October 2024 arXiv papers — page 82

João Barreto, Daniel Castro, Paolo Romano, Alexandro Baldassin

Despite the recent improvements in supporting Persistent Hardware Transactions (PHTs) on emerging persistent memories (PM), the poor performance of Read-Only (RO) transactions remains largely overlooked. We propose DUMBO, a new design for PHT that eliminates the two most crucial bottlenecks that hinder RO transactions in state-of-the-art PHT. At its core, DU

Thomas Koberda, J. de la Nuez González

Let $M$ be a compact, connected manifold of positive dimension and let $\mathcal G\leq\textrm{Homeo}(M)$ be \emph{locally approximating} in the sense that for all open $U\subseteq M$ compactly contained in a single Euclidean chart of $M$, the subgroup $\mathcal G[U]$ consisting of elements of $\mathcal G$ supported in $U$ is dense in the full group of homeom

Alex Reinhart, Ben Markey, Michael Laudenbach, Kachatad Pantusen

Large language models (LLMs) are capable of writing grammatical text that follows instructions, answers questions, and solves problems. As they have advanced, it has become difficult to distinguish their output from human-written text. While past research has found some differences in surface features such as word choice and punctuation, and developed classi

Ronglong Fang, Yuesheng Xu

Deep neural networks (DNNs) suffer from the spectral bias, wherein DNNs typically exhibit a tendency to prioritize the learning of lower-frequency components of a function, struggling to capture its high-frequency features. This paper is to address this issue. Notice that a function having only low frequency components may be well-represented by a shallow ne

Jan Christian Hauffen, Peter Jung, Giuseppe Caire

Optimizing network utility in device-to-device networks is typically formulated as a non-convex optimization problem. This paper addresses the scenario where the optimization variables are from a bounded but continuous set, allowing each device to perform power control. The power at each link is optimized to maximize a desired network utility. Specifically,

Thomas Robert, Mher Safaryan, Ionut-Vlad Modoranu, Dan Alistarh

We introduce LDAdam, a memory-efficient optimizer for training large models, that performs adaptive optimization steps within lower dimensional subspaces, while consistently exploring the full parameter space during training. This strategy keeps the optimizer's memory footprint to a fraction of the model size. LDAdam relies on a new projection-aware update r

Jinwoo Kim, Shaan Nagy, Thomas Reps, Loris D'Antoni

Applications like program synthesis sometimes require proving that a property holds for all of the infinitely many programs described by a grammar - i.e., an inductively defined set of programs. Current verification frameworks overapproximate programs' behavior when sets of programs contain loops, including two Hoare-style logics that fail to be relatively c

Philipp Maurus, Daniel P. Armstrong, Stephen H. Scott, Tyler Cluff

Humans and other animals coactivate agonist and antagonist muscles in many motor actions. Increases in muscle coactivation are thought to leverage viscoelastic properties of skeletal muscles to provide resistance against limb motion. However, coactivation also emerges in scenarios where it seems paradoxical because the goal is not to resist limb motion but i

Pavel Rytir, Ales Wodecki, Georgios Korpas, Jakub Marecek

Causal learning from data has received much attention recently. Bayesian networks can be used to capture causal relationships. There, one recovers a weighted directed acyclic graph in which random variables are represented by vertices, and the weights associated with each edge represent the strengths of the causal relationships between them. This concept is

Francesco Pecora

Measuring the energy cascade rate in space plasmas is a challenging task for several reasons. This quantity is (i) inherently three-dimensional (ii) scale-dependent, (iii) anisotropic in the interplanetary plasma, and (iv) requires measurements of plasma parameters in at least four points. Here, we show how three of such problems have been addressed by apply

Wil Liam Teng, Kasper Rasmussen

With Signal's position as one of the most popular secure messaging protocols in use today, the threat of government coercion and mass surveillance, i.e., active Man-in-the-Middle (MitM) attacks, are more relevant than ever. On the other hand, studies [29, 33, 37, 38] have shown that user awareness is very poor when it comes to authenticating keys in instant

Fei-Yu Chen, H. Lu

We calculate the holographic central charges for general higher curvature gravity theory dual to eight dimensional CFT. To do this, we first elaborate the general form of Weyl anomaly in 8d CFT and find 11 non-trivial linearly independent curvature combinations, one of which is Euler density and the rest are Weyl invariants, including 7 non-differentiated on

Danielle McCool, Peter Lugtig, Barry Schouten

Individual mobility trajectories are difficult to measure and often incur long periods of missingness. Aggregation of this mobility data without accounting for the missingness leads to erroneous results, underestimating travel behavior. This paper proposes Dynamic Time Warping-Based Multiple Imputation (DTWBMI) as a method of filling long gaps in human mobil

Devendra Dahiphale, Naveen Madiraju, Justin Lin, Rutvik Karve

Digital payment systems have revolutionized financial transactions, offering unparalleled convenience and accessibility to users worldwide. However, the increasing popularity of these platforms has also attracted malicious actors seeking to exploit their vulnerabilities for financial gain. To address this challenge, robust and adaptable scam detection mechan

Ruikun Zhang, Hao Yang, Yan Yang, Ying Fu

Image dehazing has drawn a significant attention in recent years. Learning-based methods usually require paired hazy and corresponding ground truth (haze-free) images for training. However, it is difficult to collect real-world image pairs, which prevents developments of existing methods. Although several works partially alleviate this issue by using synthet

Sepehr Assadi, Aaron Bernstein, Zachary Langley, Lap Chi Lau

In the load-balancing problem, we have an $n$-vertex bipartite graph $G=(L, R, E)$ between a set of clients and servers. The goal is to find an assignment of all clients to the servers, while minimizing the maximum load on each server, where load of a server is the number of clients assigned to it. We study load-balancing in the one-way communication model:

Nathan Tallent, Jan Strube, Luanzheng Guo, Hyungro Lee

Automating the theory-experiment cycle requires effective distributed workflows that utilize a computing continuum spanning lab instruments, edge sensors, computing resources at multiple facilities, data sets distributed across multiple information sources, and potentially cloud. Unfortunately, the obvious methods for constructing continuum platforms, orches

Lars Gröninger, Beatriz Souza, Michael Pradel

Code changes are an integral part of the software development process. Many code changes are meant to improve the code without changing its functional behavior, e.g., refactorings and performance improvements. Unfortunately, validating whether a code change preserves the behavior is non-trivial, particularly when the code change is performed deep inside a co

Jiaji Zhang, Carlos L. Benavides-Riveros, Lipeng Chen

Describing the dynamics of strong-laser driven open quantum systems is a very challenging task that requires the solution of highly involved equations of motion. While machine learning techniques are being applied with some success to simulate the time evolution of individual quantum states, their use to approximate time-dependent operators (that can evolve

Yu Zhao, Xiaotang Du, Giwon Hong, Aryo Pradipta Gema

Large language models (LLMs) can store a significant amount of factual knowledge in their parameters. However, their parametric knowledge may conflict with the information provided in the context. Such conflicts can lead to undesirable model behaviour, such as reliance on outdated or incorrect information. In this work, we investigate whether LLMs can identi

Ali Anaissi, Ali Braytee, Junaid Akram

We present an advanced approach to medical question-answering (QA) services, using fine-tuned Large Language Models (LLMs) to improve the accuracy and reliability of healthcare information. Our study focuses on optimizing models like LLaMA-2 and Mistral, which have shown great promise in delivering precise, reliable medical answers. By leveraging comprehensi

S. N. Artekha

A new analytical model for the generation of axisymmetric tornado-type vortices has been developed. A solution to the nonlinear equation for the stream function in an unstable stratified atmosphere is obtained and analyzed within the framework of ideal hydrodynamics. The solution is sought by smooth connecting continuous solutions for the internal region ("e

X. Chen, J. Su, Y. P. Shen, L. Y. Zhang

The solar composition problem has puzzled astrophysicists for more than 20 years. Recent measurements of carbon-nitrogen-oxygen (CNO) neutrinos by the Borexino experiment show a $\sim2\sigma$ tension with the "low-metallicity" determinations. $^{14}$N$(p,\gamma)^{15}$O, the slowest reaction in the CNO cycle, plays a crucial role in the standard solar model (

Boukary Tai, Mohamed Congo, Marie Françoise Ouedraogo, Arouna Ouedraogo

The aim of this paper is to investigate the boundedness of periodic Fourier integral operators in Lebesgue spaces with variable exponent $L^{p(\cdot)}$ on the $n$-dimensional torus. We deal with operators of type $(\rho, \delta)$ which symbols belong to the H\"{o}rmander class $S^{m}_{\rho, \delta}(\mathbb{T}^{n}\times\mathbb{Z}^{n})$ for $0\leq\delta<\rho\l

Igor Ricardo Filgueira e Silva, Ovidiu Lipan, Fabian Hartmann, Sven Höfling

Based on a microscopic model of nonequilibrium carrier generation in a leaky dielectric, we analytically derive hysteresis loops for the dielectric response of non-polar, non-ferroelectric materials. We demonstrate how complex dielectric responses can emerge solely from the influence of transport processes that depend on energy levels, voltage polarity, and

Zhezhang Ding, Huijing Zhao

Precise trajectory prediction in complex driving scenarios is essential for autonomous vehicles. In practice, different driving scenarios present varying levels of difficulty for trajectory prediction models. However, most existing research focuses on the average precision of prediction results, while ignoring the underlying distribution of the input scenari

Yoshitaka Hatta, Jake Montgomery

Individual quarks and gluons at small-$x$ inside an unpolarized hadron can be regarded as Bell states in which qubits in the spin and orbital angular momentum spaces are maximally entangled. Using the machinery of quantum information science, we generalize this observation to all values $0<x<1$ and describe gluons (but not quarks) as maximally entangled stat

Tobias Buck, Christian Schwarz

Recently, contrastive learning (CL), a technique most prominently used in natural language and computer vision, has been used to train informative representation spaces for galaxy spectra and images in a self-supervised manner. Following this idea, we implement CL for stars in the Milky Way, for which recent astronomical surveys have produced a huge amount o

Junjie Huang, Jiarui Qin, Jianghao Lin, Ziming Feng

Recommender systems (RS) are pivotal in managing information overload in modern digital services. A key challenge in RS is efficiently processing vast item pools to deliver highly personalized recommendations under strict latency constraints. Multi-stage cascade ranking addresses this by employing computationally efficient retrieval methods to cover diverse

Sasan Razmkhah, Jui-Yu Huang, Mehdi Kamal, Massoud Pedram

This paper presents a CMOS-compatible Lechner-Hauke-Zoller (LHZ)--based analog tile structure as a fundamental unit for developing scalable analog Ising machines (IMs). In the designed LHZ tile, the voltage-controlled oscillators are employed as the physical Ising spins, while for the ancillary spins, we introduce an oscillator-based circuit to emulate the c

Man-Yu Duan, Wen-Tao Lyu, Chu-Wen Xiao, En Wang

We study from the theoretical point of view the $\Lambda_c^+\to \pi^+ \eta \Lambda$ reaction, recently measured by the Belle and BESIII Collaborations, where clear signals are observed for $a_0(980)$, $\Lambda(1670)$, and $\Sigma(1385)$ excitation. By considering the $a_0(980)$ and $\Lambda(1670)$ as dynamically generated resonances from the meson meson and

Zhenpeng Su, Xing Wu, Zijia Lin, Yizhe Xiong

Large language models (LLM) have been attracting much attention from the community recently, due to their remarkable performance in all kinds of downstream tasks. According to the well-known scaling law, scaling up a dense LLM enhances its capabilities, but also significantly increases the computational complexity. Mixture-of-Experts (MoE) models address tha

Lasse Fischer, Aaditya Ramdas

Wald's sequential probability ratio test (SPRT) is a cornerstone of sequential analysis. Based on desired type-I, II error levels $\alpha, \beta$, it stops when the likelihood ratio crosses certain thresholds, guaranteeing optimality of the expected sample size. However, these thresholds are not closed form and the test is often applied with approximate thre

Alix Deruelle, Tristan Ozuch

In stark contrast to lower dimensions, we produce a plethora of ancient and immortal Ricci flows in real dimension $4$ with Einstein orbifolds as tangent flows at infinity. For instance, for any $k\in\mathbb{N}_0$, we obtain continuous families of non-isometric ancient Ricci flows on $\#k(\mathbb{S}^2\times \mathbb{S}^2)$ depending on a number of parameters

Zsolt Páles, Amr Zakaria

In this paper we consider the equality problem of generalized Bajraktarevi\'c means, i.e., we are going to solve the functional equation \begin{equation}\label{E0}\tag{*} f^{(-1)}\bigg(\frac{p_1(x_1)f(x_1)+\dots+p_n(x_n)f(x_n)}{p_1(x_1)+\dots+p_n(x_n)}\bigg)=g^{(-1)}\bigg(\frac{q_1(x_1)g(x_1)+\dots+q_n(x_n)g(x_n)}{q_1(x_1)+\dots+q_n(x_n)}\bigg), \end{equatio

Matteo Vilucchio, Nikolaos Tsilivis, Bruno Loureiro, Julia Kempe

Regularization, whether explicit in terms of a penalty in the loss or implicit in the choice of algorithm, is a cornerstone of modern machine learning. Indeed, controlling the complexity of the model class is particularly important when data is scarce, noisy or contaminated, as it translates a statistical belief on the underlying structure of the data. This

Nemanja Draganić, Michael Krivelevich

A connected dominating set (CDS) in a graph is a dominating set of vertices that induces a connected subgraph. Having many disjoint CDSs in a graph can be considered as a measure of its connectivity, and has various graph-theoretic and algorithmic implications. We show that $d$-regular (weakly) pseudoreandom graphs contain $(1+o(1))d/\ln d$ disjoint CDSs, wh

Alejandro Hnilo

Quantum non-locality has become a popular term. Yet, its precise meaning, and even its mere existence, is the subject of controversies. The main cause of the controversies is the never ending discussion on the appropriate definitions of Locality and Realism in the derivation of Bell's inequalities. On the other hand, Louis Sica derived Bell's inequalities fr

David Kahle, Jonathan D Hauenstein

Nonlinear systems of polynomial equations arise naturally in many applied settings, for example loglinear models on contingency tables and Gaussian graphical models. The solution sets to these systems over the reals are often positive dimensional spaces that in general may be very complicated yet have very nice local behavior almost everywhere. Standard meth

Jeremy Stephen Gabriel Yee, Pai Chet Ng, Zhengkui Wang, Ian McLoughlin

This paper presents a systematic review of the infrastructure requirements for deploying Large Language Models (LLMs) on-device within the context of small and medium-sized enterprises (SMEs), focusing on both hardware and software perspectives. From the hardware viewpoint, we discuss the utilization of processing units like GPUs and TPUs, efficient memory a

Maggie Mi, Aline Villavicencio, Nafise Sadat Moosavi

Human processing of idioms relies on understanding the contextual sentences in which idioms occur, as well as language-intrinsic features such as frequency and speaker-intrinsic factors like familiarity. While LLMs have shown high performance on idiomaticity detection tasks, this success may be attributed to reasoning shortcuts in existing datasets. To this

F. Latifian, G. Rastegarzadeh

SURA is a self-triggered radio array on the roof of physics faculty at Semnan university in Iran. It is designed to detect radio emissions from air showers produced by ultra-high energy (UHE) cosmic rays with energies exceeding 1017 eV. The array consists of 4 LPDA radio antennas operating in the 40 MHz to 80 MHz range. In this study, we present a method tha

Jingxian Li, Andrew J. Jalbert, Leah S. Simakas, Noah J. Geisler

CMOS-based microelectronics are limited to ~150{\deg}C and therefore not suitable for the extreme high temperatures in aerospace, energy, and space applications. While wide bandgap semiconductors can provide high-temperature logic, nonvolatile memory devices at high temperatures have been challenging. In this work, we develop a nonvolatile electrochemical me

Mohammed Al-Fahdi, Riccardo Rurali, Jianjun Hu, Christopher Wolverton

Designing materials with targeted lattice thermal conductivity (LTC) demands electronic-level insight into chemical bonding. We introduce two bonding descriptors, namely normalized negative integrated crystal orbital Hamilton populations (-ICOHP) and normalized integrated crystal orbital bond index (ICOBI), that strongly correlate with LTC and rattling (mean

Yu-Xuan Chen, Lei Lei, Zi-Qing Xia, Ziwei Wang

We investigate the production of axion-like particles (ALPs) in stellar cores, where they interact with electromagnetic fields and electrons, with typical masses between $\mathcal O(0.1)$ and $\mathcal O(10)$ keV. These low-energy ALPs are gravitationally trapped in the orbits of stars and subsequently decay into two photons that we detect as monochromatic X

Tomas F. D. Silva, Giovanni Bussi

RNA molecules exhibit various biological functions intrinsically dependent on their diverse ecosystem of highly flexible structures. This flexibility arises from complex hydrogen-bonding networks defined by canonical and non-canonical base pairs that require protonation events to stabilize or perturb these interactions. Constant pH molecular dynamics (CpHMD)

Ruting Chi, Zhiyi Huang, Yuexing Han

Small sample instance segmentation is a very challenging task, and many existing methods follow the training strategy of meta-learning which pre-train models on support set and fine-tune on query set. The pre-training phase, which is highly task related, requires a significant amount of additional training time and the selection of datasets with close proxim

Eleftheria Tsipidi, Franz Nowak, Ryan Cotterell, Ethan Wilcox

The Uniform Information Density (UID) hypothesis posits that speakers tend to distribute information evenly across linguistic units to achieve efficient communication. Of course, information rate in texts and discourses is not perfectly uniform. While these fluctuations can be viewed as theoretically uninteresting noise on top of a uniform target, another ex

Patrick Erik Bradley, Angel Alfredo Moran Ledezma

Motivated by multi-topology building and city model data, first a lossless representation of multiple $T_0$-topologies on a given finite set by a vertex-edge-weighted graph is given, and the subdominant ultrametric of the associated weighted graph distance matrix is proposed as an index structure for these data. This is applied in a heuristic parallel topolo

Ryan P. McMahan, Nayan N. Chawla, Christian S. Cassell, Christopher Peerapon Lee

Research involving virtual reality (VR) has dramatically increased since the introduction of consumer VR systems. In turn, research on VR games has gained popularity within several fields. However, most VR games are closed source, which limits research opportunities. Some VR games are open source, but most of them are either very basic or too complex to be e

Pramodh Senarath Yapa, Thomas Bland

Dipolar supersolids--quantum states that are simultaneously superfluid and solid--have had their superfluid nature rigorously tested, while their solid nature remain uncharted. Arguably, the defining characteristic of a solid is the existence of elastic shear waves. In this work we investigate transverse wave packet propagation in dipolar supersolids with tr

Ke Zhang, Junjie Li, Shuai Wang, Yangjie Wei

Target speaker extraction (TSE) relies on a reference cue of the target to extract the target speech from a speech mixture. While a speaker embedding is commonly used as the reference cue, such embedding pre-trained with a large number of speakers may suffer from confusion of speaker identity. In this work, we propose a multi-level speaker representation app

Zhilong Chen, Peijie Liu, Jinghua Piao, Fengli Xu

The emerging short-form video platforms have been growing tremendously and become one of the leading social media recently. Although the expanded popularity of these platforms has attracted increasing research attention, there has been a lack of understanding of whether and how they deviate from traditional long-form video-sharing platforms such as YouTube a

Ming Li, Wei Shen, Qingli Li, Yan Wang

The success of medical image segmentation usually requires a large number of high-quality labels. But since the labeling process is usually affected by the raters' varying skill levels and characteristics, the estimated masks provided by different raters usually suffer from high inter-rater variability. In this paper, we propose a simple yet effective Label

Siyuan Chen, Chengming Bai

The notions of the Novikov deformation of a commutative associative algebra and the corresponding classical limit are introduced. We show such a classical limit belongs to a subclass of transposed Poisson algebras, and hence the Novikov deformation is defined to be the quantization of the corresponding transposed Poisson algebra. As a direct consequence, we

Yanan Hu, Chengli Li, Feng Liu

Thomassen's chord conjecture from 1976 states that every longest cycle in a $3$-connected graph has a chord. The circumference $c(G)$ and induced circumference $c'(G)$ of a graph $G$ are the length of its longest cycles and the length of its longest chordless cycles, respectively. In $2017$, Harvey proposed a stronger conjecture: Every $2$-connected graph $G

Pengcheng Li, Jianzhong Pan, Jie Wu

Let $M$ be a closed orientable $(n-1)$-connected $(2n+2)$-manifold, $n\geq 2$. In this paper we combine the Postnikov tower of spheres and the homotopy decomposition of the reduced suspension space $\Sigma M$ to investigate the cohomotopy sets $\pi^\ast(M)$ for $n=2,3,4$, under the assumption that $M$ has $2$-torsion-free homology. All cohomotopy sets $\pi^i

Dario Benedetti, Razvan Gurau, Sabine Harribey

We correct the computation of one Feynman diagram in the three-loop beta functions for the long-range quartic multi-scalar model, originally presented in (2020 J. Phys. A: Math. Theor. 53 445008) [arXiv:2007.04603]. The correction requires the use of a different method than in the original paper, and we give here full details about the method. We then report

Khai Ton That, Chang Xu, Ioannis Ioannidis, Lucas Schneider

Probing spatially confined quantum states from afar - a long-sought goal to minimize external interference - has been proposed to be achievable in condensed matter systems via coherent projection. The latter can be tailored by sculpturing the eigenstates of the electron sea that surrounds the quantum state using atom-by-atom built cages, so-called quantum co

Anna Trindade Falcão, S. B. Kraemer, T. C. Fischer, H. R. Schmitt

We use the Hubble Space Telescope to analyse the extended [O III] 5007A emission in seven bright radio-quiet type 1 quasars (QSO1s), focusing on the morphology and physical conditions of their extended Narrow-Line Regions (NLRs). We find NLRs extending 3-9 kpc, with four quasars showing roughly symmetrical structures (b/a=1.2-1.5) and three displaying asymme

Shogo Iwazaki, Shion Takeno

This paper studies a non-stationary kernelized bandit (KB) problem, also called time-varying Bayesian optimization, where one seeks to minimize the regret under an unknown reward function that varies over time. In particular, we focus on a near-optimal algorithm whose regret upper bound matches the regret lower bound. For this goal, we show the first algorit

Ishan Arora, Srashti Dwivedi, Amitabha Tripathi

Let $a_1,\ldots,a_m$ be nonzero integers, $c \in \mathbb Z$ and $r \ge 2$. The Rado number for the equation \[ \sum_{i=1}^m a_ix_i = c \] in $r$ colours is the least positive integer $N$ such that any $r$-colouring of the integers in the interval $[1,N]$ admits a monochromatic solution to the given equation. We introduce the concept of $t$-distributability o

Sören Bartels, Giuseppe Buttazzo, Hedwig Keller

An eigenvalue problem arising in optimal insulation related to the minimization of the heat decay rate of an insulated body is adapted to enforce a positive lower bound imposed on the distribution of insulating material. We prove the existence of optimal domains among a class of convex shapes and propose a numerical scheme to approximate the eigenvalue. The

Raphina Liu, Sofia Bobadilla, Benoit Baudry, Martin Monperrus

Using open-source dependencies is essential in modern software development. However, this practice implies significant trust in third-party code, while there is little support for developers to assess this trust. As a consequence, attacks have been increasingly occurring through third-party dependencies. These are called software supply chain attacks. In thi

Arnon Turetzky, Avihu Dekel, Nimrod Shabtay, Slava Shechtman

We present SALAD, a zero-shot TTS autoregressive model operating over continuous speech representations. SALAD utilizes a per-token diffusion process to refine and predict continuous representations for the next time step. We compare our approach against a discrete variant of SALAD as well as publicly available zero-shot TTS systems, and conduct a comprehens

Antoine Galet

A field $K$ is quasi-classical $d$-local if there exist fields $K=k_d,\dots,k_0$ with $k_{i+1}$ Henselian admissible discretely valued with residue field $k_i$, and $k_0$ quasi-finite. We prove a duality theorem for the Galois cohomology of such $K$ with many coefficients, including finite coefficients of any order. Previously, such duality was only known in

Julian Kupka, Charles Strickland-Constable, Fridrich Valach

It has been known for some time that generalised geometry provides a particularly elegant rewriting of the action and symmetries of 10-dimensional supergravity theories, up to the lowest nontrivial order in fermions. By exhibiting the full symmetry calculations in the second-order formalism, we show in the $\mathcal N=1$ case that this analysis can be upgrad

Felix Divo, Eric Endress, Kevin Endler, Kristian Kersting

Company fundamentals are key to assessing companies' financial and overall success and stability. Forecasting them is important in multiple fields, including investing and econometrics. While statistical and contemporary machine learning methods have been applied to many time series tasks, there is a lack of comparison of these approaches on this particularl

Nicola Losacco

The Belle Collaboration has measured the complete set of angular coefficient functions for the decays ${\bar B} \to D^*\,(D\,\pi)\,\ell\,{\bar \nu}_{\ell}$, where $\ell = e,\,\mu$, in four bins of the variable $w={m_B^2+m_{D^*}^2-q^2 \over 2\, m_B\, m_{D^*}}$, with $q$ the momentum of the lepton pair. In SM this measurement is instrumental in determining the

Muhammad Umair, Vasanth Sarathy, JP de Ruiter

Turn-taking is a fundamental mechanism in human communication that ensures smooth and coherent verbal interactions. Recent advances in Large Language Models (LLMs) have motivated their use in improving the turn-taking capabilities of Spoken Dialogue Systems (SDS), such as their ability to respond at appropriate times. However, existing models often struggle

Timo Schorlepp, Ohad Shpielberg

Dynamical phase transitions are nonequilibrium counterparts of thermodynamic phase transitions and share many similarities with their equilibrium analogs. In continuous phase transitions, critical exponents play a key role in characterizing the physics near criticality. This study aims to systematically analyze the set of possible critical exponents in weak

CTA-LST Project, :, K. Abe, S. Abe

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of experiments, in particular the Cherenkov Telescope Array Observatory (CTAO), sets ambitious goals for discoveries of new gam

Isaac L. Huidobro-Meezs, Jun Dai, Guillaume Rabusseau, Rodrigo A. Vargas-Hernández

Quantum computing presents a promising alternative for the direct simulation of quantum systems with the potential to explore chemical problems beyond the capabilities of classical methods. However, current quantum algorithms are constrained by hardware limitations and the increased number of measurements required to achieve chemical accuracy. To address the

Nikos Irges, Leonidas Karageorgos

We revisit the construction of the renormalized trace $\Theta$ of the Energy-Momentum tensor in the four-dimensional $\lambda\phi^4$ theory,using dimensional regularization in $d=4-\ve$ dimensions. We first construct several basic correlators such as $\braket{\phi^2 \phi\phi}$, $\braket{\phi^4 \phi \phi}$ to order $\lambda^2$ and from these the correlators $

Paxson Swierc, Marcos Tamargo-Arizmendi, Aleksandra Ćiprijanović, Brian D. Nord

Modeling strong gravitational lenses is prohibitively expensive for modern and next-generation cosmic survey data. Neural posterior estimation (NPE), a simulation-based inference (SBI) approach, has been studied as an avenue for efficient analysis of strong lensing data. However, NPE has not been demonstrated to perform well on out-of-domain target data -- e

Luigi Forcella, Vladimir Georgiev

We consider the two-dimensional nonlinear Schr\"odinger equation with point interaction and we establish a local well-posedness theory, including blow-up alternative and continuous dependence on the initial data in the energy space. We provide a proof by employing a Kato's method along with Hardy inequalities with logarithmic correction. Moreover, we establi

Jeaung Lee, Jeewoo Lim, Keunho Byeon, Jin Tae Kwak

In computational pathology, several foundation models have recently emerged and demonstrated enhanced learning capability for analyzing pathology images. However, adapting these models to various downstream tasks remains challenging, particularly when faced with datasets from different sources and acquisition conditions, as well as limited data availability.

Jiamin Cao, Lingqi Wang, Kexin Zhang, Yuting Yang

Road++ Track3 proposes a multi-label atomic activity recognition task in traffic scenarios, which can be standardized as a 64-class multi-label video action recognition task. In the multi-label atomic activity recognition task, the robustness of visual feature extraction remains a key challenge, which directly affects the model performance and generalization

Pavel Exner, David Spitzkopf

We consider a two-dimensional system in which a charged particle is exposed to a homogeneous magnetic field perpendicular to the plane and a potential that is translationally invariant in one dimension. We derive several conditions on such a perturbation under which the Landau levels change into an absolutely continuous spectrum.

S. N. Artekha

For analytical description of the initial stage of jet generation in nonequilibrium inhomogeneous plasma in the magnetohydrodynamic approximation, possible generalizations of solutions of the nonlinear equation for the stream function are analyzed. The jet generation model is based on the mechanism of convective instability and the frozen-in condition of mag

A. J. Uría-Álvarez, J. J. Palacios

Bismuth has been shown to be topological in its different allotropes and compounds, with one of the most notable examples being the Bi-Sb alloy, the first 3D topological insulator ever discovered. In this paper we explore two-dimensional alloys of Bi and Sb, both crystalline and amorphous, to determine the critical concentrations that render the alloys topol

Shiyu Wang, Jiawei Li, Xiaoming Shi, Zhou Ye

Time series analysis plays a critical role in numerous applications, supporting tasks such as forecasting, classification, anomaly detection, and imputation. In this work, we present the time series pattern machine (TSPM), a model designed to excel in a broad range of time series tasks through powerful representation and pattern extraction capabilities. Trad

Eleonora Lippi, Manuel Gerken, Stephan Häfner, Marc Repp

We present the experimental apparatus enabling the observation of the heteronuclear Efimov effect in an optically trapped ultracold mixture of $^6$Li-$^{133}$Cs with high-resolution control of the interactions. A compact double-species Zeeman slower consisting of four interleaving helical coils allows for a fast-switching between two optimized configurations

Samuel Hewson, Will J. Handley, Christopher G. Lester

We use machine learning methods to search for parity violations in the Large-Scale Structure (LSS) of the Universe, motivated by recent claims of chirality detection using the 4-Point Correlation Function (4PCF), which would suggest new physics during the epoch of inflation. This work seeks to reproduce these claims using methods originating from high energy

Arijit Das

Training LLMs presents significant memory challenges due to growing size of data, weights, and optimizer states. Techniques such as data and model parallelism, gradient checkpointing, and offloading strategies address this issue but are often infeasible due to hardware constraints. To mitigate memory usage, alternative methods like Parameter-Efficient-Fine-T

Ben Crulis, Barthelemy Serres, Cyril De Runz, Gilles Venturini

Current large open vision models could be useful for one and few-shot object recognition. Nevertheless, gradient-based re-training solutions are costly. On the other hand, open-vocabulary object detection models bring closer visual and textual concepts in the same latent space, allowing zero-shot detection via prompting at small computational cost. We propos

Sachin Kumar, Chan Young Park, Yulia Tsvetkov, Noah A. Smith

Conventional algorithms for training language models (LMs) with human feedback rely on preferences that are assumed to account for an "average" user, disregarding subjectivity and finer-grained variations. Recent studies have raised concerns that aggregating such diverse and often contradictory human feedback to finetune models results in generic models that

Thomas Pusztai, Cynthia Marcelino, Stefan Nastic

The number of Low Earth Orbit~(LEO) satellites has grown enormously in the past years. Their abundance and low orbits allow for low latency communication with a satellite almost anywhere on Earth, and high-speed inter-satellite laser links~(ISLs) enable a quick exchange of large amounts of data among satellites. As the computational capabilities of LEO satel

Giovanni Pittiglio, Abdulhamit Donder, Pierre E. Dupont

Shape sensing of medical continuum robots is important both for closed-loop control as well as for enabling the clinician to visualize the robot inside the body. There is a need for inexpensive, but accurate shape sensing technologies. This paper proposes the use of magnetic ball chains as a means of generating shape-specific magnetic fields that can be dete

Yue Deng, Weiyu Ma, Yuxin Fan, Ruyi Song

StarCraft Multi-Agent Challenge (SMAC) has been one of the most commonly used experimental environments in multi-agent reinforcement learning (MARL), where the specific task is to control a set number of allied units to defeat enemy forces. Traditional MARL algorithms often require interacting with the environment for millions of steps to train a parametric

Angelo Monti, Blerina Sinaimeri

A graph $G=(V,E)$ is defined as a star-$k$-PCG when it is possible to assign a positive real number weight $w$ to each vertex $V$, and define $k$ distinct intervals $I_1, I_2, \ldots I_k$, in such a way that there is an edge $uv$ in $E$ if and only if the sum of the weights of vertices $u$ and $v$ falls within the union of these intervals. The star-$k$-PCG c

Akshat Pandey, Subir Ghosh

In this work we apply Dirac's Constraint Analysis (DCA) to solve Superconducting Quantum Circuits (SQC). The Lagrangian of a SQC reveals the constraints, that are classified in a Hamiltonian framework, such that redundant variables can be removed to isolate the canonical degrees of freedom for subsequent quantization of the Dirac Brackets. We demonstrate the

G. Q. Garcia, P. J. Porfírio, C. Furtado, D. C. Moreira

In this work, we are interested in how spinning effects influence the electronic properties of the graphene wormhole. For this purpose, we have described the graphene by the wormhole background based on the model developed by Gonz\'alez and his co-workers. By applying a coordinate transformation in the metric of graphene wormhole, we can introduce rotating e

Victor Le Coz, Nolwenn Allaire, Michael Benzaquen, Damien Challet

Using the secured transactions recorded within the Money Markets Statistical Reporting database of the European Central Bank, we test several stylized facts regarding interbank market of the 47 largest banks in the eurozone. We observe that the surge in the volume of traded evergreen repurchase agreements followed the introduction of the LCR regulation and w

Jintao Guo, Lei Qi, Yinghuan Shi, Yang Gao

Domain Generalization (DG) aims to enable models to generalize to unseen target domains by learning from multiple source domains. Existing DG methods primarily rely on convolutional neural networks (CNNs), which inherently learn texture biases due to their limited receptive fields, making them prone to overfitting source domains. While some works have introd

Sélim Ollivier, Yann Gousseau, Sidonie Lefebvre

State-of-the-art RGB texture synthesis algorithms rely on style distances that are computed through statistics of deep features. These deep features are extracted by classification neural networks that have been trained on large datasets of RGB images. Extending such synthesis methods to multispectral images is not straightforward, since the pre-trained netw

Damien Hutsemékers, Dominique Sluse, Đorđe Savić

MgII or H$\alpha$ line profile distortions observed in five gravitationally lensed quasars have been compared with simulated ones. The simulations are based on three BLR models, a Keplerian disk (KD), an equatorial wind (EW), and a polar wind (PW). We find that the wide variety of observed line profile distortions can be reproduced with microlensing-induced

Christopher D. Walker

I propose a semiparametric Bayesian inference framework for conditional moment equalities. The core idea is that these models deterministically map a conditional distribution of data to a structural parameter via the restriction that a conditional expectation equals zero. Consequently, a posterior for the conditional distribution leads to a posterior for the

Yinghui Wang, Yilong Ren, Zhiyong Cui, Haiyang Yu

Cybersecurity has become a crucial concern in the field of connected autonomous vehicles. Cyber threat intelligence (CTI), as the collection of cyber threat information, offers an ideal way for responding to emerging cyber threats and realizing proactive security defense. However, instant analysis and modeling of vehicle cybersecurity data is a fundamental c

Jacob Armstrong-Goodall, Yvain Bruned

We introduce a class of symplectic resonance based schemes for Schr\"odinger's equation in dimension one, building on the work in [1] wherein resonance based numerical schemes were developed in the context of dispersive PDE driven by time dependent, or space-time dependent, coloured noise. We work primarily with a cubic nonlinearity, advancing the approach i