July 2023 arXiv papers — page 98

Xin Li, Zhiwen Deng, Rui Feng, Ziyang Liu

Artificial intelligence-based three-dimensional(3D) fluid modeling has gained significant attention in recent years. However, the accuracy of such models is often limited by the processing of irregular flow data. In order to bolster the credibility of near-wall flow prediction, this paper presents a deep learning-based reduced order model for three-dimension

Mark Turner, Timo Berthold, Mathieu Besançon

The current cut selection algorithm used in mixed-integer programming solvers has remained largely unchanged since its creation. In this paper, we propose a set of new cut scoring measures, cut filtering techniques, and stopping criteria, extending the current state-of-the-art algorithm and obtaining a 5\% performance improvement for SCIP over the MIPLIB 201

Mufang Ying, Koulik Khamaru, Cun-Hui Zhang

Sequential data collection has emerged as a widely adopted technique for enhancing the efficiency of data gathering processes. Despite its advantages, such data collection mechanism often introduces complexities to the statistical inference procedure. For instance, the ordinary least squares (OLS) estimator in an adaptive linear regression model can exhibit

Jörg K. H. Franke, Frederic Runge, Frank Hutter

The field of RNA secondary structure prediction has made significant progress with the adoption of deep learning techniques. In this work, we present the RNAformer, a lean deep learning model using axial attention and recycling in the latent space. We gain performance improvements by designing the architecture for modeling the adjacency matrix directly in th

Yuyang Du, Hongyu Deng, Soung Chang Liew, Kexin Chen

Large language models (LLMs) have garnered significant attention across various research disciplines, including the wireless communication community. There have been several heated discussions on the intersection of LLMs and wireless technologies. While recent studies have demonstrated the ability of LLMs to generate hardware description language (HDL) code

Yi Huang, Ziyang Meng, Jian Sun, Wei Ren

This paper develops a unified distributed method for solving two classes of constrained networked optimization problems, i.e., optimal consensus problem and resource allocation problem with non-identical set constraints. We first transform these two constrained networked optimization problems into a unified saddle-point problem framework with set constraints

Cedric Waterschoot, Antal van den Bosch

Online news outlets are grappling with the moderation of user-generated content within their comment section. We present a recommender system based on ranking class probabilities to support and empower the moderator in choosing featured posts, a time-consuming task. By combining user and textual content features we obtain an optimal classification F1-score o

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We study the process $e^{+}e^{-}\to\Lambda_{c}^{+}\bar{\Lambda}_c^{-}$ at twelve center-of-mass energies from $4.6119$ to $4.9509~\mathrm{GeV}$ using data samples collected by the BESIII detector at the BEPCII collider. The Born cross sections and effective form factors ($|G_{\mathrm{eff}}|$) are determined with unprecedented precision after combining the si

Sylwia Cichacz, Agieszka Görlich, Karol Suchan

We study the problem of finding a minimum $k$-critical-bipartite graph of order $(n,m)$: a bipartite graph $G=(U,V;E)$, with $|U|=n$, $|V|=m$, and $n>m>1$, which is $k$-critical-bipartite, and the tuple $(|E|, \Delta_U, \Delta_V)$, where $\Delta_U$ and $\Delta_V$ denote the maximum degree in $U$ and $V$, respectively, is lexicographically minimum over all su

Lutz Klinkenberg, Christian Blumenthal, Mingshuai Chen, Darion Haase

We present an exact Bayesian inference method for inferring posterior distributions encoded by probabilistic programs featuring possibly unbounded loops. Our method is built on a denotational semantics represented by probability generating functions, which resolves semantic intricacies induced by intertwining discrete probabilistic loops with conditioning (f

Oscar Carlsson, Jan E. Gerken, Hampus Linander, Heiner Spieß

High-resolution wide-angle fisheye images are becoming more and more important for robotics applications such as autonomous driving. However, using ordinary convolutional neural networks or vision transformers on this data is problematic due to projection and distortion losses introduced when projecting to a rectangular grid on the plane. We introduce the HE

Agnes Axelsson, Gabriel Skantze

In any system that uses structured knowledge graph (KG) data as its underlying knowledge representation, KG-to-text generation is a useful tool for turning parts of the graph data into text that can be understood by humans. Recent work has shown that models that make use of pretraining on large amounts of text data can perform well on the KG-to-text task eve

Simon Blatt, Matteo Raffaelli

We apply the direct method of the calculus of variations to show that any nonplanar Frenet curve in $\mathbb{R}^{3}$ can be extended to an infinitely narrow flat ribbon having minimal bending energy. We also show that, in general, minimizers are not free of planar points, yet such points must be isolated under the mild condition that the torsion does not van

Maria Przybylska, Wojciech Szumiński, Andrzej J. Maciejewski

Relativistic Hamiltonian equations describing a motion of a point mass in an arbitrary homogeneous potential are considered. For the first time, the necessary integrability conditions for integrability in the Liouville sense for this class of systems are formulated. These conditions are obtained by means of an analysis of the differential Galois groups of va

Mohammad Javad Ahmadi, Mohammad Kazemi, Tolga M. Duman

We study the problem of unsourced random access (URA) over Rayleigh block-fading channels with a receiver equipped with multiple antennas. We propose a slotted structure with multiple stages of orthogonal pilots, each of which is randomly picked from a codebook. In the proposed signaling structure, each user encodes its message using a polar code and appends

Christian Bönicke

We investigate the dynamic asymptotic dimension for \'etale groupoids introduced by Guentner, Willett and Yu. In particular, we establish several permanence properties, including estimates for products and unions of groupoids. We also establish invariance of the dynamic asymptotic dimension under Morita equivalence. In the second part of the article, we cons

Geoffrey Exoo, Theodore Kolokolnikov, Jeanette Janssen, Timothy Salamon

We derive attainable upper bounds on the algebraic connectivity (spectral gap) of a regular graph in terms of its diameter and girth. This bound agrees with the well-known Alon-Boppana-Friedman bound for graphs of even diameter, but is an improvement for graphs of odd diameter. For the girth bound, we show that only Moore graphs can attain it, and these only

Marco Lewis, Paolo Zuliani, Sadegh Soudjani

Various techniques have been used in recent years for verifying quantum computers, that is, for determining whether a quantum computer/system satisfies a given formal specification of correctness. Barrier certificates are a recent novel concept developed for verifying properties of dynamical systems. In this article, we investigate the usage of barrier certi

Xuemei Dong, Chao Zhang, Yuhang Ge, Yuren Mao

This paper proposes a ChatGPT-based zero-shot Text-to-SQL method, dubbed C3, which achieves 82.3\% in terms of execution accuracy on the holdout test set of Spider and becomes the state-of-the-art zero-shot Text-to-SQL method on the Spider Challenge. C3 consists of three key components: Clear Prompting (CP), Calibration with Hints (CH), and Consistent Output

D. C. Moreira, A. S. Lemos, F. A. Brito

In this work we use a general covariance breaking method to obtain a class of topological charged black holes whose background geometry asymptotically approaches Lifshitz spacetimes. We discuss how this mechanism affects Einstein's equations and explore the thermodynamics and critical behavior of the solution found.

Hannaneh Akrami, Jugal Garg

We study the fundamental problem of fairly allocating a set of indivisible goods among $n$ agents with additive valuations using the desirable fairness notion of maximin share (MMS). MMS is the most popular share-based notion, in which an agent finds an allocation fair to her if she receives goods worth at least her MMS value. An allocation is called MMS if

Wen-Fong Ke, Hubert Kiechle

We investigate circular planar nearrings constructed from finite fields as well the complex number field using a multiplicative subgroup of order $k$, and characterize the overlaps of the basic graphs which arise in the associated $2$-designs.

Hubert Baty

In this paper, numerical methods using Physics-Informed Neural Networks (PINNs) are presented with the aim to solve higher-order ordinary differential equations (ODEs). Indeed, this deep-learning technique is successfully applied for solving different classes of singular ODEs, namely the well known second-order Lane-Emden equations, third order-order Emden-F

Lorenzo Piro, Andrej Vilfan, Ramin Golestanian, Benoît Mahault

We study the energetic efficiency of navigating microswimmers by explicitly taking into account the geometry of their body. We show that, as their shape transitions from prolate to oblate, non-steering microswimmers rotated by flow gradients naturally follow increasingly time-optimal trajectories. At the same time, they also require larger dissipation to swi

Witold Kosciukiewicz, Mateusz Wojcik, Tomasz Kajdanowicz, Adam Gonczarek

Document-level joint entity and relation extraction is a challenging information extraction problem that requires a unified approach where a single neural network performs four sub-tasks: mention detection, coreference resolution, entity classification, and relation extraction. Existing methods often utilize a sequential multi-task learning approach, in whic

Bjorn De Sutter, Sebastian Schrittwieser, Bart Coppens, Patrick Kochberger

Man-at-the-end (MATE) attackers have full control over the system on which the attacked software runs, and try to break the confidentiality or integrity of assets embedded in the software. Both companies and malware authors want to prevent such attacks. This has driven an arms race between attackers and defenders, resulting in a plethora of different protect

S. E. Pyatovsky

The comparative primary cosmic rays (PCR) comparative analysis by E0 and the spectra of variable stars by periods is carried out in order to establish the causes of irregularities in the spectrum of PCR by E0. The relationship between the periods of variable stars and the maximum energy E0 of the nuclei of PCRs generated by these types of stars is shown. Irr

Marcel Beetz, Yilong Yang, Abhirup Banerjee, Lei Li

Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases with associated clinical decision-making typically based on single-valued imaging biomarkers. However, such metrics only approximate the complex 3D structure and physiology of the heart and hence hinder a better understanding and prediction of MI outcomes. In this work, we invest

Dan Alistarh, Krishnendu Chatterjee, Mehrdad Karrabi, John Lazarsfeld

We initiate the study of game dynamics in the population protocol model: $n$ agents each maintain a current local strategy and interact in pairs uniformly at random. Upon each interaction, the agents play a two-person game and receive a payoff from an underlying utility function, and they can subsequently update their strategies according to a fixed local al

Kenji Leong

Active Simultaneous Localisation and Mapping (SLAM) is a critical problem in autonomous robotics, enabling robots to navigate to new regions while building an accurate model of their surroundings. Visual SLAM is a popular technique that uses virtual elements to enhance the experience. However, existing frontier-based exploration strategies can lead to a non-

Liam Lonergan, Mengjie Qian, Neasa Ní Chiaráin, Christer Gobl

ASR systems are generally built for the spoken 'standard', and their performance declines for non-standard dialects/varieties. This is a problem for a language like Irish, where there is no single spoken standard, but rather three major dialects: Ulster (Ul), Connacht (Co) and Munster (Mu). As a diagnostic to quantify the effect of the speaker's dialect on r

Elías Baro, Daniel Palacín

We introduce the Boolean algebra of d-semialgebraic (more generally, d-definable) sets and prove that its Stone space is naturally isomorphic to the Ellis enveloping semigroup of the Stone space of the Boolean algebra of semialgebraic (definable) sets. For definably connected o-minimal groups, we prove that this family agrees with the one of externally defin

Susmita Das, Ritaban Chatterjee

We study simultaneous soft ($0.7 - 7$ keV) and hard ($7 - 20$ keV) X-ray light curves at a total of eight epochs during $2016 - 2019$ of two TeV blazars Mrk 421 and 1ES 1959+650 observed by the SXT and LAXPC instruments onboard AstroSat. The light curves are $45 - 450$ ks long and may be sampled with time bins as short as $600 - 800$ sec with high signal to

Mohamed C. Ghanem, Maider D. Uribarri, Ramzi Djemai, Dipo Dunsin

Anti-forensics techniques particularly steganography and cryptography have become increasingly pressing issues that affect the current digital forensics practice. This paper advances the automation of hidden evidence extraction in the context of audio files by proposing a novel multi-approaches method which enables the correlation between unprocessed artefac

Nils Margenberg, Franz X. Kärtner, Markus Bause

We present an approach for solving optimal Dirichlet boundary control problems of nonlinear optics by using deep learning. For computing high resolution approximations of the solution to the nonlinear wave model, we propose higher order space-time finite element methods in combination with collocation techniques. Thereby, $C^{l}$-regularity in time of the gl

Martine Schut, Alexey Grinin, Andrew Dana, Sougato Bose

To test the quantum nature of gravity in a lab requires witnessing the entanglement between the two test masses (nano-crystals) solely due to the gravitational interaction kept at a distance in a spatial superposition. The protocol is known as the quantum gravity-induced entanglement of masses (QGEM). One of the main backgrounds in the QGEM experiment is ele

Yuhao Huang, Gangrong Qu, Youran Ge

Video Compressed Sensing (VCS) aims to reconstruct multiple frames from one single captured measurement, thus achieving high-speed scene recording with a low-frame-rate sensor. Although there have been impressive advances in VCS recently, those state-of-the-art (SOTA) methods also significantly increase model complexity and suffer from poor generality and ro

Noam Goldberg, Ishy Zagdoun

We derive a closed-form expression for the projection onto a capped rotated second-order cone -- a convex set that arises in perspective relaxations of nonlinear programs with binary indicator variables. The closed-form solution involves three distinct cases, one of which reduces to the classical projection onto a second-order cone. The remaining two cases y

Ignas Juodžbalis, Christopher J. Conselice, Maitrayee Singh, Nathan Adams

We present an analysis of a sample of robust high redshift galaxies selected photometrically from the `blank' fields of the Prime Extragalactic Areas for Reionization Science (PEARLS) survey and Early Release Observations (ERO) data of the James Webb Space Telescope (JWST) with the aim of selecting candidate high redshift active galactic nuclei (AGN). Source

P. F. Wang, J. L. Han, J. Xu, C. Wang

Pulsar polarization profiles are very basic database for understanding the emission processes in pulsar magnetosphere. After careful polarization calibration of the 19-beam L-band receiver and verification of beam-offset observation results, we obtain polarization profiles of 682 pulsars from observations by the Five-hundred-meter Aperture Spherical radio Te

Marc Neu, Juergen Becker, Philipp Dorwarth, Torben Ferber

We present a design methodology that enables the semi-automatic generation of a hardware-accelerated graph building architectures for locally constrained graphs based on formally described detector definitions. In addition, we define a similarity measure in order to compare our locally constrained graph building approaches with commonly used k-nearest neighb

ShangQi Deng, RuoCheng Wu, Liang-Jian Deng, Ran Ran

Multispectral and Hyperspectral Image Fusion (MHIF) is a practical task that aims to fuse a high-resolution multispectral image (HR-MSI) and a low-resolution hyperspectral image (LR-HSI) of the same scene to obtain a high-resolution hyperspectral image (HR-HSI). Benefiting from powerful inductive bias capability, CNN-based methods have achieved great success

D. Akimov, P. An, C. Awe, P. S. Barbeau

Description of the data release 10.13139/OLCF/1969085 (https://doi.ccs.ornl.gov/ui/doi/426) from the measurements of the CsI[Na] response to low energy nuclear recoils by the COHERENT collaboration. The release corresponds to the results published in "D. Akimov et al 2022 JINST 17 P10034". We share the data in the form of raw ADC waveforms, provide benchmark

Vítězslav Kala, Lucien Šíma

We study ideal-simple commutative semirings and summarize the results giving their classification, in particular when they are finitely generated. In the principal case of (para)semifields, we then consider their minimal number of generators and show that it grows linearly with the depth of an associated rooted forest.

Siyuan Yang, Jun Liu, Shijian Lu, Er Meng Hwa

One-shot skeleton action recognition, which aims to learn a skeleton action recognition model with a single training sample, has attracted increasing interest due to the challenge of collecting and annotating large-scale skeleton action data. However, most existing studies match skeleton sequences by comparing their feature vectors directly which neglects sp

Tianlin Zhang, Sikai Guo, Xiaogang Xiong, Wanlei Li

Exactly estimating and tracking the motion of surrounding dynamic objects is one of important tasks for the autonomy of a quadruped manipulator. However, with only an onboard RGB camera, it is still a challenging work for a quadruped manipulator to track the motion of a dynamic object moving with unknown and changing velocities. To address this problem, this

Ivan Kolář, Tomáš Málek

We explicitly demonstrate that the nonlocal ghost-free ultraviolet modification of general relativity (GR) known as the infinite derivative gravity (IDG) resolves nonscalar curvature singularities in exact solutions of the full theory. We analyze exact pp-wave solutions of GR and IDG describing gravitational waves generated by null radiation. Curvature of GR

Elisabet Burjons, Fabian Frei, Matthias Gehnen, Henri Lotze

We study the Feedback Vertex Set and the Vertex Cover problem in a natural variant of the classical online model that allows for delayed decisions and reservations. Both problems can be characterized by an obstruction set of subgraphs that the online graph needs to avoid. In the case of the Vertex Cover problem, the obstruction set consists of an edge (i.e.,

Alberto Domínguez Corella, Nicolai Jork, Šarká Nečasová, John Sebastian H. Simon

This paper focuses on the stability of solutions for a velocity-tracking problem associated with the two-dimensional Navier-Stokes equations. The considered optimal control problem does not possess any regularizer in the cost, and hence bang-bang solutions can be expected. We investigate perturbations that account for uncertainty in the tracking data and the

Martin von Helversen, Lara Greten, Imad Limame, Chin-Wen Shih

In recent years, much research has been undertaken to investigate the suitability of two-dimensional materials to act as single-photon sources with high optical and quantum optical quality. Amongst them, transition-metal dichalcogenides, especially WSe$_{2}$, have been one of the subjects of intensive studies. Yet, their single-photon purity and photon indis

Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek, Grzegorz Czelusta

Support vector machines (SVMs) are a well-established classifier effectively deployed in an array of pattern recognition and classification tasks. In this work, we consider extending classic SVMs with quantum kernels and applying them to satellite data analysis. The design and implementation of SVMs with quantum kernels (hybrid SVMs) is presented. It consist

Theresa Pekarek Rosin, Stefan Wermter

While Automatic Speech Recognition (ASR) models have shown significant advances with the introduction of unsupervised or self-supervised training techniques, these improvements are still only limited to a subsection of languages and speakers. Transfer learning enables the adaptation of large-scale multilingual models to not only low-resource languages but al

Robert Scheffler

Graph searches and their respective search trees are widely used in algorithmic graph theory. The problem whether a given spanning tree can be a graph search tree has been considered for different searches, graph classes and search tree paradigms. Similarly, the question whether a particular vertex can be visited last by some search has been studied extensiv

Daoqiang Liu

In this paper, we prove the long neck principle, band width estimates, and width inequalities of the geodesic collar neighborhoods of the boundary in the setting of general initial data sets for the Einstein equations, subject to certain energy conditions corresponding to the lower bounds of scalar curvature on Riemannian manifolds. Our results are establish

Pranava Madhyastha, Ye Zhang, Gabriella Vigliocco

We report a controlled study investigating the effect of visual information (i.e., seeing the speaker) on spoken language comprehension. We compare the ERP signature (N400) associated with each word in audio-only and audio-visual presentations of the same verbal stimuli. We assess the extent to which surprisal measures (which quantify the predictability of w

Miguel Palencia-Olivar

The age of social media has opened new opportunities for businesses. This flourishing wealth of information is outside traditional channels and frameworks of classical marketing research, including that of Marketing Mix Modeling (MMM). Textual data, in particular, poses many challenges that data analysis practitioners must tackle. Social media constitute mas

Liam Rogel, Ulrich Thiel

In 2015, Lusztig [Bull. Inst. Math. Acad. Sin. (N.S.)10(2015), no.1, 1-72] showed that for a connected reductive group over an algebraic closure of a finite field the associated (geometric) Hecke category admits a truncation in a two-sided Kazhdan--Lusztig cell, making it a categorification of the asymptotic algebra (J-ring), and that the categorical center

Abdul Hameed, Mikhail Tyaglov

The set $S_{\{i,j\}_{n}^{m}}=\{0,1,2,\ldots,m-1,m,m,m+1,\ldots,n-1,n\}\setminus\{i,j\},\quad 0<i<j\leqslant n$, is called Laplacian realizable if there exists a simple connected graph $G$ whose Laplacian spectrum is $S_{\{i,j\}_{n}^{m}}$. In this case, the graph $G$ is said to realize $S_{\{i,j\}_{n}^{m}}$. In this paper, we completely describe graphs realiz

Radek Cibulka

Ioffe's criterion and various reformulations of it have become a~standard tool in proving theorems guaranteeing various regularity properties such as metric regularity, i.e., the openness with a linear rate around the reference point, of a~(set-valued) mapping. We derive an analogue of it guaranteeing the almost openness with a linear rate of mappings acting

Richárd Simon, Dániel Virosztek

In one of his recent papers \cite{ML1}, Moln\'ar showed that if $\mathcal{A}$ is a von Neumann algebra without $I_1, I_2$-type direct summands, then any function from the positive definite cone of $\mathcal{A}$ to the positive real numbers preserving the Kubo-Ando power mean for some $0 \neq p \in (-1,1)$ is necessarily constant. It was shown in that paper,

Patrick Nyadjo Fonga

By employing the assessment of the asymptotic size of various sums of G\'{a}l studied by La Bret\`eche and Tenenbaum, we provide an improvement on the recent result of A. Bondarenko, P. Darbar, M. V. Hagen, W. Heap, and K. Seip regarding the large values of the Dedekind zeta-function on the critical line. Specifically, let $d\geqslant 3$ be an integer and $A

Ying Chen, Chuangchuang Kang, Jiafeng Lü, Shizhuo Yu

In this paper, we study the Manin triples associated to $n$-Lie bialgebras. We introduce the concept of operad matrices for $n$-Lie bialgebras. In particular, by studying a special case of operad matrices, it leads to the notion of local cocycle $n$-Lie bialgebras. Furthermore, we establish a one-to-one correspondence between the double of $n$-Lie bialgebras

Vilhelm Agdur, Nina Kamčev, Fiona Skerman

We prove new lower bounds on the modularity of graphs. Specifically, the modularity of a graph $G$ with average degree $\bar d$ is $\Omega(\bar{d}^{-1/2})$, under some mild assumptions on the degree sequence of $G$. The lower bound $\Omega(\bar{d}^{-1/2})$ applies, for instance, to graphs with a power-law degree sequence or a near-regular degree sequence. It

Ni Zhao, Lulu Zhang, Yongbiao Yang, Jun He

This paper introduces a method for characterizing the current noise of commercial constant-current sources(CCSs) using a free-induction-decay(FID) type optically-pumped rubidium atomic magnetometer driven by a radio-frequency(RF) magnetic field. We convert the sensitivity of the atomic magnetometer into the current noise of CCS by calibrating the coil consta

Asif Hanif, Muzammal Naseer, Salman Khan, Mubarak Shah

It is imperative to ensure the robustness of deep learning models in critical applications such as, healthcare. While recent advances in deep learning have improved the performance of volumetric medical image segmentation models, these models cannot be deployed for real-world applications immediately due to their vulnerability to adversarial attacks. We pres

Venkatraman Renganathan, Andrea Iannelli, Anders Rantzer

We present an online learning analysis of minimax adaptive control for the case where the uncertainty includes a finite set of linear dynamical systems. Precisely, for each system inside the uncertainty set, we define the model-based regret by comparing the state and input trajectories from the minimax adaptive controller against that of an optimal controlle

Ruben Becker, Davide Cenzato, Sung-Hwan Kim, Bojana Kodric

Wheeler automata were introduced in 2017 as a tool to generalize existing indexing and compression techniques based on the Burrows-Wheeler transform. Intuitively, an automaton is said to be Wheeler if there exists a total order on its states reflecting the co-lexicographic order of the strings labeling the automaton's paths; this property makes it possible t

Ramon Antoine, Pere Ara, Joan Bosa, Francesc Perera

For any ring $R$, we introduce an invariant in the form of a partially ordered abelian semigroup $\mathrm{S}(R)$ built from an equivalence relation on the class of countably generated projective modules. We call $\mathrm{S}(R)$ the Cuntz semigroup of the ring $R$. This construction is akin to the manufacture of the Cuntz semigroup of a C*-algebra using count

Kin Wai Lau, Yasar Abbas Ur Rehman, Yuyang Xie, Lan Ma

This report presents the technical details of our submission to the 2023 Epic-Kitchen EPIC-SOUNDS Audio-Based Interaction Recognition Challenge. The task is to learn the mapping from audio samples to their corresponding action labels. To achieve this goal, we propose a simple yet effective single-stream CNN-based architecture called AudioInceptionNeXt that o

Houshuang Chen, Yuchen He, Chihao Zhang

Learning with expert advice and multi-armed bandit are two classic online decision problems which differ on how the information is observed in each round of the game. We study a family of problems interpolating the two. For a vector $\mathbf{m}=(m_1,\dots,m_K)\in \mathbb{N}^K$, an instance of $\mathbf{m}$-MAB indicates that the arms are partitioned into $K$

M. -N. Célérier

In a recent series of papers new exact analytical solutions of Einstein equations representing interior spacetimes sourced by stationary rigidly rotating cylinders of fluids have been displayed. We have first considered a fluid with an axially directed pressure C\'el\'erier, Phys. Rev. D 104, 064040 (2021), J. Math. Phys. 64, 032501 (2023), then a perfect fl

Haris Jabbar

Tokenization is a critical part of modern NLP pipelines. However, contemporary tokenizers for Large Language Models are based on statistical analysis of text corpora, without much consideration to the linguistic features. I propose a linguistically motivated tokenization scheme, MorphPiece, which is based partly on morphological segmentation of the underlyin

A. Gibbs, D. P. Hewett, D. Huybrechs

Steepest descent methods combining complex contour deformation with numerical quadrature provide an efficient and accurate approach for the evaluation of highly oscillatory integrals. However, unless the phase function governing the oscillation is particularly simple, their application requires a significant amount of a priori analysis and expert user input,

Qingwen Zhang, Daniel Duberg, Ruoyu Geng, Mingkai Jia

In the field of robotics, the point cloud has become an essential map representation. From the perspective of downstream tasks like localization and global path planning, points corresponding to dynamic objects will adversely affect their performance. Existing methods for removing dynamic points in point clouds often lack clarity in comparative evaluations a

Lyne Moser, Nima Rasekh, Martina Rovelli

We provide an $(\infty,n)$-categorical version of the straightening-unstraightening construction, asserting an equivalence between the $(\infty,n)$-category of double $(\infty,n-1)$-right fibrations over an $(\infty,n)$-category $\mathcal{C}$ and that of the $(\infty,n)$-functors from $\mathcal{C}$ valued in $(\infty,n-1)$-categories. We realize this in the

Qian Chen, Wen Wang, Qinglin Zhang, Chong Deng

Transformer-based pre-trained language models, such as BERT, achieve great success in various natural language understanding tasks. Prior research found that BERT captures a rich hierarchy of linguistic information at different layers. However, the vanilla BERT uses the same self-attention mechanism for each layer to model the different contextual features.

Giuseppe Barbaro

We compute the (1,1)-Aeppli cohomology of compact simply-connected Lie groups. From this, we deduce that the Bismut flat metrics on the compact Bismut flat manifolds with finite fundamental group are globally stable for the pluriclosed flow. This prevents the existence of non-flat homogeneous Bismut Hermitian Einstein (hence also pluriclosed Calabi--Yau with

Paola Mannucci, Claudio Marchi, Cristian Mendico

The existence and the uniqueness of solutions to some semilinear parabolic equations on homogeneous Lie groups, namely, the Fokker-Planck equation and the Hamilton-Jacobi equation, are addressed. The anisotropic geometry of the state space plays a crucial role in our analysis and creates several issues that need to be overcome. Indeed, the ellipticity direct

Volker Karle, Mikhail Lemeshko

The impulsive limit (the "sudden approximation") has been widely employed to describe the interaction between molecules and short, far-off-resonant laser pulses. This approximation assumes that the timescale of the laser--molecule interaction is significantly shorter than the internal rotational period of the molecule, resulting in the rotational motion bein

Shivani Kumar, Sumit Bhatia, Milan Aggarwal, Tanmoy Chakraborty

Sharing ideas through communication with peers is the primary mode of human interaction. Consequently, extensive research has been conducted in the area of conversational AI, leading to an increase in the availability and diversity of conversational tasks, datasets, and methods. However, with numerous tasks being explored simultaneously, the current landscap

Silvia D. Almeida, Carsten T. Lüth, Tobias Norajitra, Tassilo Wald

Classification of heterogeneous diseases is challenging due to their complexity, variability of symptoms and imaging findings. Chronic Obstructive Pulmonary Disease (COPD) is a prime example, being underdiagnosed despite being the third leading cause of death. Its sparse, diffuse and heterogeneous appearance on computed tomography challenges supervised binar

Udo Schlegel, Daniela Oelke, Daniel A. Keim, Mennatallah El-Assady

With the rising necessity of explainable artificial intelligence (XAI), we see an increase in task-dependent XAI methods on varying abstraction levels. XAI techniques on a global level explain model behavior and on a local level explain sample predictions. We propose a visual analytics workflow to support seamless transitions between global and local explana

Yu Wang, Shuai Dong, Xiaoyan Yao

With the field of two-dimensional (2D) magnetic materials expanding rapidly, noncollinear topological magnetic textures in 2D materials are attracting growing interest recently. As the in-plane counterpart of magnetic skyrmions, magnetic bimerons have the same topological advantages, but are rarely observed in experiments. Employing first-principles calculat

Shubham Sharma, Harleen Dahiya

In the light-front quark-diquark model (LFQDM), the higher twist generalized transverse momentum dependent distribution (GTMD) $F_{31}(x, {\bf p_\perp},{\bf \Delta_\perp})$ for the proton has been analyzed. We have derived the GTMD overlap equation by the analysis of GTMD correlator, employing the light-front wave functions in both the scalar and vector diqu

I. Arnquist, N. Avalos, D. Baxter, X. Bertou

Dark Matter (DM) particles with sufficiently large cross sections may scatter as they travel through Earth's bulk. The corresponding changes in the DM flux give rise to a characteristic daily modulation signal in detectors sensitive to DM-electron interactions. Here, we report results obtained from the first underground operation of the DAMIC-M prototype det

Byung-Kwan Lee, Junho Kim, Yong Man Ro

Adversarial examples derived from deliberately crafted perturbations on visual inputs can easily harm decision process of deep neural networks. To prevent potential threats, various adversarial training-based defense methods have grown rapidly and become a de facto standard approach for robustness. Despite recent competitive achievements, we observe that adv

50 Collaboration, P. Agnes, I. F. M. Albuquerque, T. Alexander

Dark matter induced event rate in an Earth-based detector is predicted to show an annual modulation as a result of the Earth's orbital motion around the Sun. We searched for this modulation signature using the ionization signal of the DarkSide-50 liquid argon time projection chamber. No significant signature compatible with dark matter is observed in the ele

Denis Antipov, Aneta Neumann, Frank Neumann

The evolutionary diversity optimization aims at finding a diverse set of solutions which satisfy some constraint on their fitness. In the context of multi-objective optimization this constraint can require solutions to be Pareto-optimal. In this paper we study how the GSEMO algorithm with additional diversity-enhancing heuristic optimizes a diversity of its

Jian Ma

In this paper we propose a two-sample test based on copula entropy (CE). The proposed test statistic is defined as the difference between the CEs of the null hypothesis and the alternative. The estimator of the test statistic is proposed with the non-parametric estimator of CE, which is non-parametric and hyperparameter-free. Simulation experiments verified

Xiaofei Chen, Yuting He, Cheng Xue, Rongjun Ge

The foundation models based on pre-training technology have significantly advanced artificial intelligence from theoretical to practical applications. These models have facilitated the feasibility of computer-aided diagnosis for widespread use. Medical contrastive vision-language pre-training, which does not require human annotations, is an effective approac

Tianyi Shi, Xiaohuan Ding, Liang Zhang, Xin Yang

Curvilinear object segmentation is critical for many applications. However, manually annotating curvilinear objects is very time-consuming and error-prone, yielding insufficiently available annotated datasets for existing supervised methods and domain adaptation methods. This paper proposes a self-supervised curvilinear object segmentation method that learns

Pol Henarejos, Ana I. Pérez-Neira

Physical layer security is a field of study that continues to gain importance over time. It encompasses a range of algorithms applicable to various aspects of communication systems. While research in the physical layer has predominantly focused on secrecy capacity, which involves logical and digital manipulations to achieve secure communication, there is lim

Wenyang Qian, Robert A. M. Basili, Mary Eshaghian-Wilner, Ashfaq Khokhar

The Traveling Salesman Problem (TSP) is one of the most often-used NP-Hard problems in computer science to study the effectiveness of computing models and hardware platforms. In this regard, it is also heavily used as a vehicle to study the feasibility of the quantum computing paradigm for this class of problems. In this paper, we tackle the TSP using the qu

Ahmet M. Elbir, Asmaa Abdallah, Abdulkadir Celik, Ahmed M. Eltawil

Next-generation wireless networks strive for higher communication rates, ultra-low latency, seamless connectivity, and high-resolution sensing capabilities. To meet these demands, terahertz (THz)-band signal processing is envisioned as a key technology offering wide bandwidth and sub-millimeter wavelength. Furthermore, THz integrated sensing and communicatio

John Fernley, Emmanuel Jacob

We consider a supercritical Galton-Watson process $Z_n$ whose offspring distribution has mean $m>1$ and is bounded by some $d\in \{2,3,\ldots\}$. As well-known, the associated martingale $W_n=Z_n/m^n$ converges a.s. to some nonnegative random variable $W_\infty$. We provide a universal upper bound for the right tail of $W_\infty$ and $W_n$, which is uniform

Bincheng Yang, Gangshan Wu

While transformer models have been demonstrated to be effective for natural language processing tasks and high-level vision tasks, only a few attempts have been made to use powerful transformer models for single image super-resolution. Because transformer models have powerful representation capacity and the in-built self-attention mechanisms in transformer m

Longxiang Tang, Kai Li, Chunming He, Yulun Zhang

This paper studies source-free domain adaptive fundus image segmentation which aims to adapt a pretrained fundus segmentation model to a target domain using unlabeled images. This is a challenging task because it is highly risky to adapt a model only using unlabeled data. Most existing methods tackle this task mainly by designing techniques to carefully gene

Ya-Ru Kong, Li-Fen Lai, Xin-Qiang Li, Xin-Shuai Yan

The absence of semitauonic decays of charmed hadrons makes the decay processes mediated by the quark-level $c\to d \tau^+ \nu_{\tau}$ transition inadequate for probing a generic new physics (NP) with all kinds of Dirac structures. To fill in this gap, we consider in this paper the quasielastic neutrino scattering process $\nu_{\tau}+n\to \tau^-+\Lambda_c$, a

Mario Grobler, Leif Sabellek, Sebastian Siebertz

We study Parikh automata on finite and infinite words. First we establish some results for Parikh automata on finite words. Following, we present several definitions of Parikh automata on infinite words. We consider the deterministic as well as the non-deterministic variants and study closure properties, expressiveness, and common decision problems with appl

Norbert Hegyvári

We are looking for integer sets that resemble classical Cantor set and investigate the structure of their sum sets. Especially we investigate $FS(B)$ the subset sum of sequence type $B=\{\lfloor p^n\alpha\rfloor\}^\infty_{n=0}$. When $p=2$, then we prove $FS(B)+FS(B)=\N$ by analogy with the Cantor set, and some structure theorem for $p>2$