-dimensional (2D) bilayer magnetic van der Waals materials. We show that stacking monolayer ferromagnetic topological states into layer-spin-locked bilayer antiferromagnetic structures, and introducing sliding ferroelectricity leads to asynchronous topological evolution of different layers (spins) owing to existence of polarization potentials, thereby giving rise to rich layer-res…

GenFair: Systematic Test Generation for Fairness Fault Detection in Large Language Models
Madhusudan Srinivasan, Jubril Abdel
https://arxiv.org/abs/2506.03024

GenFair: Systematic Test Generation for Fairness Fault Detection in Large Language Models
Large Language Models (LLMs) are increasingly deployed in critical domains, yet they often exhibit biases inherited from training data, leading to fairness concerns. This work focuses on the problem of effectively detecting fairness violations, especially intersectional biases that are often missed by existing template-based and grammar-based testing methods. Previous approaches, such as CheckList and ASTRAEA, provide structured or grammar-driven test generation but struggle with low test diver…

📰 Täglich von 6 bis 23 Uhr findest Du hier und auf @… kostenlose News zu vielen Themen. Leider muss ich die Hosting-Rechnungen seit Jahren allein zahlen. Ich will die Amazon-Partnerlinks loswerden, aber das geht nur mit Eurer finanziellen Hilfe.
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KlimaCrew
Ich informiere über Zukunftsthemen, um Menschen vor Risiken zu warnen und Fortschritte sichtbar zu machen.

This https://arxiv.org/abs/2506.01811 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Quantum Circuit Encodings of Polynomial Chaos Expansions
This work investigates the expressive power of quantum circuits in approximating high-dimensional, real-valued functions. We focus on countably-parametric holomorphic maps $u:U\to \mathbb{R}$, where the parameter domain is $U=[-1,1]^{\mathbb{N}}$. We establish dimension-independent quantum circuit approximation rates via the best $n$-term truncations of generalized polynomial chaos (gPC) expansions of these parametric maps, demonstrating that these rates depend solely on the summability exponen…

On the geometry of stack-sorting simplices
Cameron Ake, Spencer F. Lewis, Amanda Louie, Andr\'es R. Vindas-Mel\'endez
https://arxiv.org/abs/2508.00219 https://

On the geometry of stack-sorting simplices
We show that all stack-sorting polytopes are simplices. Furthermore, we show that the stack-sorting polytopes generated from $Ln1$ permutations have relative volume 1. We establish an upper bound for the number of lattice points in a stack-sorting polytope. In particular, stack-sorting polytopes generated from $2Ln1$ permutations have no interior points.

In the extended version of @…'s The Internet Last Week, we spotted this #GitHub incident: https://www.

Disruption with some GitHub services
GitHub's Status Page - Disruption with some GitHub services.

Distributionally Robust Optimization for Aerial Multi-access Edge Computing via Cooperation of UAVs and HAPs
Ziye Jia, Can Cui, Chao Dong, Qihui Wu, Zhuang Ling, Dusit Niyato, Zhu Han
https://arxiv.org/abs/2506.01972

Distributionally Robust Optimization for Aerial Multi-access Edge Computing via Cooperation of UAVs and HAPs
With an extensive increment of computation demands, the aerial multi-access edge computing (MEC), mainly based on unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs), plays significant roles in future network scenarios. In detail, UAVs can be flexibly deployed, while HAPs are characterized with large capacity and stability. Hence, in this paper, we provide a hierarchical model composed of an HAP and multi-UAVs, to provide aerial MEC services. Moreover, considering the errors of c…

This https://arxiv.org/abs/2506.00631 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Phase-space distortion as a key to unraveling galactic bar buckling
For the first time, we investigate the resonant structure of $N$-body galactic bar at the stage of buckling using action-angle variables. We studied the evolution of vertical actions ($J_z$) and angles associated with vertical resonance ($θ_\mathrm{res}=θ_z - θ_R$) for all orbits in the bar. For this purpose, we divide the orbits into types according to the behavior (libration or circulation) of their resonant angle with respect to fixed points $θ_\mathrm{res}=0$ and $π$ (vertical resonanc…

Identical representation functions of linear forms
S\'andor Kiss, Csaba S\'andor
https://arxiv.org/abs/2506.03983 https://arx…

Identical representation functions of linear forms
For a set of natural numbers $A$, let $R_{A}(n)$ be the number of representations of a natural number $n$ as the sum of two terms from $A$. Many years ago, Nathanson studied the conditions for the set $A$ and $B$ of natural numbers that are needed to guarantee that $R_{A}(n) = R_{B}(n)$ for every positive integer $n$. In the last decades, similar questions have been studied by many authors. In this paper, we extend Nathanson's result to representation functions associated to linear forms and we…

This https://arxiv.org/abs/2502.12089 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
Natural data is often organized as a hierarchical composition of features. How many samples do generative models need in order to learn the composition rules, so as to produce a combinatorially large number of novel data? What signal in the data is exploited to learn those rules? We investigate these questions in the context of diffusion models both theoretically and empirically. Theoretically, we consider a simple probabilistic context-free grammar - a tree-like graphical model used to represe…

A Parameter-free Decentralized Algorithm for Composite Convex Optimization
Xiaokai Chen, Ilya Kuruzov, Gesualdo Scutari, Alexander Gasnikov
https://arxiv.org/abs/2508.01466 http…

A Parameter-free Decentralized Algorithm for Composite Convex Optimization
The paper studies decentralized optimization over networks, where agents minimize a composite objective consisting of the sum of smooth convex functions--the agents' losses--and an additional nonsmooth convex extended value function. We propose a decentralized algorithm wherein agents ${\it adaptively}$ adjust their stepsize using local backtracking procedures that require ${\it no}$ ${\it global}$ (network) information or extensive inter-agent communications. Our adaptive decentralized method …

This https://arxiv.org/abs/2504.08335 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Entropic bounds for conditionally Gaussian vectors and applications to neural networks
Using entropic inequalities from information theory, we provide new bounds on the total variation and 2-Wasserstein distances between a conditionally Gaussian law and a Gaussian law with invertible covariance matrix. We apply our results to quantify the speed of convergence to Gaussian of a randomly initialized fully connected neural network and its derivatives - evaluated in a finite number of inputs - when the initialization is Gaussian and the sizes of the inner layers diverge to infinity. O…

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
- MARS: Processing-In-Memory Acceleration of Raw Signal Genome Analysis Inside the Storage Subsystem
Soysal, Koliogeorgi, Firtina, Ghiasi, Nadig, Mao, Oliveira, Liang, Zambaku, Sadrosadati, Mutlu
…

This https://arxiv.org/abs/2505.13182 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

Information Science Principles of Machine Learning: A Causal Chain Meta-Framework Based on Formalized Information Mapping
[Objective] This study focuses on addressing the current lack of a unified formal theoretical framework in machine learning, as well as the deficiencies in interpretability and ethical safety assurance. [Methods] A formal information model is first constructed, utilizing sets of well-formed formulas to explicitly define the ontological states and carrier mappings of typical components in machine learning. Learnable and processable predicates, along with learning and processing functions, are in…

After Nano Retina's bankruptcy, "#CortiSight Medical is a fledgling neurostimulation firm that aims to restore sight to hundreds of thousands of blind people through wireless cortical implants" https://

This https://arxiv.org/abs/2505.24034 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Trainin
Reinforcement Learning (RL) has become the most effective post-training approach for improving the capabilities of Large Language Models (LLMs). In practice, because of the high demands on latency and memory, it is particularly challenging to develop an efficient RL framework that reliably manages policy models with hundreds to thousands of billions of parameters. In this paper, we present LlamaRL, a fully distributed, asynchronous RL framework optimized for efficient training of large-scale …

Advancing Speech Quality Assessment Through Scientific Challenges and Open-source Activities
Wen-Chin Huang
https://arxiv.org/abs/2508.00317 https://arxiv.…

Advancing Speech Quality Assessment Through Scientific Challenges and Open-source Activities
Speech quality assessment (SQA) refers to the evaluation of speech quality, and developing an accurate automatic SQA method that reflects human perception has become increasingly important, in order to keep up with the generative AI boom. In recent years, SQA has progressed to a point that researchers started to faithfully use automatic SQA in research papers as a rigorous measurement of goodness for speech generation systems. We believe that the scientific challenges and open-source activities…

[2025-08-04 Mon (UTC), 1 new article found for math.GR Group Theory]
toXiv_bot_toot

A General Approach to Visualizing Uncertainty in Statistical Graphics
Bernarda Petek, David Nabergoj, Erik \v{S}trumbelj
https://arxiv.org/abs/2508.00937 https://

A General Approach to Visualizing Uncertainty in Statistical Graphics
Visualizing uncertainty is integral to data analysis, yet its application is often hindered by the need for specialized methods for quantifying and representing uncertainty for different types of graphics. We introduce a general approach that simplifies this process. The core idea is to treat the statistical graphic as a function of the underlying distribution. Instead of first calculating uncertainty metrics and then plotting them, the method propagates uncertainty through to the visualization…

This https://arxiv.org/abs/2504.14870 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Acting Less is Reasoning More! Teaching Model to Act Efficiently
Tool-integrated reasoning (TIR) augments large language models (LLMs) with the ability to invoke external tools during long-form reasoning, such as search engines and code interpreters, to solve tasks beyond the capabilities of internal reasoning. While reinforcement learning (RL) has shown promise in training such agents, most of existing approaches typically optimize only for final correctness without considering the efficiency or necessity of external tool use. This often leads to excessive …

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- The time slot allocation problem in liberalised passenger railway markets: a multi-objective appr...
Be\v{s}inovi\'c, Garc\'ia-R\'odenas, L\'opez-Garc\'ia, L\'opez-G\'omez, Mart\'i…

This https://arxiv.org/abs/2505.19636 has been replaced.
initial toot: https://mastoxiv.page/@a…

Longitudinal magnetoconductivity in chiral multifold semimetals exemplified by pseudospin-1 nodal points
We embark on computing the longitudinal magnetoconductivity within the semiclassical Boltzmann formalism, where an isotropic triple-point semimetal (TSM) is subjected to collinear electric ($\boldsymbol E $) and magnetic ($\boldsymbol B$) fields. Except for the Drude part, the $B$-dependence arises exclusively from topological properties like the Berry curvature and the orbital magnetic moment. We solve the Boltzmann equations exactly in the linear-response regime, applicable in the limit of we…

If you identify as a neuronationalist, you will be instantly blocked without exception because fascism has no place on my page.
#Fascism #Neuronationalism

Urge Coach to Stop Selling Leather #AnimalRights

Urge Coach to Stop Selling Leather
Cows suffer for leather, and animal agriculture – which includes the leather industry – is a leading contributor to the climate catastrophe. We can help stop this.

Prediction of the SVOM MXT camera end of life spectral performance based onproton irradiation results
Clara Plasse, Diego G\"otz, Aline Meuris, Miguel Fernandez Moita, Philippe Ferrando, Leo Favier, Francesco Ceraudo
#toXiv_bot_toot

Equivariant deformation problems and homotopy operators
Sebasti\'an Daza, Jo\~ao Nuno Mestre
https://arxiv.org/abs/2506.03967 https://

Equivariant deformation problems and homotopy operators
We use homotopy operators for the $L_\infty$-algebra associated with an equivariant deformation problem in order to describe a smooth parametrization of the space of structures around a given one. Along the way we give new algebraic and explicit proofs of rigidity and unobstructedness theorems.

This https://arxiv.org/abs/2505.24198 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control
Can your humanoid walk up and hand you a full cup of beer, without spilling a drop? While humanoids are increasingly featured in flashy demos like dancing, delivering packages, traversing rough terrain, fine-grained control during locomotion remains a significant challenge. In particular, stabilizing a filled end-effector (EE) while walking is far from solved, due to a fundamental mismatch in task dynamics: locomotion demands slow-timescale, robust control, whereas EE stabilization requires rap…

This https://arxiv.org/abs/2505.22769 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

MAC-Gaze: Motion-Aware Continual Calibration for Mobile Gaze Tracking
Mobile gaze tracking faces a fundamental challenge: maintaining accuracy as users naturally change their postures and device orientations. Traditional calibration approaches, like one-off, fail to adapt to these dynamic conditions, leading to degraded performance over time. We present MAC-Gaze, a Motion-Aware continual Calibration approach that leverages smartphone Inertial measurement unit (IMU) sensors and continual learning techniques to automatically detect changes in user motion states and…

This https://arxiv.org/abs/2501.07198 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Large charge operators at large spin from relativistically rotating vortices
We study the ground states of CFTs with a global $U(1)$ symmetry on $\mathbb{R}\times S^2$ in the regime of large charge $Q$ and large angular momentum $J$, using large charge EFT. We find that in the range $Q \ll J \ll Q^2$, the ground state solution is a superfluid densely populated with vortices rotating at a constant angular velocity $Ω$. This is a relativistic generalization of the known (non-relativistic) rigid rotation phase, which corresponds to the small $Ω$ limit of our solution. In…

This https://arxiv.org/abs/2411.16666 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

CatNet: Controlling the False Discovery Rate in LSTM with SHAP Feature Importance and Gaussian Mirrors
We introduce CatNet, an algorithm that effectively controls False Discovery Rate (FDR) and selects significant features in LSTM. CatNet employs the derivative of SHAP values to quantify the feature importance, and constructs a vector-formed mirror statistic for FDR control with the Gaussian Mirror algorithm. To avoid instability due to nonlinear or temporal correlations among features, we also propose a new kernel-based independence measure. CatNet performs robustly on different model settings …

This https://arxiv.org/abs/2502.09304 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG
Graph-RAG constructs a knowledge graph from text chunks to improve retrieval in Large Language Model (LLM)-based question answering. It is particularly useful in domains such as biomedicine, law, and political science, where retrieval often requires multi-hop reasoning over proprietary documents. Some existing Graph-RAG systems construct KNN graphs based on text chunk relevance, but this coarse-grained approach fails to capture entity relationships within texts, leading to sub-par retrieval and…

This https://arxiv.org/abs/2505.24603 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
Gaussian sketching, which consists of pre-multiplying the data with a random Gaussian matrix, is a widely used technique for multiple problems in data science and machine learning, with applications spanning computationally efficient optimization, coded computing, and federated learning. This operation also provides differential privacy guarantees due to its inherent randomness. In this work, we revisit this operation through the lens of Renyi Differential Privacy (RDP), providing a refined pri…

This https://arxiv.org/abs/2503.05651 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Inverting no-hair theorems: How requiring General Relativity solutions restricts scalar-tensor theories
Black hole solutions in general scalar-tensor theories are known to permit hair, i.e. non-trivial scalar profiles and/or metric solutions different from the ones of General Relativity (GR). Imposing that some such solutions$\unicode{x2013}$e.g. Schwarzschild or de Sitter solutions motivated in the context of black hole physics or cosmology$\unicode{x2013}$should exist, the space of scalar-tensor theories is strongly restricted. Here we investigate precisely what these restrictions are within ge…

The Role of the Satellite in Quantum Information Networks
Luca Paccard, Valentin Leloup, Luca Lazzarini, Agathe Blaise, Mailys Guerault, Mickael Faugeron, Fabrice Arnal, Mathieu Bertrand, Raphael Aymeric, Michel Sotom, St\'ephanie Molin, Patrick G\'elard, Pierre Besancenot, Cyrille Laborde, Laurent de Forges de Parny, Mathias van den Bossche
https://

The Role of the Satellite in Quantum Information Networks
Quantum Information Networks (QIN) attract increasing interest, as they will enable interconnection of multiple quantum devices in a distributed organization thus enhancing intrinsic computing, sensing, and security capabilities. The core mechanism of a QIN is quantum state swapping, based on teleportation, which consumes quantum entanglement, and which can be seen in this context as a new kind of network resource. The satellite is expected to play a central role for supporting global connectiv…

An Algorithmic Pipeline for GDPR-Compliant Healthcare Data Anonymisation: Moving Toward Standardisation
Hamza Khan, Lore Menten, Liesbet M. Peeters
https://arxiv.org/abs/2506.02942

An Algorithmic Pipeline for GDPR-Compliant Healthcare Data Anonymisation: Moving Toward Standardisation
High-quality real-world data (RWD) is essential for healthcare but must be transformed to comply with the General Data Protection Regulation (GDPR). GDPRs broad definitions of quasi-identifiers (QIDs) and sensitive attributes (SAs) complicate implementation. We aim to standardise RWD anonymisation for GDPR compliance while preserving data utility by introducing an algorithmic method to identify QIDs and SAs and evaluate utility in anonymised datasets. We conducted a systematic literature review…

This https://arxiv.org/abs/2506.00951 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Physics-Informed Neural Networks for the Relativistic Burgers Equation in the Exterior of a Schwarzschild Black Hole
We introduce a Physics-Informed Neural Networks(PINN) to solve a relativistic Burgers equation in the exterior domain of a Schwarzschild black hole. Our main contribution is a PINN architecture that is able to simulate shock wave formations in such curved spacetime, by training a shock- aware network block and introducing a Godunov-inspired residuals in the loss function. We validate our method with numerical experiments with different kinds of initial conditions. We show its ability to reprodu…

In May, Microsoft launched Signal, a 120-page print magazine focused on its tech and distributed to business leaders every few months, to counter digital noise (Tom Warren/The Verge)
https://www.theverge.com/notepad-microsoft

Why Microsoft has created its own print magazine
Microsoft has created its own print magazine, named Signal. It’s a reaction to the digital noise and ephemeral content.

A Fan-type condition involving bipartite independence number for hamiltonicity in graphs
Hongxi Liu, Long-Tu Yuan, Xiaowen Zhang
https://arxiv.org/abs/2506.02687

A Fan-type condition involving bipartite independence number for hamiltonicity in graphs
The bipartite independence number of a graph $G$, denoted by $\widetildeα(G)$, is defined as the smallest integer $q$ for which there exist positive integers $s$ and $t$ satisfying $s + t = q + 1$, such that for any two disjoint subsets $A, B \subseteq V(G)$ with $|A| = s$ and $|B| = t$, there exists an edge between $A$ and $B$. In this paper, we prove that for a $2$-connected graph $G$ of order at least three, if $\max\{d_G(x),d_G(y)\}\geq \widetildeα(G)$ for any pair of …

This https://arxiv.org/abs/2504.14522 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Biased by Design: Leveraging AI Inherent Biases to Enhance Critical Thinking of News Readers
This paper explores the design of a propaganda detection tool using Large Language Models (LLMs). Acknowledging the inherent biases in AI models, especially in political contexts, we investigate how these biases might be leveraged to enhance critical thinking in news consumption. Countering the typical view of AI biases as detrimental, our research proposes strategies of user choice and personalization in response to a user's political stance, applying psychological concepts of confirmation bia…

This https://arxiv.org/abs/2505.22727 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The galaxy-halo connection of disc galaxies over six orders of magnitude in stellar mass
(Abridged) The relations between stellar ($M_\ast$), gas ($M_{\rm gas}$), baryonic ($M_{\rm bar} = M_\ast + M_{\rm gas}$), and dark matter halo mass ($M_{200}$) provide unique constraints on galaxy formation and cosmology. The shape of the relations constrains how galaxies regulate their growth through gas accretion, star formation, and feedback; their scatter probes the stochasticity of galaxy assembly. Here, we assemble a sample of 49 nearby gas-rich dwarf and massive disc galaxies with unm…

Minnesota Gov. Tim Walz says Democrats need to take a page from Donald Trump’s own playbook.
“Maybe it’s time for us to be a little meaner,” the former vice presidential hopeful said during a speech at the South Carolina Democratic Party’s annual convention in Columbia, South Carolina.
“Maybe it’s time for us to be a little more fierce because we have to ferociously push back on this.”
“When it’s a bully like Donald Trump, you bully the s--t out of him,” Walz added

Walz Tells Dems to ‘Bully the S**t’ Out of Trump or Risk Becoming ‘Roadkill’
The former vice presidential candidate doled out harsh words for both the president and his own party.

Linesearch-free adaptive Bregman proximal gradient for convex minimization without relative smoothness
Hongjia Ou, Puya Latafat, Andreas Themelis
https://arxiv.org/abs/2508.01353

Linesearch-free adaptive Bregman proximal gradient for convex minimization without relative smoothness
This paper introduces adaptive Bregman proximal gradient algorithms for solving convex composite minimization problems without relying on global relative smoothness or strong convexity assumptions. Building upon recent advances in adaptive stepsize selections, the proposed methods generate stepsizes based on local curvature estimates, entirely eliminating the need for backtracking linesearch. A key innovation is a Bregman generalization of Young's inequality, which allows controlling a critical…

AC-Refiner: Efficient Arithmetic Circuit Optimization Using Conditional Diffusion Models
Chenhao Xue, Kezhi Li, Jiaxing Zhang, Yi Ren, Zhengyuan Shi, Chen Zhang, Yibo Lin, Lining Zhang, Qiang Xu, Guangyu Sun
https://arxiv.org/abs/2507.02598

AC-Refiner: Efficient Arithmetic Circuit Optimization Using Conditional Diffusion Models
Arithmetic circuits, such as adders and multipliers, are fundamental components of digital systems, directly impacting the performance, power efficiency, and area footprint. However, optimizing these circuits remains challenging due to the vast design space and complex physical constraints. While recent deep learning-based approaches have shown promise, they struggle to consistently explore high-potential design variants, limiting their optimization efficiency. To address this challenge, we pro…

Helicity Fluxes and Hemispheric Helicity Rule of Active Regions Emerging from the Convection Zone Dynamo
V. V. Pipin, Shangbin Yang, A. G. Kosovichev
https://arxiv.org/abs/2508.00309

Helicity Fluxes and Hemispheric Helicity Rule of Active Regions Emerging from the Convection Zone Dynamo
Using a 3D non-linear mean-field solar dynamo model, we investigate the magnetic helicity flux and magnetic twist, and tilt parameters of bipolar magnetic regions (BMRs) emerging from the solar convection zone due to the magnetic buoyancy instability. The twist and tilt of the BMR magnetic field are modeled as a result of an effective electromotive force along the rising part of the toroidal magnetic field. This force generates the poloidal field that tilts the whole magnetic configuration. We …

Diffractive electroproduction of light vector particles: leading Fock-state contribution in the presence of significant higher Fock-state effects
Chao Shi, Liming Lu, Jian-feng Li, Wenbao Jia
https://arxiv.org/abs/2508.01874

Diffractive electroproduction of light vector particles: leading Fock-state contribution in the presence of significant higher Fock-state effects
We study exclusive diffractive production of vector mesons and photon using the color dipole model with leading Fock state light front wave functions derived from Dyson Schwinger and Bethe Salpeter equations. New results for the $ϕ$ meson and real photon are presented. Without data fitting, our calculation well matches HERA data in certain kinematical domains. The key finding of this paper is that in a color dipole model study for $ρ/γ$ and $ϕ$, where light quarks are involved, the leading …

This https://arxiv.org/abs/2411.09689 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Probing LLM Hallucination from Within: Perturbation-Driven Approach via Internal Knowledge
LLM hallucination, where unfaithful text is generated, presents a critical challenge for LLMs' practical applications. Current detection methods often resort to external knowledge, LLM fine-tuning, or supervised training with large hallucination-labeled datasets. Moreover, these approaches do not distinguish between different types of hallucinations, which is crucial for enhancing detection performance. To address such limitations, we introduce hallucination probing, a new task that classifies …

Replaced article(s) found for math.GR. https://arxiv.org/list/math.GR/new
[1/1]:
- Geometric invariants of locally compact groups: the homological perspective
Kai-Uwe Bux, Elisa Hartmann, Jos\'e Pedro Quintanilha

This https://arxiv.org/abs/2311.18804 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Holographic complexity of the Klebanov-Strassler background
We study the complexity of the gravity dual to the confining $SU(N)\times SU(N+M)$ Klebanov-Strassler gauge theory, which is an important test case for holographic complexity in higher-dimensional and nonconformal gauge/gravity dualities. We emphasize the dependence of the complexity on parameters of the gauge theory, finding a common behavior with confinement scale for several complexity functionals. We also analyze how the complexity diverges with the UV cut off, which is more complicated tha…

Ask your MP to support a ban on the import and sale of fur in the UK #AnimalRights

Ask your MP to urge the government to legislate to ban the import and sale of real fur and foie gras as soon as possible
Please write to your MP straight away ask them to support a ban on the import and sale of fur and foie gras. Thank you

Replaced article(s) found for stat.ME. https://arxiv.org/list/stat.ME/new
[1/1]:
- Conformal prediction after data-dependent model selection
Ruiting Liang, Wanrong Zhu, Rina Foygel Barber

This https://arxiv.org/abs/2506.03074 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

GL-LowPopArt: A Nearly Instance-Wise Minimax Estimator for Generalized Low-Rank Trace Regression
We present `GL-LowPopArt`, a novel Catoni-style estimator for generalized low-rank trace regression. Building on `LowPopArt` (Jang et al., 2024), it employs a two-stage approach: nuclear norm regularization followed by matrix Catoni estimation. We establish state-of-the-art estimation error bounds, surpassing existing guarantees (Fan et al., 2019; Kang et al., 2022), and reveal a novel experimental design objective, $\mathrm{GL}(π)$. The key technical challenge is controlling bias from the non…

Learning Feasible Quantum States for Quadratic Constrained Binary Optimization Problems
Anthony Wilkie, Alexander DeLise, Andrew Del Real, Rebekah Herrman, James Ostrowski
https://arxiv.org/abs/2508.02590

Learning Feasible Quantum States for Quadratic Constrained Binary Optimization Problems
Quantum computing approaches excel at solving quadratic unconstrained binary optimization (QUBO) problems, however solving quadratic constrained binary optimization problems (QCBOs) is more challenging. In this work, we develop a variational approach that creates an equal superposition of quantum states that satisfy constraints in a QCBO. The method relies on flag qubits, one per constraint, to identify when a constraint is violated or not. The resulting equal superposition can be used as an in…

This https://arxiv.org/abs/2504.13865 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

A Survey on (M)LLM-Based GUI Agents
Graphical User Interface (GUI) Agents have emerged as a transformative paradigm in human-computer interaction, evolving from rule-based automation scripts to sophisticated AI-driven systems capable of understanding and executing complex interface operations. This survey provides a comprehensive examination of the rapidly advancing field of LLM-based GUI Agents, systematically analyzing their architectural foundations, technical components, and evaluation methodologies. We identify and analyze f…

EDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment
Mikolaj Walczak, Romina Aalishah, Wyatt Mackey, Brittany Story, David L. Boothe Jr., Nicholas Waytowich, Xiaomin Lin, Tinoosh Mohsenin
https://arxiv.org/abs/2506.03046

EDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment
Deep reinforcement learning agents are often fragile while humans remain adaptive and flexible to varying scenarios. To bridge this gap, we present EDEN, a biologically inspired navigation framework that integrates learned entorhinal-like grid cell representations and reinforcement learning to enable autonomous navigation. Inspired by the mammalian entorhinal-hippocampal system, EDEN allows agents to perform path integration and vector-based navigation using visual and motion sensor data. At th…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/4]:
- Directional Sign Loss: A Topology-Preserving Loss Function that Approximates the Sign of Finite D...
Harvey Dam, Tripti Agarwal, Ganesh Gopalakrishnan

Service Time Window Design in Last-Mile Delivery
Davod Hosseini, Borzou Rostami, Mojtaba Araghi
https://arxiv.org/abs/2508.01032 https://arxiv.org/pdf/2508…

Service Time Window Design in Last-Mile Delivery
Our study focuses on designing reliable service time windows for customers in a last-mile delivery system to boost dependability and enhance customer satisfaction. To construct time windows for a pre-determined route (e.g., provided by commercial routing software), we introduce two criteria that balance window length and the risk of violation. The service provider can allocate different penalties reflecting risk tolerances to each criterion, resulting in various time windows with varying levels…

Harnessing the Power of Interleaving and Counterfactual Evaluation for Airbnb Search Ranking
Qing Zhang, Alex Deng, Michelle Du, Huiji Gao, Liwei He, Sanjeev Katariya
https://arxiv.org/abs/2508.00751

Harnessing the Power of Interleaving and Counterfactual Evaluation for Airbnb Search Ranking
Evaluation plays a crucial role in the development of ranking algorithms on search and recommender systems. It enables online platforms to create user-friendly features that drive commercial success in a steady and effective manner. The online environment is particularly conducive to applying causal inference techniques, such as randomized controlled experiments (known as A/B test), which are often more challenging to implement in fields like medicine and public policy. However, businesses face…

System-performance and cost modeling of Large Language Model training and inference
Wenzhe Guo, Joyjit Kundu, Uras Tos, Weijiang Kong, Giuliano Sisto, Timon Evenblij, Manu Perumkunnil
https://arxiv.org/abs/2507.02456

System-performance and cost modeling of Large Language Model training and inference
Large language models (LLMs), based on transformer architectures, have revolutionized numerous domains within artificial intelligence, science, and engineering due to their exceptional scalability and adaptability. However, the exponential growth in LLM size and complexity has outpaced advancements in compute capacity, memory bandwidth, network performance, and cost efficiency, posing significant challenges to their scalability on distributed systems. To address these limitations, alternative m…

This https://arxiv.org/abs/2505.17836 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
This paper addresses the problem of robust estimation in gossip algorithms over arbitrary communication graphs. Gossip algorithms are fully decentralized, relying only on local neighbor-to-neighbor communication, making them well-suited for situations where communication is constrained. A fundamental challenge in existing mean-based gossip algorithms is their vulnerability to malicious or corrupted nodes. In this paper, we show that an outlier-robust mean can be computed by globally estimating …

This https://arxiv.org/abs/2504.07879 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Towards Sustainable Creativity Support: An Exploratory Study on Prompt Based Image Generation
Creativity is a valuable human skill that has long been augmented through both analog and digital tools. Recent progress in generative AI, such as image generation, provides a disruptive technological solution to supporting human creativity further and helping humans generate solutions faster. While AI image generators can help to rapidly visualize ideas based on user prompts, the use of such AI systems has also been critiqued due to their considerable energy usage. In this paper, we report on …

Quantum chemistry with provable convergence via randomized sample-based quantum diagonalization
Samuele Piccinelli, Alberto Baiardi, Max Rossmannek, Almudena Carrera Vazquez, Francesco Tacchino, Stefano Mensa, Edoardo Altamura, Ali Alavi, Mario Motta, Javier Robledo-Moreno, William Kirby, Kunal Sharma, Antonio Mezzacapo, Ivano Tavernelli
https://

Quantum chemistry with provable convergence via randomized sample-based quantum diagonalization
Sample-based quantum diagonalization (SQD) is a recently proposed algorithm to approximate the ground-state wave function of many-body quantum systems on near-term and early-fault-tolerant quantum devices. In SQD, the quantum computer acts as a sampling engine that generates the subspace in which the Hamiltonian is classically diagonalized. A recently proposed SQD variant, Sample-based Krylov Quantum Diagonalization (SKQD), uses quantum Krylov states as circuits from which samples are collected…

OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis
Junting Chen, Haotian Liang, Lingxiao Du, Weiyun Wang, Mengkang Hu, Yao Mu, Wenhai Wang, Jifeng Dai, Ping Luo, Wenqi Shao, Lin Shao
https://arxiv.org/abs/2506.04217

OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis
The rapid progress of navigation, manipulation, and vision models has made mobile manipulators capable in many specialized tasks. However, the open-world mobile manipulation (OWMM) task remains a challenge due to the need for generalization to open-ended instructions and environments, as well as the systematic complexity to integrate high-level decision making with low-level robot control based on both global scene understanding and current agent state. To address this complexity, we propose a …

This https://arxiv.org/abs/2504.09567 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Conditional Independence Test Based on Transport Maps
Testing conditional independence between two random vectors given a third is a fundamental and challenging problem in statistics, particularly in multivariate nonparametric settings due to the complexity of conditional structures. We propose a innovative framework for testing conditional independence using transport maps. At the population level, we show that two well-defined transport maps can transform the conditional independence test into an unconditional independence test, this substantial…

This https://arxiv.org/abs/2502.20491 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Examining Algorithmic Curation on Social Media: An Empirical Audit of Reddit's r/popular Feed
Platforms are increasingly relying on algorithms to curate the content within users' social media feeds. However, the growing prominence of proprietary, algorithmically curated feeds has concealed what factors influence the presentation of content on social media feeds and how that presentation affects user behavior. This lack of transparency can be detrimental to users, from reducing users' agency over their content consumption to the propagation of misinformation and toxic content. To uncover…

Online Convex Optimization for Coordinated Long-Term and Short-Term Isolated Microgrid Dispatch
Ning Qi, Yousuf Baker, Bolun Xu
https://arxiv.org/abs/2507.02636

Online Convex Optimization for Coordinated Long-Term and Short-Term Isolated Microgrid Dispatch
This paper proposes a novel non-anticipatory long-short-term coordinated dispatch framework for isolated microgrid with hybrid short-long-duration energy storages (LDES). We introduce a convex hull approximation model for nonconvex LDES electrochemical dynamics, facilitating computational tractability and accuracy. To address temporal coupling in SoC dynamics and long-term contracts, we generate hindsight-optimal state-of-charge (SoC) trajectories of LDES and netloads for offline training. In t…

This https://arxiv.org/abs/2503.04091 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Generalization in Federated Learning: A Conditional Mutual Information Framework
Federated learning (FL) is a widely adopted privacy-preserving distributed learning framework, yet its generalization performance remains less explored compared to centralized learning. In FL, the generalization error consists of two components: the out-of-sample gap, which measures the gap between the empirical and true risk for participating clients, and the participation gap, which quantifies the risk difference between participating and non-participating clients. In this work, we apply an i…

This https://arxiv.org/abs/2404.06432 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Missing Pieces: How Do Designs that Expose Uncertainty Longitudinally Impact Trust in AI Decision Aids? An In Situ Study of Gig Drivers
Decision aids based on artificial intelligence (AI) induce a wide range of outcomes when they are deployed in uncertain environments. In this paper, we investigate how users' trust in recommendations from an AI decision aid is impacted over time by designs that expose uncertainty in predicted outcomes. Unlike previous work, we focus on gig driving - a real-world, repeated decision-making context. We report on a longitudinal mixed-methods study ($n=51$) where we measured gig drivers' trust as th…

This https://arxiv.org/abs/2409.03685 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

View-Invariant Policy Learning via Zero-Shot Novel View Synthesis
Large-scale visuomotor policy learning is a promising approach toward developing generalizable manipulation systems. Yet, policies that can be deployed on diverse embodiments, environments, and observational modalities remain elusive. In this work, we investigate how knowledge from large-scale visual data of the world may be used to address one axis of variation for generalizable manipulation: observational viewpoint. Specifically, we study single-image novel view synthesis models, which learn …

[2025-06-05 Thu (UTC), 10 new articles found for cs.HC Human-Computer Interaction]
#toXiv_bot_toot

Neural and Cognitive Impacts of AI: The Influence of Task Subjectivity on Human-LLM Collaboration
Matthew Russell, Aman Shah, Giles Blaney, Judith Amores, Mary Czerwinski, Robert J. K. Jacob
https://arxiv.org/abs/2506.04167

Neural and Cognitive Impacts of AI: The Influence of Task Subjectivity on Human-LLM Collaboration
AI-based interactive assistants are advancing human-augmenting technology, yet their effects on users' mental and physiological states remain under-explored. We address this gap by analyzing how Copilot for Microsoft Word, a LLM-based assistant, impacts users. Using tasks ranging from objective (SAT reading comprehension) to subjective (personal reflection), and with measurements including fNIRS, Empatica E4, NASA-TLX, and questionnaires, we measure Copilot's effects on users. We also evaluate …

Understanding Mental Models of Generative Conversational Search and The Effect of Interface Transparency
Chadha Degachi, Samuel Kernan Freire, Evangelos Niforatos, Gerd Kortuem
https://arxiv.org/abs/2506.03807

Understanding Mental Models of Generative Conversational Search and The Effect of Interface Transparency
The experience and adoption of conversational search is tied to the accuracy and completeness of users' mental models -- their internal frameworks for understanding and predicting system behaviour. Thus, understanding these models can reveal areas for design interventions. Transparency is one such intervention which can improve system interpretability and enable mental model alignment. While past research has explored mental models of search engines, those of generative conversational search re…

PromptCanvas: Composable Prompting Workspaces Using Dynamic Widgets for Exploration and Iteration in Creative Writing
Rifat Mehreen Amin, Oliver Hans K\"uhle, Daniel Buschek, Andreas Butz
https://arxiv.org/abs/2506.03741

PromptCanvas: Composable Prompting Workspaces Using Dynamic Widgets for Exploration and Iteration in Creative Writing
We introduce PromptCanvas, a concept that transforms prompting into a composable, widget-based experience on an infinite canvas. Users can generate, customize, and arrange interactive widgets representing various facets of their text, offering greater control over AI-generated content. PromptCanvas allows widget creation through system suggestions, user prompts, or manual input, providing a flexible environment tailored to individual needs. This enables deeper engagement with the creative proce…

Enhancing Text Comprehension for Dyslexic Readers: A 3D Semantic Visualization Approach Using Transformer Mode
Zhengyang Li
https://arxiv.org/abs/2506.03731

Enhancing Text Comprehension for Dyslexic Readers: A 3D Semantic Visualization Approach Using Transformer Mode
Dyslexic individuals often face significant challenges with traditional reading, particularly when engaging with complex texts such as mystery novels. These texts typically demand advanced narrative tracking and information integration skills, making it difficult for dyslexic readers to fully comprehend the content. However, research indicates that while dyslexic individuals may struggle with textual processing, they often possess strong spatial imagination abilities. Leveraging this strength, …

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

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

Understanding Visually Impaired Tramway Passengers Interaction with Public Transport Systems
Dominik Mimra, Dominik Kaar, Enrico Del Re, Novel Certad, Joshua Cherian Varughese, David Seibt, Cristina Olaverri-Monreal
https://arxiv.org/abs/2506.03687

Understanding Visually Impaired Tramway Passengers Interaction with Public Transport Systems
Designing inclusive public transport services is crucial to developing modern, barrier-free smart city infrastructure. This research contributes to the design of inclusive public transport by considering accessibility challenges emerging from socio-technical systems, thus demanding the integration of technological and social solutions. Using Actor-Network Theory (ANT) as a theoretical framework and a mixed-method approach, including shadowing and a focus group, this study examines the socio-tec…

VChatter: Exploring Generative Conversational Agents for Simulating Exposure Therapy to Reduce Social Anxiety
Han Zhang, KaWing Tsang, Zhenhui Peng
https://arxiv.org/abs/2506.03520

VChatter: Exploring Generative Conversational Agents for Simulating Exposure Therapy to Reduce Social Anxiety
Many people struggle with social anxiety, feeling fear, or even physically uncomfortable in social situations like talking to strangers. Exposure therapy, a clinical method that gradually and repeatedly exposes individuals to the source of their fear and helps them build coping mechanisms, can reduce social anxiety but traditionally requires human therapists' guidance and constructions of situations. In this paper, we developed a multi-agent system VChatter to explore large language models(LLMs…

The Stress of Improvisation: Instructors' Perspectives on Live Coding in Programming Classes
Xiaotian Su, April Wang
https://arxiv.org/abs/2506.03402 h…

The Stress of Improvisation: Instructors' Perspectives on Live Coding in Programming Classes
Live coding is a pedagogical technique in which an instructor writes and executes code in front of students to impart skills like incremental development and debugging. Although live coding offers many benefits, instructors face many challenges in the classroom, like cognitive challenges and psychological stress, most of which have yet to be formally studied. To understand the obstacles faced by instructors in CS classes, we conducted (1) a formative interview with five teaching assistants in e…

Sampling Preferences Yields Simple Trustworthiness Scores
Sean Steinle
https://arxiv.org/abs/2506.03399 https://arxiv.org/pdf/2506.03…

Sampling Preferences Yields Simple Trustworthiness Scores
With the onset of large language models (LLMs), the performance of artificial intelligence (AI) models is becoming increasingly multi-dimensional. Accordingly, there have been several large, multi-dimensional evaluation frameworks put forward to evaluate LLMs. Though these frameworks are much more realistic than previous attempts which only used a single score like accuracy, multi-dimensional evaluations can complicate decision-making since there is no obvious way to select an optimal model. Th…

From Reality to Recognition: Evaluating Visualization Analogies for Novice Chart Comprehension
Oliver Huang, Patrick Lee, Carolina Nobre
https://arxiv.org/abs/2506.03385

From Reality to Recognition: Evaluating Visualization Analogies for Novice Chart Comprehension
Novice learners often have difficulty learning new visualization types because they tend to interpret novel visualizations through the mental models of simpler charts they have previously encountered. Traditional visualization teaching methods, which usually rely on directly translating conceptual aspects of data into concrete data visualizations, often fail to attend to the needs of novice learners navigating this tension. To address this, we conducted an empirical exploration of how analogies…

A Theory-driven and AI-enhanced Simulation Platform for Cultivating Nutrition Literacy
Shan Li, Guozhu Ding
https://arxiv.org/abs/2507.02138 https://

A Theory-driven and AI-enhanced Simulation Platform for Cultivating Nutrition Literacy
This study introduces and evaluates Healthy Choice, an innovative theory-driven and AI-enhanced simulation platform designed to cultivate nutrition literacy through interactive scenario-based learning experiences. We collected feedback from 114 university students with diverse backgrounds who completed simulated product selection scenarios. Quantitative ratings of usefulness and ease of use demonstrated high user satisfaction.