December 2024 arXiv papers — page 55

Junyi Ye, Ankan Dash, Wenpeng Yin, Guiling Wang

Flowcharts are typically presented as images, driving the trend of using vision-language models (VLMs) for end-to-end flowchart understanding. However, two key challenges arise: (i) Limited controllability--users have minimal influence over the downstream task, as they can only modify input images, while the training of VLMs is often out of reach for most re

Laura Battaglia, Chris U. Carmona, Ross A. Haines, Max Anderson Loake

In Bayesian inference prior hyperparameters are chosen subjectively or estimated using empirical Bayes methods. Generalised Bayesian Inference (GBI) also has a learning rate hyperparameter. This is compounded in Semi-Modular Inference (SMI), a GBI framework for multiple datasets (multi-modular problems). As part of any GBI workflow it is necessary to check s

Huan Liu, Lingyu Xiao, Jiangjiang Liu, Xiaofan Li

With the rapid advancement of Multimodal Large Language Models (MLLMs), a variety of benchmarks have been introduced to evaluate their capabilities. While most evaluations have focused on complex tasks such as scientific comprehension and visual reasoning, little attention has been given to assessing their fundamental image classification abilities. In this

Manuel Sandoval, Mohammed Abuhamad, Patrick Furman, Mujtaba Nazari

Social media has revolutionized communication, allowing people worldwide to connect and interact instantly. However, it has also led to increases in cyberbullying, which poses a significant threat to children and adolescents globally, affecting their mental health and well-being. It is critical to accurately detect the roles of individuals involved in cyberb

Tianyi Bai, Xinxin Chen, Yuval Peres

In this paper, we prove that hitting probability of Minkowski sum of fractal percolations can be characterized by capacity. Then we extend this result to Minkowski sum of general random sets in $\mathbb Z^d$, including ranges of random walks and critical branching random walks, whose hitting probabilities are described by Newtonian capacity individually.

Dmitry Bylinkin, Aleksandr Beznosikov

In recent years, as data and problem sizes have increased, distributed learning has become an essential tool for training high-performance models. However, the communication bottleneck, especially for high-dimensional data, is a challenge. Several techniques have been developed to overcome this problem. These include communication compression and implementat

Niklas Sapountzoglou, Yassine Tahraoui, Guy Vallet, Aleksandra Zimmermann

We study a nonlinear, pseudomonotone, stochastic diffusion-convection evolution problem on a bounded spatial domain, in any space dimension, with homogeneous boundary conditions and reflection. The additive noise term is given by a stochastic It\^{o} integral with respect to a Hilbert space valued $Q$-Wiener process. We show existence of a solution to the ps

Sai Surya Gadiraju, Duoduo Liao, Akhila Kudupudi, Santosh Kasula

This pilot study presents the development of the InfoTech Assistant, a domain-specific, multimodal chatbot engineered to address queries in bridge evaluation and infrastructure technology. By integrating web data scraping, large language models (LLMs), and Retrieval-Augmented Generation (RAG), the InfoTech Assistant provides accurate and contextually relevan

Yang He, Vassiliy Lubchenko

We construct a thermodynamic potential that can guide training of a generative model defined on a set of binary degrees of freedom. We argue that upon reduction in description, so as to make the generative model computationally-manageable, the potential develops multiple minima. This is mirrored by the emergence of multiple minima in the free energy proper o

Md Robiul Islam

In this era of technological advancements, several cutting-edge techniques are being implemented to enhance Autonomous Driving (AD) systems, focusing on improving safety, efficiency, and adaptability in complex driving environments. However, AD still faces some problems including performance limitations. To address this problem, we conducted an in-depth stud

Amanda S. Rios, Ibrahima J. Ndiour, Parual Datta, Jaroslaw Sydir

AI deployed in the real-world should be capable of autonomously adapting to novelties encountered after deployment. Yet, in the field of continual learning, the reliance on novelty and labeling oracles is commonplace albeit unrealistic. This paper addresses a challenging and under-explored problem: a deployed AI agent that continuously encounters unlabeled d

Jingyi Liu, Yi Man, Eva Kanso

Sessile ciliates attach to substrates and generate feeding currents to capture passing particulates and dissolved nutrients. Optimal ciliary activity that maximizes nutrient flux at the cell surface while minimizing the rate of hydrodynamic energy dissipation is well characterized in uniform nutrient fields. However, it is unclear how ciliary motion should c

Anamitra Saha, Sai Ravela

As climate change drives an increase in global extremes, it is critical for Bangladesh, a nation highly vulnerable to these impacts, to assess future risks for effective adaptation and mitigation planning. Downscaling coarse-resolution climate models to finer scales is essential for accurately evaluating the risk of extremes. In this study, we apply our down

Prabal Adhikari, Martin Ammon, Sidney S. Avancini, Alejandro Ayala

Magnetic fields are ubiquitous across different physical systems of current interest; from the early Universe, compact astrophysical objects and heavy-ion collisions to condensed matter systems. A proper treatment of the effects produced by magnetic fields during the dynamical evolution of these systems, can help to understand observables that otherwise show

Andreas Eberle, Francis Lörler

Non-reversible lifts reduce the relaxation time of reversible diffusions at most by a square root. For reversible diffusions on domains in Euclidean space, or, more generally, on a Riemannian manifold with boundary, non-reversible lifts are in particular given by the Hamiltonian flow on the tangent bundle, interspersed with random velocity refreshments, or p

Antonio J. Martínez Aparicio, Francescantonio Oliva, Francesco Petitta

In this paper we extend the classical sub-supersolution Sattinger iteration method to $1$-Laplace type boundary value problems of the form \begin{equation*} \begin{cases} \displaystyle -Δ_1 u = F(x,u) & \text{in}\;Ω,\\ \newline u=0 & \text{on}\;\partialΩ, \end{cases} \end{equation*} where $Ω$ is an open bounded domain of $\mathbb{R}^N$ ($N\geq 2$) with Lipsc

Hiroto Takahashi, Chun-Chih Hsu, Fabian Jerzembeck, Jack Murphy

An emerging concept for identification of different types of spin liquids is through the use of spontaneous spin noise. Here we develop spin noise spectroscopy for spin liquid studies by considering Ca$_{10}$Cr$_7$O$_{28}$, a material hypothesized to be either a quantum or a spiral spin liquid. By enhancing techniques introduced for magnetic monopole noise s

Erica Chiang, Divya Shanmugam, Ashley N. Beecy, Gabriel Sayer

Disease progression models are widely used to inform the diagnosis and treatment of many progressive diseases. However, a significant limitation of existing models is that they do not account for health disparities that can bias the observed data. To address this, we develop an interpretable Bayesian disease progression model that captures three key health d

Benjamin X. Shi, Flaviano Della Pia, Yasmine S. Al-Hamdani, Angelos Michaelides

The accurate treatment of non-covalent interactions is necessary to model a wide range of applications, from molecular crystals to surface catalysts to aqueous solutions and many more. Quantum diffusion Monte Carlo (DMC) and coupled cluster theory with single, double and perturbative triple excitations [CCSD(T)] are considered two widely-trusted methods for

Massimiliano Gubinelli, Martin Hairer, Tadahiro Oh, Younes Zine

We present a simple PDE construction of the sine-Gordon measure below the first threshold ($\be^2 < 4\pi$), in both the finite and infinite volume settings, by studying the corresponding parabolic sine-Gordon model. We also establish pathwise global well-posedness of the hyperbolic sine-Gordon model in finite volume for $\be^2 < 2\pi$.

Lucas K. Johnson, Grant M Domke, Stephen V Stehman, Michael J Mahoney

Fine-resolution maps of forest aboveground biomass (AGB) effectively represent spatial patterns and can be flexibly aggregated to map subregions by computing spatial averages or totals of pixel-level predictions. However, generalized model-based uncertainty estimation for spatial aggregates requires computationally expensive processes like iterative bootstra

Zach Branson, Monica Paz Parra, Ronald Yurko

Data visualization is a core part of statistical practice and is ubiquitous in many fields. Although there are numerous books on data visualization, instructors in statistics and data science may be unsure how to teach data visualization, because it is such a broad discipline. To give guidance on teaching data visualization from a statistical perspective, we

Reinhard M. Grassmann, Jessica Burgner-Kahrs

In this paper, we consider an arbitrary number of joints and their arbitrary joint locations along the center line of a displacement-actuated continuum robot. To achieve this, we revisit the derivation of the Clarke transform leading to a formulation capable of considering arbitrary joint locations. The proposed modified Clarke transform opens new opportunit

Chun-Chi Lin

The aim of this article is to present a concise proof for the interior H\"{o}lder continuity of two-dimensional stationary Q-valued maps. The proof employs a blow-up argument based on the monotonicity formula for the frequency function, along with the oscillation estimate from the author's previous article, which leverages the conformality of the modified ma

Peyman Soltani, Milan ten Hacken, Arie van der Meijden, Frans Snik

Understanding and classifying chiral structural color of scarab beetles across the phylogenetic tree is an important scientific tool to explore the origins of the homochiral optical response in biological structures with a potential relation to the homochirality of (chitin) molecules. We report hyperspectral polarization resolved images of the scarab beetle

Sam Russell

This paper describes a novel method for efficiently calculating CRC checksums without lookup tables or hardware support for polynomial multiplication. Throughput of CRC32 is increased by 100% across different platforms compared with the current state of the art. Performance is on par with or exceeds hardware-accelerated solutions on x86_64 and ARMv8 processo

Lucía Pedraza, Nicolas Saintier, Juan Pablo Pinasco, Pablo Balenzuela

In recent years, numerous mathematical models of opinion formation have been developed, incorporating diverse interaction mechanisms such as imitation and majority rule. However, limited attention has been given to models grounded in persuasive arguments theory (PAT), which describes how individuals may alter their opinions through the exchange of arguments

Karim Cherifi, Hannes Gernandt, Dorothea Hinsen, Volker Mehrmann

The relationship between different dissipativity concepts for linear time-varying systems is studied, in particular between port-Hamiltonian systems, passive systems, and systems with nonnegative supply. It is shown that linear time-varying port-Hamiltonian systems are passive, have nonnegative supply rates, and solve (under different smoothness assumptions)

Rashmeet Kaur Nayyar, Siddharth Srivastava

Abstraction is key to scaling up reinforcement learning (RL). However, autonomously learning abstract state and action representations to enable transfer and generalization remains a challenging open problem. This paper presents a novel approach for inventing, representing, and utilizing options, which represent temporally extended behaviors, in continual RL

Zahiriddin Rustamov, Abderrahmane Lakas, Nazar Zaki

Class imbalance poses a significant challenge in machine learning (ML), often leading to biased models favouring the majority class. In this paper, we propose GAT-RWOS, a novel graph-based oversampling method that combines the strengths of Graph Attention Networks (GATs) and random walk-based oversampling. GAT-RWOS leverages the attention mechanism of GATs t

Courtney L. Crawford, Jamie Soon, Geoffrey C. Clayton, Patrick Tisserand

The R Coronae Borealis (RCB) variables are rare, hydrogen-deficient, carbon-rich supergiants known for large, erratic declines in brightness due to dust formation. Recently, the number of known RCB stars in the Milky Way and Magellanic Clouds has increased from $\sim$30 to 162. We use all-sky and targeted photometric surveys to create the longest possible li

Christian Gerbig, Silvio Morgenstern, Ahmed S. Hassanien, Marlene Adrian

Coherent optical phonons in the degenerate inter-layer shear mode of graphite launched by femtosecond laser pulses were investigated using ultrafast electron diffraction. The collective atomic motion is shown to be polarized in a direction related to the linear polarization of the incoming laser pulse. Using a fit with a generic driven-oscillator model, the

Einar Bjarki Gunnarsson, Benedikt Vilji Magnússon, Jasmine Foo

While cancer has traditionally been considered a genetic disease, mounting evidence indicates an important role for non-genetic (epigenetic) mechanisms. Common anti-cancer drugs have recently been observed to induce the adoption of non-genetic drug-tolerant cell states, thereby accelerating the evolution of drug resistance. This confounds conventional high-d

Ashley Melvin, J. C. Mandal

In this paper, a novel fully-explicit weakly compressible solver is developed for solving incompressible two-phase flows. The two-phase flow is modelled by coupling the general pressure equation, momentum conservation equations and the conservative level set advection equation. A HLLC-type Riemann solver is proposed to evaluate the convective fluxes along wi

Atahan Karagoz

Generative AI models like GPT-4o and DALL-E 3 are reshaping digital content creation, offering industries tools to generate diverse and sophisticated text and images with remarkable creativity and efficiency. This paper examines both the capabilities and challenges of these models within creative workflows. While they deliver high performance in generating c

Santiago Cabrera, Gonzalo De Polsi, Nicolás Wschebor

The behavior of many critical phenomena at large distances is expected to be invariant under the full conformal group, rather than only isometries and scale transformations. When studying critical phenomena, approximations are often required, and the framework of the nonperturbative, or functional renormalization group is no exception. The derivative expansi

Yifeng Fan, Zhizhen Zhao

The emerging problem of joint community detection and group synchronization, with applications in signal processing and machine learning, has been extensively studied in recent years. Previous research has predominantly focused on a statistical model that extends the stochastic block model~(SBM) by incorporating additional group transformations. In its simpl

John C. Baez

If we treat the symmetric group $S_n$ as a probability measure space where each element has measure $1/n!$, then the number of cycles in a permutation becomes a random variable. The Cycle Length Lemma describes the expected values of products of these random variables. Here we categorify the Cycle Length Lemma by showing that it follows from an equivalence b

Mohsen Sadr, Hossein Gorji

Inspired by the Boltzmann kinetics, we propose a collision-based dynamics with a Monte Carlo solution algorithm that approximates the solution of the multi-marginal optimal transport problem via randomized pairwise swapping of sample indices. The computational complexity and memory usage of the proposed method scale linearly with the number of samples, makin

Paul Duetting, Michal Feldman, Inbal Talgam-Cohen

A contract is an economic tool used by a principal to incentivize one or more agents to exert effort on her behalf, by defining payments based on observable performance measures. A key challenge addressed by contracts -- known in economics as moral hazard -- is that, absent a properly set up contract, agents might engage in actions that are not in the princi

Francesco Di Cursi, Chiara Boldrini, Andrea Passarella, Marco Conti

The tremendous success of major Online Social Networks (OSNs) platforms has raised increasing concerns about negative phenomena, such as mass control, fake news, and echo chambers. In addition, the increasingly strict control over users' data by platform owners questions their trustworthiness as open interaction tools. These trends and, notably, the recent d

Amin Bigdeli, Negar Arabzadeh, Ebrahim Bagheri, Charles L. A. Clarke

Recent research has shown that neural information retrieval techniques may be susceptible to adversarial attacks. Adversarial attacks seek to manipulate the ranking of documents, with the intention of exposing users to targeted content. In this paper, we introduce the Embedding Perturbation Rank Attack (EMPRA) method, a novel approach designed to perform adv

Bangwei Guo, Meng Ye, Yunhe Gao, Bingyu Xin

Despite the advances in learning-based image segmentation approach, the accurate segmentation of cardiac structures from magnetic resonance imaging (MRI) remains a critical challenge. While existing automatic segmentation methods have shown promise, they still require extensive manual corrections of the segmentation results by human experts, particularly in

Huawei Sun, Nastassia Vysotskaya, Tobias Sukianto, Hao Feng

Recently, radar-camera fusion algorithms have gained significant attention as radar sensors provide geometric information that complements the limitations of cameras. However, most existing radar-camera depth estimation algorithms focus solely on improving performance, often neglecting computational efficiency. To address this gap, we propose LiRCDepth, a li

Sergey Kryzhevich, Yiwei Zhang, Magdalena Chmara

We study the dynamics of a family of replicator maps, depending on two parameters. Such studies are motivated by the analysis of the dynamics of evolutionary games under selections. From the dynamics viewpoint, we prove the existence of hyperbolic chaos for the considered map. Moreover, we also give a partial solution of an open problem formulated in \cite{M

Alessandro Massaad

In this thesis we explore S. Klainerman's proof on the global existence of small amplitude solutions to nonlinear Klein-Gordon equations in four space-time dimensions, as established in his paper from 1985. We consider initial data with small amplitude and compact support and aim prove the global existence and uniform decay of smooth solutions. We establish

Taneesh Gupta, Rahul Madhavan, Xuchao Zhang, Chetan Bansal

To mitigate reward hacking from response verbosity, modern preference optimization methods are increasingly adopting length normalization (e.g., SimPO, ORPO, LN-DPO). While effective against this bias, we demonstrate that length normalization itself introduces a failure mode: the URSLA shortcut. Here models learn to satisfy the alignment objective by prematu

Alexander Kiselev, Naji A. Sarsam

We derive a PDE that models the behavior of a boundary layer solution to the incompressible porous media (IPM) equation posed on the 2D periodic half-plane. This 1D IPM model is a transport equation with a non-local velocity similar to the well-known C\'{o}rdoba-C\'{o}rdoba-Fontelos (CCF) equation. We discuss how this modification of the CCF equation can be

Kevin Lee

NOAA's Deep-ocean Assessment and Reporting of Tsunamis (DART) data are critical for NASA-JPL's tsunami detection, real-time operations, and oceanographic research. However, these time-series data often contain spikes, steps, and drifts that degrade data quality and obscure essential oceanographic features. To address these anomalies, the work introduces an I

Martin R. Evans, John C. Sunil

Stochastic resetting has been a subject of considerable interest within statistical physics, both as means of improving completion times of complex processes such as searches and as a paradigm for generating nonequilibrium stationary states. In these lecture notes we give a self-contained introduction to the toy model of diffusion with stochastic resetting.

Yicheng Gao, Jinkui Hao, Bo Zhou

Recent advancements in deep learning have shown transformative potential in medical imaging, yet concerns about fairness persist due to performance disparities across demographic subgroups. Existing methods aim to address these biases by mitigating sensitive attributes in image data; however, these attributes often carry clinically relevant information, and

Malachy Bloom, Alexander Criswell, Vuk Mandic

The Laser Interferometer Space Antenna (LISA), a spaceborne gravitational wave (GW) detector set to launch in 2035, will observe several stochastic GW backgrounds in the mHz frequency band. At least one of these signals -- arising from the tens of millions of unresolved white dwarf binaries in the Milky Way -- is expected to be highly anisotropic on the sky.

Jungchul Noh, Clément Livache, Donghyo Hahm, Valerio Pinchetti

Incorporation of manganese impurities into II-VI semiconductors results in a dramatic change in their properties due to strong exchange interactions between the Mn ion and the semiconductor host. In colloidal quantum dots (QDs), these interactions result in a rapid bidirectional energy transfer between the magnetic impurity and the QD intrinsic states, which

Robert Clausecker, Daniel Lemire, Florian Schintke

The positional population count operation pospopcnt() counts for an array of w-bit words how often each of the w bits was set. Various applications in bioinformatics, database engineering, and digital processing exist. Building on earlier work by Klarqvist et al., we show how positional population counts can be rapidly computed using SIMD techniques with goo

Ajay Kumar Shrestha, Ankur Barthwal, Molly Campbell, Austin Shouli

This systematic literature review investigates perceptions, concerns, and expectations of young digital citizens regarding privacy in artificial intelligence (AI) systems, focusing on social media platforms, educational technology, gaming systems, and recommendation algorithms. Using a rigorous methodology, the review started with 2,000 papers, narrowed down

Sergi Elizalde, Nadia Lafrenière, Joel Brewster Lewis, Erin McNicholas

We find a generating function for interval-closed sets of the product of two chains poset by constructing a bijection to certain bicolored Motzkin paths. We also find a functional equation for the generating function of interval-closed sets of truncated rectangle posets, including the type $A$ root poset, by constructing a bijection to certain quarter-plane

Saakaar Bhatnagar, Andrew Comerford, Zelu Xu, Simone Reitano

Thermal runaway in lithium-ion batteries is a critical safety concern for the battery industry due to its potential to cause uncontrolled temperature rises and subsequent fires that can engulf the battery pack and its surroundings. Modeling and simulation offer cost-effective tools for designing strategies to mitigate thermal runaway. Accurately simulating t

Hansi Hettiarachchi, Tharindu Ranasinghe, Paul Rayson, Ruslan Mitkov

The first Workshop on Language Models for Low-Resource Languages (LoResLM 2025) was held in conjunction with the 31st International Conference on Computational Linguistics (COLING 2025) in Abu Dhabi, United Arab Emirates. This workshop mainly aimed to provide a forum for researchers to share and discuss their ongoing work on language models (LMs) focusing on

Shijie Zhou, Ruiyi Zhang, Yufan Zhou, Changyou Chen

Large multimodal models still struggle with text-rich images because of inadequate training data. Self-Instruct provides an annotation-free way for generating instruction data, but its quality is poor, as multimodal alignment remains a hurdle even for the largest models. In this work, we propose LLaVAR-2, to enhance multimodal alignment for text-rich images

Fabian B. Kugler, Jeremy Lee-Hand, Harrison LaBollita, Lorenzo Van Muñoz

Direct-current resistivity is a key probe for the physical properties of materials. In metals, Fermi-liquid (FL) theory serves as the basis for understanding transport. A $T^2$ behavior of the resistivity is often taken as a signature of FL electron-electron scattering. However, the presence of impurity and phonon scattering as well as material-specific aspe

Jacek Okolowicz, Marek Ploszajczak

Recently, $B(E2, 0^+_1 \to 2^+_1)$ transition strength have been measured in $^{36}$Ca and $^{38}$Ca. Surprisingly, the measured value in $^{36}$Ca: $B(E2\ \uparrow) = 131(20)$ e$^2$fm$^4$, is significantly larger than in $^{38}$Ca, where $B(E2\ \uparrow) = 101(11)$ e$^2$fm$^4$, whereas an opposite tendency of $B(E2)$ values is seen in the mirror nuclei $^{3

Amine Ouasfi, Shubhendu Jena, Eric Marchand, Adnane Boukhayma

We consider the challenging problem of learning Signed Distance Functions (SDF) from sparse and noisy 3D point clouds. In contrast to recent methods that depend on smoothness priors, our method, rooted in a distributionally robust optimization (DRO) framework, incorporates a regularization term that leverages samples from the uncertainty regions of the model

Yiming Pang, Joshua E. Castro, Trevor J. Steiner, Liao Duan

Integrated photonic microresonators have become an essential resource for generating photonic qubits for quantum information processing, entanglement distribution and networking, and quantum communications. The pair generation rate is enhanced by reducing the microresonator radius, but this comes at the cost of increasing the frequency mode spacing and reduc

Nilanjana Das, Edward Raff, Aman Chadha, Manas Gaur

As the AI systems become deeply embedded in social media platforms, we've uncovered a concerning security vulnerability that goes beyond traditional adversarial attacks. It becomes important to assess the risks of LLMs before the general public use them on social media platforms to avoid any adverse impacts. Unlike obvious nonsensical text strings that safet

Mikael Yeghiazaryan, Sai Abhishek Siddhartha Namburu, Emily Kim, Stanislav Panev

Detecting vehicles in aerial images is difficult due to complex backgrounds, small object sizes, shadows, and occlusions. Although recent deep learning advancements have improved object detection, these models remain susceptible to adversarial attacks (AAs), challenging their reliability. Traditional AA strategies often ignore practical implementation constr

Kento Kaneko, Claude Le Bris, Anthony T. Patera

We consider the dunking problem: a solid body at uniform temperature $T_\text{i}$ is placed in a environment characterized by farfield temperature $T_\infty$ and time-independent spatially uniform heat transfer coefficient; we permit heterogeneous material composition. The problem is described by a heat equation with Robin boundary conditions. The crucial pa

Han Lou

In [FOOO12], K. Fukaya, Y. Oh, H. Ohta, and K. Ono (FOOO) obtained the monotone symplectic manifold $S^2\times S^2$ by resolving the singularity of a toric degeneration of a Hirzebruch surface. They identified a continuum of toric fibers in the resolved toric degeneration that are not Hamiltonian isotopic to the toric fibers of the standard toric structure o

Adam Davies, Elisa Nguyen, Michael Simeone, Erik Johnston

With the rise of foundation models, there is growing concern about their potential social impacts. Social science has a long history of studying the social impacts of transformative technologies in terms of pre-existing systems of power and how these systems are disrupted or reinforced by new technologies. In this position paper, we build on prior work study

I. Zakir Ahmed, Hamid Sadjadpour

In traditional Reconfigurable Intelligent Surfaces (RIS) systems, the RIS is mounted on stationary structures like buildings, walls, or posts. They have shown promising results in enhancing the performance of wireless systems like capacity and MSE in poor channel conditions. The traditional RIS is a monolithic structure containing a large number of reflectin

Yekaterina Epshteyn, Akil Narayan, Yinqian Yu

Shallow water equations (SWE) are fundamental nonlinear hyperbolic PDE-based models in fluid dynamics that are essential for studying a wide range of geophysical and engineering phenomena. Therefore, stable and accurate numerical methods for SWE are needed. Although some algorithms are well studied for deterministic SWE, more effort should be devoted to hand

Rachel Bailey

The aim of this review paper is to discuss some applications of orthogonal polynomials in quantum information processing. The hope is to keep the paper self contained so that someone wanting a brief introduction to the theory of orthogonal polynomials and continuous time quantum walks on graphs may find it in one place. In particular, we focus on the associa

Sophie Frisch, Franz Halter-Koch

Let F:K be a Galois extension of number fields and Q a prime ideal of O_F lying over the prime P of O_K. By analyzing the Q-adic closure of O_K in O_F we characterize those rings of integers O_K for which every residue class ring of Int(O_K) modulo a non-zero prime ideal is GE2 (meaning that every unimodular pair can be trasformed to (1,0) by a series of ele

Jade Sheffey, Amir Houmansadr

Censorship and censorship circumvention are closely connected, and each is constantly making decisions in reaction to the other. When censors deploy a new Internet censorship technique, the anti-censorship community scrambles to find and develop circumvention strategies against the censor's new strategy, i.e., by targeting and exploiting specific vulnerabili

Lucas Soster Moriggi, Magno Valério Trindade Machado

In this work, we confront the geometrical scaling properties of inclusive DIS cross section ($e+p\rightarrow e +X$) with the scaling entropy obtained from event multiplicity. We show that these two quantities are equivalent in the kinematic range probed by H1 Collaboration data. We propose that scaling entropy associated with partonic interactions is a more

Riccardo Morandin, Dorothea Hinsen

The concept of dissipativity plays a crucial role in the analysis of control systems. Dissipative energy functionals, also known as Hamiltonians, storage functions, or Lyapunov functions, depending on the setting, are extremely valuable to analyze and control the behavior of dynamical systems, but in general circumstances they are very difficult to compute,

JunEn Low, Maximilian Adang, Javier Yu, Keiko Nagami

We propose a new simulator, training approach, and policy architecture, collectively called SOUS VIDE, for end-to-end visual drone navigation. Our trained policies exhibit zero-shot sim-to-real transfer with robust real-world performance using only onboard perception and computation. Our simulator, called FiGS, couples a computationally simple drone dynamics

Akram Entezami, Ghosheh Abed Hodtani

From both practical and theoretical viewpoints, performance analysis of communication systems using information-theoretic results is very important. In this study, first, we obtain a general achievable rate for a two-user wireless multiple access channel (MAC) with specially correlated sources as a more general version for continuous alphabet MACs, by extend

Catherine E. Grant, Marshall W. Bautz, Eric D. Miller, Richard F. Foster

The Arcus Probe mission concept provides high-resolution soft X-ray and UV spectroscopy to reveal feedback-driven structure and evolution throughout the universe with an agile response capability ideal for probing the physics of time-dependent phenomena. The X-ray Spectrograph (XRS) utilizes two nearly identical CCD focal planes to detect and record X-ray ph

Hugo Depuydt, Merve Gülmez, Thomas Nyman, Jan Tobias Mühlberg

Stack canaries and shadow stacks are widely deployed mitigations to memory-safety vulnerabilities. While stack canaries are introduced by the compiler and rely on sentry values placed between variables and control data, shadow stack implementations protect return addresses explicitly and rely on hardware features available in modern processor designs for eff

Pedro Frejlich, David Martínez Torres

We discuss in this note two dual canonical operations on Dirac structures $L$ and $R$ -- the \emph{tangent product} $L \star R$ and the \emph{cotangent product} $L \circledast R$. Our first result gives an explicit description of the leaves of $L \star R$ in terms of those of $L$ and $R$, surprisingly ruling out the pathologies which plague general ``induced

Ferit Akaybicen, Aaron Cummings, Lota Iwuagwu, Xinyue Zhang

The rapid identification of medical emergencies through digital communication channels remains a critical challenge in modern healthcare delivery, particularly with the increasing prevalence of telemedicine. This paper presents a novel approach leveraging large language models (LLMs) and prompt engineering techniques for automated emergency detection in medi

John R. Harper, Lee Kennard

In 1960, J.F. Adams introduced secondary cohomology operations that are defined on cohomology elements on which sufficiently many Steenrod algebra elements vanish. This led to his theorem on singly generated cohomology rings, which in turn led to his celebrated resolution of the Hopf invariant one problem. Here we advertise a conjecture that would extend Ada

Melody Y. Guan, Manas Joglekar, Eric Wallace, Saachi Jain

As large-scale language models increasingly impact safety-critical domains, ensuring their reliable adherence to well-defined principles remains a fundamental challenge. We introduce Deliberative Alignment, a new paradigm that directly teaches the model safety specifications and trains it to explicitly recall and accurately reason over the specifications bef

Gastão A. Braga, Jussara M. Moreira, Antônio Marcos da Silva, Camila F. Souza

In this paper we employ the Renormalization Group (RG) method to study higher order corrections to the long-time asymptotics of a class of nonlinear integral equations with a generalized heat kernel and with time-dependent coefficients. This is a follow up of the papers \cite{bib:souz-brag-more-art,bib:souz-brag-more-marginal,bib:brag-more-silv}.

Naveed A. Abbasi, Tathagat Pal, Kelvin Arana, Vikram Vasudevan

Growing demand for high data rates is driving interest in the upper mid-band (FR 3) spectrum (6-24 GHz). While some propagation measurements exist in literature, the impact of vegetation on link performance remains under-explored. This study examines vegetation-induced losses in an urban scenario across 6-18 GHz. A simple method for calculating vegetation de

Israel F. Araujo, Hyeondo Oh, Nayeli A. Rodríguez-Briones, Daniel K. Park

This work introduces the Schmidt quantum compressor, an innovative approach to quantum data compression that leverages the principles of Schmidt decomposition to encode quantum information efficiently. In contrast to traditional variational quantum autoencoders, which depend on stochastic optimization and face challenges such as shot noise, barren plateaus,

Gunel Jahangirova, Nargiz Humbatova, Jinhan Kim, Shin Yoo

As the adoption of Deep Learning (DL) systems continues to rise, an increasing number of approaches are being proposed to test these systems, localise faults within them, and repair those faults. The best attestation of effectiveness for such techniques is an evaluation that showcases their capability to detect, localise and fix real faults. To facilitate th

Daniel Smolyak, Arshana Welivita, Margrét V. Bjarnadóttir, Ritu Agarwal

Objective. Demographic groups are often represented at different rates in medical datasets. These differences can create bias in machine learning algorithms, with higher levels of performance for better-represented groups. One promising solution to this problem is to generate synthetic data to mitigate potential adverse effects of non-representative data set

Cijo Jose, Théo Moutakanni, Dahyun Kang, Federico Baldassarre

Self-supervised visual foundation models produce powerful embeddings that achieve remarkable performance on a wide range of downstream tasks. However, unlike vision-language models such as CLIP, self-supervised visual features are not readily aligned with language, hindering their adoption in open-vocabulary tasks. Our method, named dino.txt, unlocks this ne

Sahar Yarmohammadtoosky Dinesh Chowdary Attota

As several studies have shown, predicting credit risk is still a major concern for the financial services industry and is receiving a lot of scholarly interest. This area of study is crucial because it aids financial organizations in determining the probability that borrowers would default, which has a direct bearing on lending choices and risk management ta

Urs Frauenfelder, Joa Weber

In this article we consider operators of the form $\partial_s\xi+A(s)\xi$ where $s$ lies in an interval $[-T,T]$ and $s\mapsto A(s)$ is continuous. Without boundary conditions these operators are not Fredholm. However, using interpolation theory one can define suitable boundary conditions for these operators so that they become Fredholm. We show that in this

Anas Mifrani

The concept of efficiency plays a prominent role in the formal solution of decision problems that involve incomparable alternatives. This paper develops necessary and sufficient conditions for the efficient points in a sum of sets of alternatives to be identical to the efficient points in one of the summands. Some of the conditions cover both finite and infi

Francisco Arana-Herrera, Alex Wright

We prove a semisimplicity result for the boundary, in the corresponding Deligne-Mumford compactification, of a totally geodesic subvariety of a moduli space of Riemann surfaces. At the level of Teichm\"uller space, this semisimplicity theorem gives that each component of the boundary is a product of simple factors, each of which behaves metrically like a dia

Marcus Jenkins, Kirsty A. Franklin, Malcolm A. C. Nicoll, Nik C. Cole

Monitoring animal populations is crucial for assessing the health of ecosystems. Traditional methods, which require extensive fieldwork, are increasingly being supplemented by time-lapse camera-trap imagery combined with an automatic analysis of the image data. The latter usually involves some object detector aimed at detecting relevant targets (commonly ani

Pete Austin, Nicolas Mazzocchi, Sougata Bose, Patrick Totzke

Temporal graphs extend ordinary graphs with discrete time that affects the availability of edges. We consider solving games played on temporal graphs where one player aims to explore the graph, i.e., visit all vertices. The complexity depends majorly on two factors: the presence of an adversary and how edge availability is specified. We demonstrate that on s

Zachary Friggstad, Mahya Jamshidian

In this paper, we present an improved approximation algorithm for three related problems. In the Minimum Sum of Radii clustering problem (MSR), we aim to select $k$ balls in a metric space to cover all points while minimizing the sum of the radii. In the Minimum Sum of Diameters clustering problem (MSD), we are to pick $k$ clusters to cover all the points su

Vivek Ramanujan, Kushal Tirumala, Armen Aghajanyan, Luke Zettlemoyer

Current image generation methods are based on a two-stage training approach. In stage 1, an auto-encoder is trained to compress an image into a latent space; in stage 2, a generative model is trained to learn a distribution over that latent space. This reveals a fundamental trade-off, do we compress more aggressively to make the latent distribution easier fo

Marc Carauleanu, Michael Vaiana, Judd Rosenblatt, Cameron Berg

As AI systems increasingly make critical decisions, deceptive AI poses a significant challenge to trust and safety. We present Self-Other Overlap (SOO) fine-tuning, a promising approach in AI Safety that could substantially improve our ability to build honest artificial intelligence. Inspired by cognitive neuroscience research on empathy, SOO aims to align h

Paul M. Masanja, Toraya Fernández-Ruiz, Esther J. Tarimo, Nayara Carral-Sainz

The development of advanced materials with high specific energy is crucial for enabling sustainable energy storage solutions, particularly in applications such as lithium-air batteries. Lithium peroxide (Li$_{2}$O$_{2}$) is a key discharge product in non-aqueous lithium-air systems, where its structural and electronic properties significantly influence batte

Hasara Kalumin, Amol Deshpande

As database query processing techniques are being used to handle diverse workloads, a key emerging challenge is how to efficiently handle multi-way join queries containing multiple many-to-many joins. While uncommon in traditional enterprise settings that have been the focus of much of the query optimization work to date, such queries are seen frequently in