December 2024 arXiv papers — page 147

Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez, Ethan Steinberg

Foundation Models (FMs) trained on Electronic Health Records (EHRs) have achieved state-of-the-art results on numerous clinical prediction tasks. However, most existing EHR FMs have context windows of <1k tokens. This prevents them from modeling full patient EHRs which can exceed 10k's of events. Recent advancements in subquadratic long-context architectures

Igor Ciganović

In this paper, we determine the composition series of the induced representation $\delta([\nu^{\frac{1}{2}}\rho,\nu^c\rho])\times \delta([\nu^{-a}\rho,\nu^b\rho]) \rtimes \sigma$ where $a, b, c \in \mathbb{Z}+\frac{1}{2}$ such that $\frac{1}{2}\leq a < b < c$, $\rho$ is an irreducible cuspidal unitary representation of a general linear group and $\sigma$ is

In Gim, Seung-seob Lee, Lin Zhong

Large language models (LLMs) use function calls to interface with external tools and data source. However, the current approach to LLM function calling is inherently synchronous, where each call blocks LLM inference, limiting LLM operation and concurrent function execution. In this work, we propose AsyncLM, a system for asynchronous LLM function calling. Asy

Junke Jiang, Tammo van der Heide, Simon Thébaud, Carlos Raúl Lien-Medrano

Density Functional Tight-Binding (DFTB), an approximative approach derived from Density Functional Theory (DFT), has the potential to pave the way for simulations of large periodic or non-periodic systems. We have specifically tailored DFTB parameters to enhance the accuracy of electronic band gap calculations in both 3D and 2D lead-iodide perovskites, at a

Youyuan Liu, Taolue Yang, Sian Jin

Scientific applications typically generate large volumes of floating-point data, making lossy compression one of the most effective methods for data reduction, thereby lowering storage requirements and improving performance in large-scale applications. However, variations in compression time can significantly impact overall performance improvement, due to in

Giorgia Carra, Bogdan Kulynych, François Bastardot, Daniel E. Kaufmann

Although Large Language Models (LLMs) have shown promising performance in healthcare-related applications, their deployment in the medical domain poses unique challenges of ethical, regulatory, and technical nature. In this study, we employ a systematic participatory approach to investigate the needs and expectations regarding clinical applications of LLMs a

Petr Honzík, Stefanos Lappas, Lenka Slavíková

We establish the full quasi-Banach range of $L^{p_1}(\mathbb R) \times L^{p_2}(\mathbb R) \rightarrow L^p(\mathbb R)$ bounds for one-dimensional bilinear singular integral operators with homogeneous kernels whose restriction $\Omega$ to the unit sphere $\mathbb S^1$ is supported away from the degenerate line $\theta_1=\theta_2$, belongs to $L^q(\mathbb S^1)$

Rohit Hegde

Supplementing the Heisenberg model with a Hubbard-commuting kinetic of electrons adds to its spectrum without interference. One consequence is the precise incorporation of canonical linear spin wave theory within the time-dependent Hartree-Fock framework, as pure localization emerges from itinerant dynamics. This embedding method generalizes to all spin-1/2

Jieyu Zhang, Le Xue, Linxin Song, Jun Wang

With the rise of multimodal applications, instruction data has become critical for training multimodal language models capable of understanding complex image-based queries. Existing practices rely on powerful but costly large language models (LLMs) or multimodal language models (MLMs) to produce instruction data. These are often prone to hallucinations, lice

Hai V. Nguyen, Tan Bui-Thanh, Clint Dawson

Efficient real-time solvers for forward and inverse problems are essential in engineering and science applications. Machine learning surrogate models have emerged as promising alternatives to traditional methods, offering substantially reduced computational time. Nevertheless, these models typically demand extensive training datasets to achieve robust genera

Kazi Ranjibul Islam, Andrey Chubukov

We analyze superconductivity in a multi-orbital fermionic system near the onset of a nematic order, using doped FeSe as an example. We associate nematicity with a spontaneous polarization between $d_{\text{xz}}$ and $d_{\text{yz}}$ orbitals (a Pomeranchuk-type order) and analyze the pairing mediated by soft nematic fluctuations. Such a pairing gives rise to

Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker

Large-scale generative models have shown impressive image-generation capabilities, propelled by massive data. However, this often inadvertently leads to the generation of harmful or inappropriate content and raises copyright concerns. Driven by these concerns, machine unlearning has become crucial to effectively purge undesirable knowledge from models. While

Toai Luong, Tadele Mengesha, Steven M. Wise, Ming Hei Wong

Diffuse domain methods (DDMs) have garnered significant attention for approximating solutions to partial differential equations on complex geometries. These methods implicitly represent the geometry by replacing the sharp boundary interface with a diffuse layer of thickness $\varepsilon$, which scales with the minimum grid size. This approach reformulates th

Lauren F. O'Donnell, Gonzalo G. Rodriguez, Gregory Lemberskiy, Zidan Yu

We developed a new sodium magnetic resonance fingerprinting ($^\text{23}\text{Na}$ MRF) method for the simultaneous mapping of $\text{T}_\text{1}$, $\text{T}_\text{2,long}^{*}$, $\text{T}_\text{2,short}^{*}$ and sodium density with built-in $\Delta\text{B}_{1}^{+}$ (radiofrequency transmission inhomogeneities) and $\Delta\text{f}_\text{0}$ corrections (frequ

Behzad Ousat, Mahshad Shariatnasab, Esteban Schafir, Farhad Shirani Chaharsooghi

Web traffic has evolved to include both human users and automated agents, ranging from benign web crawlers to adversarial scanners such as those capable of credential stuffing, command injection, and account hijacking at the web scale. The estimated financial costs of these adversarial activities are estimated to exceed tens of billions of dollars in 2023. I

Shivam Mundhra, Elina Sendonaris, Robert M. Gray, James Williams

Thin-film lithium niobate (TFLN) has recently emerged as a promising platform for integrated nonlinear photonics, enabling the use of optical parametric amplifiers (OPAs) for applications in quantum information processing, precision metrology, and ultrafast optical signal processing. However, OPA waveguide designs have not yet achieved the phase-matching con

Nora Belrose, Adam Scherlis

We examine the geometry of neural network training using the Jacobian of trained network parameters with respect to their initial values. Our analysis reveals low-dimensional structure in the training process which is dependent on the input data but largely independent of the labels. We find that the singular value spectrum of the Jacobian matrix consists of

Alexander E. Thelen, Katherine de Kleer, Martin A. Cordiner, Imke de Pater

We present spatially resolved measurements of SO$_2$ and NaCl winds on Io at several unique points in its orbit: before and after eclipse, and at maximum eastern and western elongation. The derived wind fields represent a unique case of meteorology in a rarified, volcanic atmosphere. Through the use of Doppler shift measurements in emission spectra obtained

E. H. Essaky, M. Hassani, C. E. Rhazlane

The purpose of this paper is to study certain set-valued integrals in UMD Banach spaces and provide a compatible form of the martingale representation theorem for set-valued martingales. Under specific conditions, these martingales can be expressed using revised set-valued stochastic integrals with respect to a real standard Brownian motion $W = (W_t)_{t\in[

Edward Ratner, Elliot Farmer, Brandon Warner, Christopher Douglas

Utilizing machine learning techniques has always required choosing hyperparameters. This is true whether one uses a classical technique such as a KNN or very modern neural networks such as Deep Learning. Though in many applications, hyperparameters are chosen by hand, automated methods have become increasingly more common. These automated methods have become

N. Zimniak, J. Ferreira, J. Jacquemin-Ide

The theory of jet emitting disks (JEDs) provides a mathematical framework for a self-consistent treatment of steady-state accretion and ejection. A large-scale vertical magnetic field threads the accretion disk where magnetic turbulence occurs in a strongly magnetized plasma. A fraction of mass leaves the disk and feeds the two laminar super-Alf\'enic jets.

R. N. Ball, A. W. Hager

In the category \(\mathbf{V}\) of unital archimedean vector lattices, four notions of uniform completeness obtain. In all cases completeness requires the convergence of uniformly Cauchy sequences; the completions are distinguished by the manner in which the convergence is regulated. Ordinary uniform convergence is regulated by the canonical unit \(1\). Inner

Susheel Kumar, Chiranjit Majhi, Krishnacharya Khare, Manjesh Kumar Singh

Adhesion control at the interface of two surfaces is crucial in many applications. Examples are the design of micro and nanodevices such as microfuidics devices, biochips, and electronic sensors. Adhesion at the interface of two materials can be controlled by various methods such as chemical treatment on the surface of the materials, modification of the surf

S. A. Paston, D. S. Shatkov

We investigate the possibility of the existence of a classical version of Hawking radiation - solutions to classical field equations that consist solely of outgoing waves, in the spacetime of a collapsing black hole. The non-static nature of the corresponding metric results in the absence of energy conservation for matter, which could otherwise a priori proh

Bodhisatwa Chatterjee, Neeraj Jadhav, Santosh Pande

Application profiling is essential for software optimization tasks such as code layout and memory placement, where optimization decisions depend on program behavior. However, modern applications exhibit significant input-dependent variability, limiting the effectiveness of conventional profiling approaches that rely on a single representative execution. We p

Xavier Calmet, Stephen D. H. Hsu

In this invited review, we discuss the evaporation of a black hole, with emphasis on the resulting macroscopically distinct patterns of Hawking radiation. The density matrix of this radiation can approach a pure final state in the form of a highly entangled macroscopic superposition state. We note that this exact property is exhibited in replica wormhole cal

Le Song, Eran Segal, Eric Xing

We present an approach of using AI to model and simulate biology and life. Why is it important? Because at the core of medicine, pharmacy, public health, longevity, agriculture and food security, environmental protection, and clean energy, it is biology at work. Biology in the physical world is too complex to manipulate and always expensive and risky to tamp

Binglu Wang, Ching Jin, Chaoming Song, Johannes Bjelland

Despite the vast literature on the diffusion of innovations that impacts a broad range of disciplines, our understanding of the abandonment of innovations remains limited yet is essential for a deeper understanding of the innovation lifecycle. Here, we analyze four large-scale datasets that capture the temporal and structural patterns of innovation abandonme

Lei Zeng, Hamideh Rouhanitazangi, Xianyang Chen, Jiacai Lu

Three-phase multiphase flows are found in an extraordinarily large number of applications. Often those involve a liquid phase and a gas phase in addition to a third phase that consists of either liquid drops or solid particles, suspended in the flow. Frequently the third phase is in contact with both the liquid and the gas, resulting in a contact line where

Guy Kornowski, Ohad Shamir

We study the problem of solving matrix games of the form $\min_{\mathbf{p}\in\Delta}\max_{\mathbf{w}\in\mathcal{W}}\mathbf{p}^{\top}A\mathbf{w}$, where $A$ is a matrix and $\Delta$ is the probability simplex. This problem encapsulates canonical tasks such as finding a linear separator and computing Nash equilibria in zero-sum games. However, perhaps surprisi

Luis Morales-Navarro, Yasmin B. Kafai, Lauren Vogelstein, Evelyn Yu

While there is widespread interest in supporting young people to critically evaluate machine learning-powered systems, there is little research on how we can support them in inquiring about how these systems work and what their limitations and implications may be. Outside of K-12 education, an effective strategy in evaluating black-boxed systems is algorithm

Raffaella Morganti

The presence, distribution and kinematics of atomic neutral hydrogen in the central regions of galaxies can be traced by the HI 21~cm line observed in absorption. Depending only on the strength of the radio continuum, the associated absorption can trace the gas down to pc scale, which is ideal for exploring the HI in the nuclear regions of radio AGN. This pa

Yukun Du

We establish a general completeness criterion for Dirichlet-Selberg domains in the symmetric space $SL(n,\mathbb{R})/SO(n)$. By introducing and analyzing Busemann-Selberg functions - which extend classical Busemann functions and capture asymptotic behavior toward the Satake boundary - we show that every gluing manifold or orbifold produced by Dirichlet-Selbe

Michael P. Landry, Yair N. Minsky, Samuel J. Taylor

Let phi be a pseudo-Anosov flow on a closed oriented atoroidal 3-manifold M. We show that if F is any taut foliation almost transverse to phi, then the action of pi_1(M) on the boundary of the flow space, together with a natural collection of explicitly described monotone maps, defines a universal circle for F in the sense of Thurston and Calegari-Dunfield.

Maria T. Tagliaferri, Leonardo Campeggi, Owen N. Beck, Inseung Kang

Falls during daily ambulation activities are a leading cause of injury in older adults due to delayed physiological responses to disturbances of balance. Lower-limb exoskeletons have the potential to mitigate fall incidents by detecting and reacting to perturbations before the user. Although commonly used, the standard metric for perturbation detection, whol

David S. Pereira

We propose \emph{Scalar-Tensor Baryogenesis} (STB), in which the $C\!P$-violating bias needed for baryogenesis is sourced by the \emph{gravitational} scalars that appear in scalar-tensor representations of modified gravity. Derivative couplings $M_\ast^{-d}\nabla_\mu f(\phi_i)\,J^\mu_{B-L}$ act as an effective chemical potential $\mu_{B-L}\propto\dot f$ in a

Kejia Ren, Gaotian Wang, Andrew S. Morgan, Kaiyu Hang

Robotic manipulation research has investigated contact-rich problems and strategies that require robots to intentionally collide with their environment, to accomplish tasks that cannot be handled by traditional collision-free solutions. By enabling compliant robot motions, collisions between the robot and its environment become more tolerable and can thus be

Justin R. Crepp, Jonathan Crass, Andrew J. Bechter, Brian L. Sands

Precision radial velocity (RV) spectrographs that use adaptive optics (AO) show promise to advance telescope observing capabilities beyond those of seeing-limited designs. We are building a spectrograph for the Large Binocular Telescope (LBT) named iLocater that uses AO to inject starlight directly into single mode fibers (SMF). iLocater's first acquisition

Yash Savani, Marc Finzi, J. Zico Kolter

We introduce a novel, training-free method for sampling differentiable representations (diffreps) using pretrained diffusion models. Rather than merely mode-seeking, our method achieves sampling by "pulling back" the dynamics of the reverse-time process--from the image space to the diffrep parameter space--and updating the parameters according to this pulled

Suchinthaka Wanninayaka, Achintha Wijesinghe, Weiwei Wang, Yu-Chieh Chao

The rapid expansion of edge devices and Internet-of-Things (IoT) continues to heighten the demand for data transport under limited spectrum resources. The goal-oriented communications (GO-COM), unlike traditional communication systems designed for bit-level accuracy, prioritizes more critical information for specific application goals at the receiver. To imp

Abdelrahman A. Ali, Aya E. Fouda, Radwa J. Hanafy, Mohammed E. Fouda

Mental health disorders are increasingly prevalent worldwide, creating an urgent need for innovative tools to support early diagnosis and intervention. This study explores the potential of Large Language Models (LLMs) in multimodal mental health diagnostics, specifically for detecting depression and Post Traumatic Stress Disorder through text and audio modal

Darin C. Mumma, Zhonghao Sun, Alexis Mercenne, Kristina D. Launey

Solving atomic nuclei from first principles places enormous demands on computational resources, which grow exponentially with increasing number of particles and the size of the space they occupy. We present first quantum simulations based on the variational quantum eigensolver for the low-lying structure of the $^{12}$C nucleus that provide acceptable bound-

Mehdi Noroozi, Isma Hadji, Victor Escorcia, Anestis Zaganidis

There has been immense progress recently in the visual quality of Stable Diffusion-based Super Resolution (SD-SR). However, deploying large diffusion models on computationally restricted devices such as mobile phones remains impractical due to the large model size and high latency. This is compounded for SR as it often operates at high res (e.g. 4Kx3K). In t

Eduardo Willwock Lussi, Lucas Cavalcante de Sousa, Jerusa Marchi, Rafael de Santiago

Quantum finite automata can be used for pattern recognition. Present implementations on actual quantum devices face decoherence issues, which compromise the quality of long strings computation. In this work, we focus on the Measure Once 1-way Quantum Finite Automata (MO1QFA) model for addressing the MOD^p problem, investigating how quantum errors may affect

Andrew Hardt, David Wallach

The "back-stabilization number" for products of Schubert polynomials is the distance the corresponding permutations must be shifted before the structure constants stabilize. We give an explicit formula for this number and thereby prove a conjecture of N. Li in a strengthened form. This leads to an additional result: a formula for the smallest $n$ such that a

Arda Sevinc, Abdurrahman Gumus

Chain of Thought (CoT) was introduced in recent research as a method for improving step-by-step reasoning in Large Language Models. However, CoT has limited applications such as its need for hand-crafted few-shot exemplar prompts and no capability to adjust itself to different queries. In this work, we propose a system to automatically generate rationales us

Zhenggang Tang, Yuchen Fan, Dilin Wang, Hongyu Xu

Recent sparse multi-view scene reconstruction advances like DUSt3R and MASt3R no longer require camera calibration and camera pose estimation. However, they only process a pair of views at a time to infer pixel-aligned pointmaps. When dealing with more than two views, a combinatorial number of error prone pairwise reconstructions are usually followed by an e

Andreas Gsponer, Philipp Gaggl, Jürgen Burin, Simon Waid

Due to the increased commercial availability, wide-bandgap semiconductors and their radiation hardness have recently received increased interest from the particle physics community. 4H-Silicon Carbide (SiC), especially, is an attractive candidate for future radiation-hard detectors which do not require cooling. This paper investigates the radiation hardness

Dhimiter Canko, Mattia Pozzoli

We present analytic results on physical kinematics for four integral families that are relevant to the production of two off-shell vector bosons with different masses. Our study consists of a ladder-box, a tennis-court, and two reducible ladder-box-like families. The results for the master integrals of these families are expressed up to order six in the dime

Giusi Capobianco, Yoav Len

We prove that the tropical Abel--Prym map $\Psi\colon \widetilde\Gamma\to Prym(\widetilde\Gamma/\Gamma)$ associated with a free double cover $\pi\colon \widetilde\Gamma\to \Gamma$ of hyperelliptic metric graphs is harmonic of degree $2$ in accordance with the already established algebraic result. We then prove a partial converse. Contrary to the analogous al

Khondoker Ittehadul Islam

In this paper, we conduct experiment to analyze whether models can classify offensive texts better with the help of sentiment. We conduct this experiment on the SemEval 2019 task 6, OLID, dataset. First, we utilize pre-trained language models to predict the sentiment of each instance. Later we pick the model that achieved the best performance on the OLID tes

C. J. Lang

In this paper, we examine Lie group actions on moduli spaces (sets themselves built as quotients by group actions) and their fixed points. We show that when the Lie group is compact and connected, we obtain a linear constraint. This constraint makes the problem of finding fixed points one of representation theory, greatly simplifying the search for such poin

Nick E. Mavromatos

I review a mechanism for a potential explanation of the dominance of matter over antimatter in the Universe (``our existence''), based on a (3+1)-dimensional string-inspired cosmological model, characterised by (uncancelled) gravitational Chern-Simons (gCS) anomalies in the premordial epochs. The model is consistent with general covariance but entails sponta

Yaniv Benny, Lior Wolf

This paper proposes a novel method for omnidirectional 360$\degree$ perception. Most common previous methods relied on equirectangular projection. This representation is easily applicable to 2D operation layers but introduces distortions into the image. Other methods attempted to remove the distortions by maintaining a sphere representation but relied on com

Yingyi Ma, Zhe Liu, Ozlem Kalinli

The advent of Large Language Models (LLM) has reformed the Automatic Speech Recognition (ASR). Prompting LLM with audio embeddings to generate transcriptions becomes the new state-of-the-art ASR. Despite LLMs being trained with an extensive amount of text corpora, high-quality domain-specific text data can still significantly enhance ASR performance on domai

A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman

"Machine unlearning" is a popular proposed solution for mitigating the existence of content in an AI model that is problematic for legal or moral reasons, including privacy, copyright, safety, and more. For example, unlearning is often invoked as a solution for removing the effects of specific information from a generative-AI model's parameters, e.g., a part

Tornike Karchkhadze, Mohammad Rasool Izadi, Shuo Zhang, Shlomo Dubnov

In this work, we propose an approach to music source separation that uses a generative diffusion model as a last-stage refinement on top of a deterministic separator, progressively enhancing the separated sources through iterative denoising. While the diffusion refinement yields measurable quality gains, it requires iterative steps at inference, increasing c

Md Mahadi Rajib, Dhritiman Bhattacharya, Christopher J. Jensen, Gong Chen

Recent progresses in magnetoionics offer exciting potentials to leverage its non-linearity, short-term memory, and energy-efficiency to uniquely advance the field of physical reservoir computing. In this work, we experimentally demonstrate the classification of temporal data using a magneto-ionic (MI) heterostructure. The device was specifically engineered t

Pierre Dumond, Gilles Chabrier

It is well known that departure from sphericity in the geometry of primordial dark matter halos modifies their mass function. The ellipsoidal collapse model yields a better agreement with simulations of hierarchical clustering than the original, spherical model. In the present paper, we examine the same issue in the context of star formation by studying the

Ian Miller

In this article we obtain new scattering and blow-up solutions for intercritical focusing nonlinear Schr\"{o}dinger equations (NLS) above the ground state mass-energy threshold. The main focus of this article is the establishment of some solutions with arbitrarily large mass-energy which scatter in both time directions. In particular, large mass-energy which

Subramaniam Saravana Sankar, Stanislav Kovar, Martin Pospisilik, Michael Galda

With the advent of smartphones, there has been a recent increase in the use of capacitive touch sensing for various Human Machine Interfaces (HMI). Capacitive-based touch sensing provides higher flexibility and cost-effectiveness than, methodologies such as resistive-based touch sensing. However, Capacitive-based touch sensing is more prone to disturbances s

Albrecht Kurze, Alexa Becker

More and more smart devices enter our homes. Often these devices come with a variety of sensors, mostly simple sensors, e.g., for light, temperature, humidity or motion. And they all collect data. While it is data of the home environment it is also data of domestic life in the home. Thus it is data of the people and by the people in the home capturing their

Fu Wang, Xinquan Huang, Tariq Alkhalifah

Full waveform inversion (FWI) often faces challenges due to inadequate seismic observations, resulting in band-limited and geologically inaccurate inversion results. Incorporating prior information from potential velocity distributions, well-log information, and our geological knowledge and expectations can significantly improve FWI convergence to a realisti

Jorge Guevara, Victor Nascimento, Johannes Schmude, Daniel Salles

Wind downscaling is essential for improving the spatial resolution of weather forecasts, particularly in operational Numerical Weather Prediction (NWP). This study advances wind downscaling by extending the DownGAN framework introduced by Annau et al.,to operational datasets from the Global Deterministic Prediction System (GDPS) and High-Resolution Determini

Tim B. Miller, Katherine A. Suess, David J. Setton, Sedona H. Price

We study the rest-frame optical and ultraviolet morphology of galaxies in the first billion years of the Universe. Using JWST data from the UNCOVER and MegaScience surveys targeting the lensing cluster Abell 2744 we present multi-band morphological measurements for a sample of 995 galaxies selected using 20-band NIRCam photometry and 35 using NIRSpec Prism s

Diwakar Khadka, Satish Adhikari, Atit Pokharel, Sandeep Marasinee

Solar energy utilization in places like Nepal, is often obstructed by unpredicted environmental factors and existing technological barriers. The challenges encountered often result in fluctuating energy outputs, hindering the transition to greener energy solutions. To tackle these issues, this study introduces a custom-designed Maximum Power Point Tracking (

Callum W. Fairbairn

Bending waves are perhaps the most fundamental and analytically tractable phenomena in warped disc dynamics. In this work we conduct 3D grid-based, numerical experiments of bending waves in laminar, viscous hydrodynamic and turbulent, weakly magnetised discs, capturing their behaviour in unprecedented detail. We clearly elucidate the theory from first princi

Haoyu Yang, Zheng Zhang, Saket Sathe

Large language models, such as ChatGPT, Claude, or LLaMA, are gigantic, monolithic, and possess the superpower to simultaneously support thousands of tasks. However, high-throughput applications often prefer smaller task-specific models because of their lower latency and cost. One challenge of using task-specific models is the incremental need for solving ne

Nadia Athar Sheikh, Daniel Buades Marcos, Anne-Laure Jousse, Akintunde Oladipo

Given the dominance of dense retrievers that do not generalize well beyond their training dataset distributions, domain-specific test sets are essential in evaluating retrieval. There are few test datasets for retrieval systems intended for use by healthcare providers in a point-of-care setting. To fill this gap we have collaborated with medical professional

Serkan Doruk Hazinedar, Yaghoub Heydarzade, Maryam Ranjbar

Cotton theory (CT) introduces a higher derivative extension of General Relativity (GR) characterized by third-rank field equations. Recently, key distinctions between CT and GR concerning wave and vacuum solutions have been highlighted in [1, 2]. In this study, two particular non-vacuum solutions of CT are investigated within its Codazzi formulation. The mot

Michal Dory, Shaked Matar

We present fast algorithms for approximate shortest paths in the massively parallel computation (MPC) model. We provide randomized algorithms that take $poly(\log{\log{n}})$ rounds in the near-linear memory MPC model. Our results are for unweighted undirected graphs with $n$ vertices and $m$ edges. Our first contribution is a $(1+\epsilon)$-approximation alg

Rozina L. Myoya, Vukosi Marivate, Idris Abdulmumin

Public transport systems in many Sub-Saharan countries often receive less attention compared to other sectors, underscoring the need for innovative solutions to improve the Quality of Service (QoS) and overall user experience. This study explored commuter opinion mining to understand sentiments toward existing public transport systems in Kenya, Tanzania, and

BABAR Collaboration

A mechanism of baryogenesis and dark matter production via $B$-meson oscillations and decays has recently been proposed to explain the observed dark matter abundance and matter-antimatter asymmetry in the universe. This mechanism introduces a light dark sector particle ($\psi_D$) with a non-zero baryonic charge. We present a search for this new state in $B^+

Ahmad Bin Rabiah, Nafis Sadeq, Julian McAuley

Conversational recommendation systems (CRS) leverage contextual information from conversations to generate recommendations but often struggle due to a lack of collaborative filtering (CF) signals, which capture user-item interaction patterns essential for accurate recommendations. We introduce Reddit-ML32M, a dataset that links Reddit conversations with inte

Haya Samaana, Diego Elias Costa, Ahmad Abdellatif, Emad Shihab

To comply with high productivity demands, software developers reuse free open-source software (FOSS) code to avoid reinventing the wheel when incorporating software features. The reliance on FOSS reuse has been shown to improve productivity and the quality of delivered software; however, reusing FOSS comes at the risk of exposing software projects to public

Venkat Margapuri

Ulcerative Colitis (UC) is an incurable inflammatory bowel disease that leads to ulcers along the large intestine and rectum. The increase in the prevalence of UC coupled with gastrointestinal physician shortages stresses the healthcare system and limits the care UC patients receive. A colonoscopy is performed to diagnose UC and assess its severity based on

Bardia Nadimi, Ghali Omar Boutaib, Hao Zheng

Recently, there has been a growing interest in leveraging Large Language Models for Verilog code generation. However, the current quality of the generated Verilog code remains suboptimal. This is largely due to the absence of well-defined, well-organized datasets with high-quality samples, as well as a lack of innovative fine-tuning methods and models specif

Osvaldo Gramaxo Freitas, Anastasios Theodoropoulos, Nino Villanueva, Tiago Fernandes

Gravitational-wave approximants are essential for gravitational-wave astronomy, allowing the coverage binary black hole parameter space for inference or match filtering without costly numerical relativity (NR) simulations, but generally trading some accuracy for computational efficiency. To reduce this trade-off, NR surrogate models can be constructed using

Cella M. Sum, Caroline Shi, Sarah E. Fox

With the rise of remote work, a range of surveillance technologies are increasingly being used by business owners to track and monitor employees, raising concerns about worker rights and privacy. Through analysis of Reddit posts and in-depth semi-structured interviews, this paper seeks to understand how workers across a range of sectors make sense of and res

Sergei Sinchuk

In this paper we study the $\mathbb{A}^1$-invariance of the unstable functor $\mathrm{K}_2(\Phi, R)$ in the case when $\Phi$ is an irreducible root system of type $\mathsf{ADE}$ containing $\mathsf{A}_4$ and not of type $\mathsf{E}_8$. We show that in the geometric case, i. e. when $R$ is a regular ring containing a field $k$ one has $\mathrm{K}_2(\Phi, R[t]

Priti Oli, Rabin Banjade, Andrew M. Olney, Vasile Rus

This paper investigates various approaches using Large Language Models (LLMs) to identify gaps and misconceptions in students' self-explanations of specific instructional material, in our case explanations of code examples. This research is a part of our larger effort to automate the assessment of students' freely generated responses, focusing specifically o

Roland Speicher, Alexander Wendel

In this article, we investigate how the entrywise application of a non-linear function to symmetric orthogonally invariant random matrix ensembles alters the spectral distribution. We treat also the multivariate case where we apply multivariate functions to entries of several orthogonally invariant matrices; where even correlations between the matrices are a

Diego Mondéjar

We show that the Hausdorff reflection preserves the shape type of spaces. Some examples as well as the applicability in inverse limits of finite spaces are presented.

Qiaochu Wan, Daniel Vaz, Li Xiang, Anshul Ramavath

Previous experimental and theoretical work has given evidence of the existence of doubly charged exciton states in strongly screened bilayers of transition metal dichalcogenide (TMD) layers. These complexes are important because they are performed electron pairs that can, in principle, undergo Bose-Einstein condensation (BEC), in which case they would also f

Jiachen Xu, Yushuai Li, Torben Bach Pedersen, Yuqiang He

Emerging digital twin technology has the potential to revolutionize voltage control in power systems. However, the state-of-the-art digital twin method suffers from low computational and sampling efficiency, which hinders its applications. To address this issue, we propose a Gumbel-Consistency Digital Twin (GC-DT) method that enhances voltage control with im

Samuel S. Taylor, Nicholas Skoufis, Hongbo Du, Cody Covington

Time-dependent density-functional theory simulations are performed to examine the effects of varying incident points and kinetic energies of hydrogen atom projectiles on a graphene-like structure. The simulations reveal that the incident point significantly influences the hydrogen atom's kinetic energy post-interaction, the vibrational dynamics of the graphe

Jan Li, Tim Coopmans, Patrick Emonts, Kenneth Goodenough

Quantum repeaters play a crucial role in the effective distribution of entanglement over long distances. The nearest-future type of quantum repeater requires two operations: entanglement generation across neighbouring repeaters and entanglement swapping to promote short-range entanglement to long-range. For many hardware setups, these actions are probabilist

Christoph Winkler, Kristina Dabrock, Serhiy Kapustyan, Craig Hart

Rooftop photovoltaic (RTPV) systems are essential for building a decarbonized and, due to its decentralized structure, more resilient energy system, and are particularly important for Ukraine, where recent conflicts have damaged more than half of its electricity and heat supply capacity. Favorable solar irradiation conditions make Ukraine a strong candidate

Aiden Lewington, Alekhya Vittalam, Anshumaan Singh, Anuja Uppuluri

Advances in artificial intelligence (AI) present significant risks and opportunities, requiring improved governance to mitigate societal harms and promote equitable benefits. Current incentive structures and regulatory delays may hinder responsible AI development and deployment, particularly in light of the transformative potential of large language models (

Charo I. del Genio

Numerous networked systems feature a structure of nontrivial communities, which often correspond to their functional modules. Such communities have been detected in real-world biological, social and technological systems, as well as in synthetic models thereof. While much effort has been devoted to developing methods for community detection in traditional ne

Dmitry Mukhin, Roman Samoilov, Abdel Hannachi

The low-frequency variability of the mid-latitude atmosphere involves complex nonlinear and chaotic dynamical processes posing predictability challenges. It is characterized by sporadically recurring, often long-lived patterns of atmospheric circulation of hemispheric scale known as weather regimes. The evolution of these circulation regimes in addition to t

Andrew Hofstrand

The unique geometry of the two-dimensional tripartite Kagome lattice is responsible for shaping diverse families of spatially localized and time-periodic nonlinear modes known as discrete breathers. We state conditions for the existence of breathers and compute their spatiotemporal profiles near the edges of the linear phonon spectrum. Our findings include t

Hoi-Yin Lee, Peng Zhou, Anqing Duan, Wanyu Ma

The ability to wield tools was once considered exclusive to human intelligence, but it's now known that many other animals, like crows, possess this capability. Yet, robotic systems still fall short of matching biological dexterity. In this paper, we investigate the use of Large Language Models (LLMs), tool affordances, and object manoeuvrability for non-pre

Deniz Kus, Markus Reineke

We derive a piecewise-linear formula for the rigid representation of a Dynkin quiver of a given dimension vector, and illustrate the formula in several examples.

Mayank Sharma, Nahum Arav, Kirk T. Korista, Manuel Bautista

Context: The study of quasar outflows is essential in understanding the connection between active galactic nuclei (AGN) and their host galaxies. We analyze the VLT/UVES spectrum of quasar SDSS J0932+0840 and identify several narrow and broad outflow components in absorption, with multiple ionization species including Fe II, which puts it among a rare class o

Ankit Kumar Patel, Dewanshi Paul, Sarthak Giri, Sneha Chaudhary

Security systems relying on passwords are vulnerable to being forgotten, guessed, or breached. Likewise, biometric systems that operate independently are at risk of template spoofing and replay incidents. This paper introduces a biocryptosystem utilizing face recognition techniques to address these issues, allowing for the encryption and decryption of variou

Bharath Raj, Garvit Suri, Vikrant Dewangan, Raghav Sonavane

Traditional greedy tokenization methods have been a critical step in Natural Language Processing (NLP), influencing how text is converted into tokens and directly impacting model performance. While subword tokenizers like Byte-Pair Encoding (BPE) are widely used, questions remain about their optimality across model scales and languages. In this work, we demo

Wendelin Lutz

We prove a generic Torelli theorem for a class of three-dimensional log Calabi--Yau pairs $(Y, D)$ with maximal boundary.

Lars Hertel, Neil Daftary, Fedor Borisyuk, Aman Gupta

We study user history modeling via Transformer encoders in deep learning recommendation models (DLRM). Such architectures can significantly improve recommendation quality, but usually incur high latency cost necessitating infrastructure upgrades or very small Transformer models. An important part of user history modeling is early fusion of the candidate item

Chen-Xin Jiang, Zi-Xiang Hu, Bo Yang

Flat bands result in a divergent density of states and high sensitivity to interactions in physical systems. While such bands are well known in systems under magnetic fields, their realization and behavior in zero-field settings remain largely unexplored. Here we compare the behavior of electrons confined to a single flat band on the surface of a sphere to t