May 2024 arXiv papers — page 136

Rosario Corso, Gabriele Gucciardi

In approximation theory classical discrete operators, like generalized sampling, Sz\'{a}sz-Mirak'jan, Baskakov and Bernstein operators, have been extensively studied for scalar functions. In this paper, we look at the approximation of curves by a class of discrete operators and we exhibit graphical examples concerning several cases. The topic has useful impl

D. L. Ferrario

The main problem is to understand and to find periodic symmetric orbits in the $n$-body problem, in the sense of finding methods to prove or compute their existence, and more importantly to describe their qualitative and quantitative properties. In order to do so, and in order to classify such orbits and their symmetries, computers have been extensively used

Zhichao Han, Long Xu, Liuao Pei, Fei Gao

In recent times, an increasing number of researchers have been devoted to utilizing deep neural networks for end-to-end flight navigation. This approach has gained traction due to its ability to bridge the gap between perception and planning that exists in traditional methods, thereby eliminating delays between modules. However, the practice of replacing ori

Amandeep Singh Bhatia, David E. Bernal Neira

Healthcare industries frequently handle sensitive and proprietary data, and due to strict privacy regulations, they are often reluctant to share data directly. In today's context, Federated Learning (FL) stands out as a crucial remedy, facilitating the rapid advancement of distributed machine learning while effectively managing critical concerns regarding da

Hang Zhou

We present the recent measurements of the $e^+e^-\to K^+K^- J/\psi$ process carried out by the BESIII experiment. A new decay mode $Y(4230)\to K^+K^- J/\psi$ is firstly identified by BESIII. Furthermore, two vector charmoniumlike states, $Y(4500)$ and $Y(4710)$, are reported for the first time in the energy-dependent line shape of $e^+e^-\to K^+K^- J/\psi$ c

Prabhat Kumar

This paper introduces "\texttt{TOPress3D}," a 3D topology optimization MATLAB code for structures subjected to design-dependent pressure loads. With a primary focus on pedagogical objectives, the code provides an easy learning experience, making it a valuable tool and practical gateway for newcomers, students, and researchers towards this topic. \texttt{TOPr

Siegfried Hörmann, Daniel Strenger

We extend the scope of Azadkia-Chatterjee's dependence coefficient between a scalar response $Y$ and a multivariate covariate $X$ to the case where $X$ takes values in a general metric space. Particular attention is paid to the case where $X$ is a curve. Although extending this framework at the population level is relatively straightforward, analyzing the as

Nicolas Delporte, Naoki Sasakura

The largest eigenvalue of random tensors is an important feature of systems involving disorder, equivalent to the ground state energy of glassy systems or to the injective norm of quantum states. For symmetric Gaussian random tensors of order 3 and of size $N$, in the presence of a Gaussian noise, continuing the work [arXiv:2310.14589], we compute the genuin

Sidharth Ranjan, Marten van Schijndel

Previous work has shown that isolated non-canonical sentences with Object-before-Subject (OSV) order are initially harder to process than their canonical counterparts with Subject-before-Object (SOV) order. Although this difficulty diminishes with appropriate discourse context, the underlying cognitive factors responsible for alleviating processing challenge

A. Basyrov, N. O. Stutzer, J. G. S. Lunde, H. K. Eriksen

We revisit the impact of finite time responses of bolometric detectors used for deep observations of the cosmic microwave background (CMB). Until now, bolometer transfer functions have been accounted for through a two-step procedure by first deconvolving an estimate of their Fourier-space representation from the raw time-ordered data (TOD), and then averagin

Feng-Li Lin, Bo Ning

Inspired by the recent discovery of a violation of strong cosmic censorship (SCC) for the near-extremal Reissner-Nordstr\"om black holes in de Sitter space (RN-dS), we investigate if the weak cosmic censorship conjecture (WCCC) can also be violated in RN-dS with a fixed cosmological constant. Our method is based on the recent formulation of examining WCCC by

Shane Kepley, Babette A. J. de Wolff

Pseudospectral approximation provides a means to approximate the dynamics of delay differential equations (DDE) by ordinary differential equations (ODE). This article develops a computer-aided algorithm to determine the distance between the unstable manifold of a DDE and the unstable manifold of the approximating pseudospectral ODE. The algorithm is based up

Letian Peng, Jingbo Shang

Persona-driven role-playing (PRP) aims to build AI characters that can respond to user queries by faithfully sticking with all persona statements. Unfortunately, existing faithfulness criteria for PRP are limited to coarse-grained LLM-based scoring without a clear definition or formulation. This paper presents a pioneering exploration to quantify PRP faithfu

Maxime Flin, Magnus M. Halldorsson, Alexandre Nolin

Graph coloring is fundamental to distributed computing. We give the first sub-logarithmic distributed algorithm for coloring cluster graphs. These graphs are obtained from the underlying communication network by contracting nodes and edges, and they appear frequently as components in the study of distributed algorithms. In particular, we give a $O(\log^* n)$

Fernando Lucatelli Nunes, Matthijs Vákár

We examine the categorical structure of the Grothendieck construction $\Sigma_{\mathsf{C}}\mathsf{L}$ of an indexed category $\mathsf{L} \colon \mathsf{C}^{op} \to \mathsf{CAT}$. Our analysis begins with characterisations of fibred limits, colimits, and monoidal (closed) structures. The study of fibred colimits leads naturally to a generalisation of the noti

Khanh-Tung Tran, Barry O'Sullivan, Hoang D. Nguyen

The development of Large Language Models (LLMs) has predominantly focused on high-resource languages, leaving extremely low-resource languages like Irish with limited representation. This work presents UCCIX, a pioneering effort on the development of an open-source Irish-based LLM. We propose a novel framework for continued pre-training of LLMs specifically

Davide Moltisanti, Hakan Bilen, Laura Sevilla-Lara, Frank Keller

We focus on the problem of recognising the end state of an action in an image, which is critical for understanding what action is performed and in which manner. We study this focusing on the task of predicting the coarseness of a cut, i.e., deciding whether an object was cut "coarsely" or "finely". No dataset with these annotated end states is available, so

Biswadeep Ghosh, Anup Dewanji, Sudipta Das

In survival analysis, frailty variables are often used to model the association in multivariate survival data. Identifiability is an important issue while working with such multivariate survival data with or without competing risks. In this work, we consider bivariate survival data with competing risks and investigate identifiability results with non-paramet

Thanasis Athanasiou, Michela Geri, Patrice Roose, Gareth H. McKinley

Abstract Knowledge of the evolution of mechanical properties of the curing matrix is of great importance in composite parts or structure fabrication. Conventional rheometry, based on small amplitude oscillatory shear is limited by long interrogation times. In rapidly evolving materials, time sweeps can provide a meaningful measurement albeit at a single freq

Kento Tsubouchi, Yosuke Mitsuhashi, Kunal Sharma, Nobuyuki Yoshioka

Twirling noise affecting quantum gates is essential in understanding and controlling errors, but applicable operations to noise are usually restricted by symmetries inherent in quantum gates. In this work, we propose symmetric Clifford twirling, a Clifford twirling utilizing only symmetric Clifford operators that commute with certain Pauli subgroups. We full

Jiarui Fang, Shangchun Zhao

Sequence parallelism (SP), which divides the sequence dimension of input tensors across multiple computational devices, is becoming key to unlocking the long-context capabilities of generative AI models. This paper investigates the state-of-the-art SP approaches, i.e. DeepSpeed-Ulysses and Ring-Attention, and proposes a unified SP approach, which is more rob

Sadek Belamfedel Alaoui, Adnane Saoud

This work establishes fundamental principles for verifying contract for interconnected hybrid systems. When system's hybrid arcs conform to the contract for a certain duration but subsequently violate it, the composition of hybrid dynamical systems becomes challenging. The objective of this work is to analyze the temporal satisfaction of the contract, allowi

Chenhao Wu, Qingbo Wu, Haoran Wei, Shuai Chen

Despite demonstrating superior rate-distortion (RD) performance, learning-based image compression (LIC) algorithms have been found to be vulnerable to malicious perturbations in recent studies. However, the adversarial attacks considered in existing literature remain divergent from real-world scenarios, both in terms of the attack direction and bitrate. Addi

Federico Laudisa

The Bohr and von Neumann views on the measurement process in quantum mechanics have been interpreted for a long time in somewhat controversial terms, often leading to misconceptions. On the basis of some textual analysis, I would like to show that, contrary to a widespread opinion, their views should be taken less inconsistent, and much closer to each other,

Antonio Laface, Luca Ugaglia, Macarena Vilches

We provide a characterization of asymptotical speciality of a nef and big divisor $D$ on an algebraic surface in terms of the arithmetic genus of curves in $D^{\perp}$. As a consequence we prove that the SHGH conjecture for linear systems on the blowing-up $X_r^2$ of the projective plane at points in very general position is equivalent to the fact that each

Marta Ziosi, Dasha Pruss

This paper presents a critical, qualitative study of the social role of algorithmic bias in the context of the Chicago crime prediction algorithm, a predictive policing tool that forecasts when and where in the city crime is most likely to occur. Through interviews with 18 Chicago-area community organizations, academic researchers, and public sector actors,

Wen Shang, Yuan Liao, Vasilis Friderikos, Halim Yanikomeroglu

Due to their ability to anchor into tall urban landforms, such as lampposts or street lights, robotic aerial base stations (RABSs) can create a hyper-flexible wireless multi-hop heterogeneous network to meet the forthcoming green, densified, and dynamic network deployment to support, inter alia, high data rates. In this work, we propose a network infrastruct

Ellen Baake, Michael Baake

The computation of matrix functions is a well-studied problem. Of special importance are the exponential and the logarithm of a matrix, where the latter also raises existence and uniqueness questions. This is particularly relevant in the context of matrix semigroups and their generators. Here, we look at matrix functions of triangular matrices, where a recur

Christian Zimmermann, Andreas Schäfer

Following previous works on that topic, we consider Euclidean hadronic matrix elements in position space of two spatially separated local currents on the lattice, in order to extract the $x$ dependence of parton distribution functions (PDFs). The corresponding approach is often referred to by the term lattice cross section. In this work we will consider vale

Shun Takagi, Li Xiong, Fumiyuki Kato, Yang Cao

Human mobility data offers valuable insights for many applications such as urban planning and pandemic response, but its use also raises privacy concerns. In this paper, we introduce the Hierarchical and Multi-Resolution Network (HRNet), a novel deep generative model specifically designed to synthesize realistic human mobility data while guaranteeing differe

Dipankar Barman, Debasish Ghosh, Bibhas Ranjan Majhi

Fulling-Davies-Unruh effect contains great amount of theoretical importance in various branches of physics. Requirement of very high acceleration hinders its experimental evidence. We put forward an idea to experimentally probe this effect by utilizing the Pancharatnam-Berry phase of an accelerated atom in presence of mirrors. We show that for much lower acc

Theodore S. Rappaport, Mingjun Ying, Nicola Piovesan, Antonio De Domenico

This paper introduces Waste Factor (W), also denoted as Waste Figure (WF) in dB, a promising new metric for quantifying energy efficiency in a wide range of circuits and systems applications, including data centers and RANs. Also, the networks used to connect data centers and AI computing engines with users for ML applications must become more power efficien

Zhong-Peng Li, Yu Wang, Ting Sun, Feng Wan

Spin rotation is central for the spin-manipulation of lepton beams which, in turn, plays an important role in investigation of the properties of spin-polarized lepton beams and the examination of spin-dependent interactions. However, realization of compact and ultrafast spin rotation of lepton beams, between longitudinal and transverse polarizations, still f

Vitalijs Brejevs, Andy Wand

We construct an infinite family of non-positive open books with once-punctured torus pages that support Stein-fillable contact structures. Combined with a result of Wendl, this allows us to give a complete answer to a long-standing question about the mapping class group of a compact surface with boundary: namely, we conclude that the monoid of monodromies su

Ren Wang, Ding-Tao Yang, Tao Xin, Shuai Shi

Recent advancements in optical, terahertz, and microwave systems have unveiled non-transverse optical toroidal pulses characterized by skyrmionic topologies, fractal-like singularities, space-time nonseparability, and anapole-exciting ability. Despite this, the longitudinally polarized fields of canonical toroidal pulses notably lag behind their transverse c

Yogesh Agarwal, Varun Jindal

This paper examines the equivalence between various set convergences, as studied in [7, 13, 22], induced by an arbitrary bornology $\mathcal{S}$ on a metric space $(X,d)$. Specifically, it focuses on the upper parts of the following set convergences: convergence deduced through uniform convergence of distance functionals on $\mathcal{S}$ ($\tau_{\mathcal{S},

Y. X. Zhang, B. R. Liu, K. Y. Zhang, J. M. Yao

We present a systematic study on the structural properties of odd-$Z$ superheavy nuclei with proton numbers $Z=117, 119$, and neutron numbers $N$ increasing from $N=170$ to the neutron dripline within the framework of axially deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc). The results are compared with those of even-even superheavy nucl

Mihai Masala, Denis C. Ilie-Ablachim, Dragos Corlatescu, Miruna Zavelca

In recent years, Large Language Models (LLMs) have achieved almost human-like performance on various tasks. While some LLMs have been trained on multilingual data, most of the training data is in English. Hence, their performance in English greatly exceeds their performance in other languages. This document presents our approach to training and evaluating th

Xiaojun Yuan, Yuqing Zheng, Mingchen Zhang, Boyu Teng

This paper studies a passive localization system, where an extremely large-scale antenna array (ELAA) is deployed at the base station (BS) to locate a user equipment (UE) residing in its near-field (Fresnel) region. We propose a novel algorithm, named array partitioning-based location estimation (APLE), for scalable near-field localization. The APLE algorith

Jonathan Windle, Iain Matthews, Sarah Taylor

Co-speech gesturing is an important modality in conversation, providing context and social cues. In character animation, appropriate and synchronised gestures add realism, and can make interactive agents more engaging. Historically, methods for automatically generating gestures were predominantly audio-driven, exploiting the prosodic and speech-related conte

Liangrui Pan, Yijun Peng, Yan Li, Yiyi Liang

Integrating the different data modalities of cancer patients can significantly improve the predictive performance of patient survival. However, most existing methods ignore the simultaneous utilization of rich semantic features at different scales in pathology images. When collecting multimodal data and extracting features, there is a likelihood of encounter

D. C. Thakur, Jalim Singh, A. V. Anil Kumar

We numerically investigate the dependence of range of attractive potential on the phase separation of 2-D binary systems. Through extensive simulations and analysis, we show that when the range of attractive interactions approaches the sticky sphere limit, the system undergoes a phase separation at lower temperature. Further reduction in temperature causes t

Okko Räsänen, Daniil Kocharov

Child-directed speech (CDS) is a particular type of speech that adults use when addressing young children. Its properties also change as a function of extralinguistic factors, such as age of the child being addressed. Access to large amounts of representative and varied CDS would be useful for child language research, as this would enable controlled computat

Danfeng Xiang, Jun Mo, Xiaofeng Wang, Lingzhi Wang

We present a detailed analysis of the progenitor and its local environment for the recently discovered type II supernova (SN) 2024ggi at a distance of about 6.7~Mpc, by utilizing the pre-explosion images from the Hubble Space Telescope (HST) and \textit{Spitzer} Space Telescope. The progenitor is identified as a red, bright variable star, with absolute $F814

Abdul Hannan Khan, Syed Tahseen Raza Rizvi, Dheeraj Varma Chittari Macharavtu, Andreas Dengel

Autonomous driving systems require a quick and robust perception of the nearby environment to carry out their routines effectively. With the aim to avoid collisions and drive safely, autonomous driving systems rely heavily on object detection. However, 2D object detections alone are insufficient; more information, such as relative velocity and distance, is r

Elsa Dupraz, Ismaila Salihou Adamou, Reza Asvadi, Tad Matsumoto

This paper investigates practical coding schemes for Distributed Hypothesis Testing (DHT). While the literature has extensively analyzed the information-theoretic performance of DHT and established bounds on Type-II error exponents through quantize and quantize-binning achievability schemes, the practical implementation of DHT coding schemes has not yet been

Tommy Shu

J.H.C. Whitehead introduced the concept of crossed modules in the early 20th century. These crossed modules are crucial for algebraic models of 2-type homotopy, which involve connected spaces with no higher than second-degree homotopy groups. They consist of two groups and certain relations between them, with known connections to 2-groups. By employing cross

Xueying Jiang, Sheng Jin, Xiaoqin Zhang, Ling Shao

Monocular 3D object detection aims for precise 3D localization and identification of objects from a single-view image. Despite its recent progress, it often struggles while handling pervasive object occlusions that tend to complicate and degrade the prediction of object dimensions, depths, and orientations. We design MonoMAE, a monocular 3D detector inspired

Riki Matsui, Shigeo S Kimura, Hamid Hamidani

In gamma-ray bursts (GRBs), $\sim$ 100 - 1000 s after the prompt emission, afterglow observations have consistently shown X-ray excesses detected in the form of flares (XFs; in long GRBs) or extended emission (EEs; in short GRBs). These observations are interpreted as emissions from jets launched by late central engine activity. However, the characteristics

Qing-Fu Song, Qi-Fang Lü, Dian-Yong Chen, Yu-Bing Dong

In present work, we perform a coupled-channel analysis of $B^{(*)}_{(s)}\bar{B}^{(*)}_{(s)}$ systems with the one-boson-exchange potentials. We first study the $I(J^{PC})=1(1^{+-})$ $B\bar{B}^{*}/B^{*}\bar{B}^{*}$ system to describe the $Z_{b}(10610)$ and $Z_{b}(10650)$ particles as molecular states and determine the reasonable range of cutoff parameter $\La

Giacomo Fedi

The ATLAS, CMS, and LHCb collaborations have leveraged data from proton-proton collisions at the Large Hadron Collider (LHC) to advance our understanding of fundamental particles and their interactions. These collaborative efforts underscore the significance of integrating datasets across different runs and energy levels, yielding insights that contribute to

Samuel Blitz, Josef Šilhan

We provide a natural generalization to submanifolds of the holographic method used to extract higher-order local invariants of both Riemannian and conformal embeddings, some of which depend on a choice of parallelization of the normal bundle. Qualitatively new behavior is observed in the higher-codimension case, giving rise to new invariants that obstruct th

Zhen Cao, F. Aharonian, Q. An, Axikegu

The first source catalog of Large High Altitude Air Shower Observatory reported the detection of a very-high-energy gamma ray source, 1LHAASO J1219+2915. In this paper a further detailed study of the spectral and temporal behavior of this point-like source have been carried. The best-fit position of the TeV source ($\rm{RA}=185.05^{\circ}\pm0.04^{\circ}$, $\

Jiang Wei, Su Chunmei, Zhang Ganghui

We present and analyze three distinct semi-discrete schemes for solving nonlocal geometric flows incorporating perimeter terms. These schemes are based on the finite difference method, the finite element method, and the finite element method with a specific tangential motion. We offer rigorous proofs of quadratic convergence under $H^1$-norm for the first sc

Guangjin Pan, Shugong Xu, Shunqing Zhang, Xiaojing Chen

Extended Reality (XR) is an important service in the 5G network and in future 6G networks. In contrast to traditional video on demand services, real-time XR video is transmitted frame-by-frame, requiring low latency and being highly sensitive to network fluctuations. In this paper, we model the quality of experience (QoE) for real-time XR video transmission

Knud Thomsen

On a scientific meta-level, it is discussed how an overall understanding of the physical universe can be built on the basis of well-proven theories, observations, and recent experiments. In the light of almost a century of struggle to make (common) sense of Quantum Mechanics and to reconcile it with General Relativity, it is proposed to (for some time) forge

Mayukh Mukherjee, Soumyadeb Samanta, Soumyadip Thandar

We identify a single computationally checkable analytic quantity interlacing Martin boundary collapse, Green geometry, and linear escape for transient random walks on finitely generated groups: the Green-variation functional \[ \Delta(S;a,b):=\max_{x\in\partial S}\frac{|G(a,x)-G(b,x)|}{G(a,x)}. \] We prove that $\Delta\to0$ along exhaustions characterises th

Chenxi Li, Weining Lu, Zhihao Ma, Litong Meng

Collaborative path planning for robot swarms in complex, unknown environments without external positioning is a challenging problem. This requires robots to find safe directions based on real-time environmental observations, and to efficiently transfer and fuse these observations within the swarm. This study presents a filtering method based on Fast Fourier

Zejian Zhuang, Raquel Molina, Jun-Xu Lu, Li-Sheng Geng

The $\Lambda(1405)$ has been one of the most controversial exotic baryons. If the $\Lambda(1405)$ possesses a two-pole molecular structure, these poles are expected to evolve differently towards the SU(3) limit. From an analysis of a recent LQCD simulation on the $\pi\Sigma-\bar{K}N$ scattering for $I=0$ and the study of the quark mass dependence of the octe

Tao Xue, Ying Zhang, Yanbin Wang, Wenbo Wang

IoT edge computing positions computing resources closer to the data sources to reduce the latency, relieve the bandwidth pressure on the cloud, and enhance data security. Nevertheless, data security in IoT edge computing still faces critical threats (e.g., data breaches). Access control is fundamental for mitigating these threats. However, IoT edge computing

Camille Pouchol, Emmanuel Trélat, Christophe Zhang

Motivated by applications requiring sparse or nonnegative controls, we investigate reachability properties of linear infinite-dimensional control problems under conic constraints. Relaxing the problem to convex constraints if the initial cone is not already convex, we provide a constructive approach based on minimising a properly defined dual functional, whi

Jianjun Jin

In this paper we introduce and study the integral means spectrum (IMS) functionals on Teichm\"uller spaces. We show that the IMS functionals on the closure of the universal Teichm\"uller space and the universal asymptotic Teichm\"uller space are both continuous. During the proof, we consider the Pre-Schwarzian derivative model of universal asymptotic Teichm\

Jianyi Chen, Wei Xue, Xu Tan, Zhen Ye

Singing Accompaniment Generation (SAG), which generates instrumental music to accompany input vocals, is crucial to developing human-AI symbiotic art creation systems. The state-of-the-art method, SingSong, utilizes a multi-stage autoregressive (AR) model for SAG, however, this method is extremely slow as it generates semantic and acoustic tokens recursively

Vjekoslav Kovač

We help Alice play a certain "convergence game" against Bob and win the prize, which is a constructive solution to a problem by Erd\H{o}s and Graham, posed in their 1980 book on open questions in combinatorial number theory. Namely, after several reductions using peculiar arithmetic identities, the game outcome shows that the set of points \[ \Big(\sum_{n\in

Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti, Jonathan Weber

The development of generative artificial intelligence for human motion generation has expanded rapidly, necessitating a unified evaluation framework. This paper presents a detailed review of eight evaluation metrics for human motion generation, highlighting their unique features and shortcomings. We propose standardized practices through a unified evaluation

Thao Le, Tim Miller, Ruihan Zhang, Liz Sonenberg

This paper presents Visual Evaluative AI, a decision aid that provides positive and negative evidence from image data for a given hypothesis. This tool finds high-level human concepts in an image and generates the Weight of Evidence (WoE) for each hypothesis in the decision-making process. We apply and evaluate this tool in the skin cancer domain by building

Yufei Gu

Double descent presents a counter-intuitive aspect within the machine learning domain, and researchers have observed its manifestation in various models and tasks. While some theoretical explanations have been proposed for this phenomenon in specific contexts, an accepted theory for its occurring mechanism in deep learning remains yet to be established. In t

G. Kaniadakis

The axiomatic structure of the $\kappa$-statistcal theory is proven. In addition to the first three standard Khinchin--Shannon axioms of continuity, maximality, and expansibility, two further axioms are identified, namely the self-duality axiom and the scaling axiom. It is shown that both the $\kappa$-entropy and its special limiting case, the classical Bolt

Ivan Hejný, Jonas Wallin, Małgorzata Bogdan, Michał Kos

Popular regularizers with non-differentiable penalties, such as Lasso, Elastic Net, Generalized Lasso, or SLOPE, reduce the dimension of the parameter space by inducing sparsity or clustering in the estimators' coordinates. In this paper, we focus on linear regression and explore the asymptotic distributions of the resulting low-dimensional patterns when the

Roman Chertovskih, Nikolay Pogodaev, Maxim Staritsyn, A. Pedro Aguiar

This work collects some methodological insights for numerical solution of a "minimum-dispersion" control problem for nonlinear stochastic differential equations, a particular relaxation of the covariance steering task. The main ingredient of our approach is the theoretical foundation called $\infty$-order variational analysis. This framework consists in esta

Yilin Ma, Jiajia Huang, Shengyong Gao, iangyu Li

Rechargeable Zn batteries offer safe, inexpensive energy storage, but when deeply discharged to compete with lithium-ion batteries, they are plagued by parasitic reactions at the Zn anodes. We apply super-concentrated alkaline electrolytes to suppress two key parasitic reactions, hydrogen evolution and ZnO passivation. An electrolyte with 15 M KOH displays a

Sonit Singh

The novel coronavirus (COVID-19), a highly infectious respiratory disease caused by the SARS-CoV-2 has emerged as an unprecedented healthcare crisis. The pandemic had a devastating impact on the health, well-being, and economy of the global population. Early screening and diagnosis of symptomatic patients plays crucial role in isolation of patient to help st

Supryadi, Leiyu Pan, Deyi Xiong

Massively multilingual neural machine translation (MMNMT) has been proven to enhance the translation quality of low-resource languages. In this paper, we empirically investigate the translation robustness of Indonesian-Chinese translation in the face of various naturally occurring noise. To assess this, we create a robustness evaluation benchmark dataset for

Stephan Dempe, Patrick Mehlitz

Usually, bilevel optimization problems need to be transformed into single-level ones in order to derive optimality conditions and solution algorithms. Among the available approaches, the replacement of the lower-level problem by means of duality relations became popular quite recently. We revisit three realizations of this idea which are based on the lower-l

Martin Berglund, Willeke Martens, Brink van der Merwe

Many natural language processing systems operate over tokenizations of text to address the open-vocabulary problem. In this paper, we give and analyze an algorithm for the efficient construction of deterministic finite automata (DFA) designed to operate directly on tokenizations produced by the popular byte pair encoding (BPE) technique. This makes it possib

Nadezhda Semenova

In recent years, more and more works have appeared devoted to the analog (hardware) implementation of artificial neural networks, in which neurons and the connection between them are based not on computer calculations, but on physical principles. Such networks offer improved energy efficiency and, in some cases, scalability, but may be susceptible to interna

Yamato Honda, Soma Onoda, Hiroshi Suzuki

Employing the modified Villain lattice formulation of the axion quantum electrodynamics, we present an alternative and much simpler derivation of the conclusion of~Ref.~\cite{Honda:2024sdz} that the sweep of the axial $U(1)$ non-invertible symmetry operator over the (non-genuine) gauge invariant 't~Hooft line operator with an integer magnetic charge does not

Qilin Zhou, Zhengyuan Wei, Haipeng Wang, Bo Jiang

Patch robustness certification is an emerging kind of defense technique against adversarial patch attacks with provable guarantees. There are two research lines: certified recovery and certified detection. They aim to label malicious samples with provable guarantees correctly and issue warnings for malicious samples predicted to non-benign labels with provab

Haoran Li, Yulin Chen, Zihao Zheng, Qi Hu

With rapid advances, generative large language models (LLMs) dominate various Natural Language Processing (NLP) tasks from understanding to reasoning. Yet, language models' inherent vulnerabilities may be exacerbated due to increased accessibility and unrestricted model training on massive data. A malicious adversary may publish poisoned data online and cond

André Chailloux, Thomas Debris-Alazard

Understanding the maximum size of a code with a given minimum distance is a major question in computer science and discrete mathematics. The most fruitful approach for finding asymptotic bounds on such codes is by using Delsarte's theory of association schemes. With this approach, Delsarte constructs a linear program such that its maximum value is an upper b

Artemy Kolchinsky

The partial information decomposition (PID) aims to quantify the amount of redundant information that a set of sources provides about a target. Here, we show that this goal can be formulated as a type of information bottleneck (IB) problem, termed the "redundancy bottleneck" (RB). The RB formalizes a tradeoff between prediction and compression: it extracts i

Rui Zhu

Geospatial knowledge graphs have emerged as a novel paradigm for representing and reasoning over geospatial information. In this framework, entities such as places, people, events, and observations are depicted as nodes, while their relationships are represented as edges. This graph-based data format lays the foundation for creating a "FAIR" (Findable, Acces

Harry Walsh, Ben Saunders, Richard Bowden

Sign Language Production (SLP) is a challenging task, given the limited resources available and the inherent diversity within sign data. As a result, previous works have suffered from the problem of regression to the mean, leading to under-articulated and incomprehensible signing. In this paper, we propose using dictionary examples to create expressive sign

Ricardo Knauer, Erik Rodner

Many industry verticals are confronted with small-sized tabular data. In this low-data regime, it is currently unclear whether the best performance can be expected from simple baselines, or more complex machine learning approaches that leverage meta-learning and ensembling. On 44 tabular classification datasets with sample sizes $\leq$ 500, we find that L2-r

Michele Gianfelice

In this note we complete the analysis carried on in \cite{CGSV} about the topological synchronisation of unimodal maps of the interval coupled in a master-slave configuration, by answering to the questions raised in that paper. Namely, we compute the weak limits of the invariant measure of the coupled system as the coupling strength $k\in\left( 0,1\right) $

Omar M. Saad, Matteo Ravasi, Tariq Alkhalifah

Distributed Acoustic Sensing (DAS) is a promising technology introducing a new paradigm in the acquisition of high-resolution seismic data. However, DAS data often show weak signals compared to the background noise, especially in tough installation environments. In this study, we propose a new approach to denoise DAS data that leverages an unsupervised deep

Erkki Thuneberg

We study Andreev reflection in a one-dimensional square-well pair-potential. We discuss the history of the model. The current-phase relation is presented as a sum over Matsubara frequencies. How the current arises from bound and continuum levels is found by analytic continuation. We discuss two limiting cases of the square-well potential, the zero-length wel

Joshua Holstein, Philipp Spitzer, Marieke Hoell, Michael Vössing

As organizations face the challenges of processing exponentially growing data volumes, their reliance on analytics to unlock value from this data has intensified. However, the intricacies of big data, such as its extensive feature sets, pose significant challenges. A crucial step in leveraging this data for insightful analysis is an in-depth understanding of

Amir Jahangiri, Vladislav Orekhov

Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained several artificial neural networks in our new toolbox Magnetic Resonance with Artificial intelligence (MR-Ai) to so

Alessandro Artale, Roman Kontchakov, Andrea Mazzullo, Frank Wolter

Definite descriptions, such as 'the General Chair of KR 2024', are a semantically transparent device for object identification in knowledge representation. In first-order modal logic, definite descriptions have been widely investigated for their non-rigidity, which allows them to designate different objects (or none at all) at different states. We propose ex

Liuxin Bao, Xiaofei Zhou, Xiankai Lu, Yaoqi Sun

Depth images and thermal images contain the spatial geometry information and surface temperature information, which can act as complementary information for the RGB modality. However, the quality of the depth and thermal images is often unreliable in some challenging scenarios, which will result in the performance degradation of the two-modal based salient o

Marvin Schneider

Let $\Lambda$ be a complete noetherian local ring with finite residue field of characteristic $p$ and $K/\mathbb{Q}_p$ a $p$-adic field. We show that, by deformation of the structure sheaf on the (transversal) prismatic site of a bounded $p$-adic formal scheme $\mathfrak{X}$, the category of prismatic $(\Lambda,F)$-crystals on $\mathfrak{X}$ is equivalent to

Thomas Pöllabauer, Volker Knauthe, André Boller, Arjan Kuijper

Deep Neural Networks (DNNs) require large amounts of annotated training data for a good performance. Often this data is generated using manual labeling (error-prone and time-consuming) or rendering (requiring geometry and material information). Both approaches make it difficult or uneconomic to apply them to many small-scale applications. A fast and straight

Michal Košťál, Evžen Losa, Stanislav Simakov, Tomáš Czakoj

The measured and evaluated excitation functions are fundamental quantities that affect the accuracy of all calculations in nuclear applications. Some cross sections, such as 14N(n,p)14C, have added value for special applications, as these reactions may be responsible for possible contamination in industrial processes such as spent fuel reprocessing. For the

Zeyu Wang, Yuanchun Shi, Yuntao Wang, Yuchen Yao

Modern information querying systems are progressively incorporating multimodal inputs like vision and audio. However, the integration of gaze -- a modality deeply linked to user intent and increasingly accessible via gaze-tracking wearables -- remains underexplored. This paper introduces a novel gaze-facilitated information querying paradigm, named G-VOILA,

Andrea Vezzosi, Carlos Payá, Paweł Wójcik, Andrea Bertoni

Full-shell hybrid nanowires (NWs), structures comprising a superconductor shell that encapsulates a semiconductor (SM) core, have attracted considerable attention in the search for Majorana zero modes (MZMs). However, the predicted Rashba spin-orbit coupling (SOC) in the SM is too small to achieve substantial topological minigaps. In addition, the SM wavefun

Jin Won Kim, Prashant G. Mehta

Duality between estimation and control is a foundational concept in Control Theory. Most students learn about the elementary duality -- between observability and controllability -- in their first graduate course in linear systems theory. Therefore, it comes as a surprise that for a more general class of nonlinear stochastic systems (hidden Markov models or H

Anirudh Dash, Aditya Siripuram

Motivated by orthogonal dictionary learning problems, we propose a novel method for matrix factorization, where the data matrix $\mathbf{Y}$ is a product of a Householder matrix $\mathbf{H}$ and a binary matrix $\mathbf{X}$. First, we show that the exact recovery of the factors $\mathbf{H}$ and $\mathbf{X}$ from $\mathbf{Y}$ is guaranteed with $\Omega(1)$ co

Qingguo Liu, Chenyi Zhuang, Pan Gao, Jie Qin

Existing Blind image Super-Resolution (BSR) methods focus on estimating either kernel or degradation information, but have long overlooked the essential content details. In this paper, we propose a novel BSR approach, Content-aware Degradation-driven Transformer (CDFormer), to capture both degradation and content representations. However, low-resolution imag

Shahid Hussain, Young-Chon Kim

The larger battery capacities and the longer waiting and charging time of electric vehicles (EVs) results in low utilization of charging stations (CSs). This paper, proposes fuzzy logic weight based coordination (FLWC) scheme to enhance the utilization of CSs. Each EV has an associated uncertain information including stay time and the current state-of-charge