February 2024 arXiv papers — page 142

J. Ossorio-Castillo, José M. Tornero

Two quantum algorithms are presented, which tackle well--known problems in the context of numerical semigroups: the numerical semigroup membership problem (NSMP) and the Sylvester denumerant problem (SDP).

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The first observation of the $B_c^+ \to J/\psi \pi^+ \pi^0$ decay is reported with high significance using proton-proton collision data, corresponding to an integrated luminosity of 9fb$^{-1}$, collected with the LHCb detector at centre-of-mass energies of 7, 8, and 13 TeV. The ratio of its branching fraction relative to the $B_c^+ \to J/\psi \pi^+$ channel

Janez Rus, Aleksi Bossart, Benjamin Apffel, Matthieu Mallejac

Wakes are medium perturbations created by a moving object, such as wave patterns behind boats, or wingtip vortices following an aircraft. Here, we report about an experimental study of an uncharted form of parabolic wakes occurring in media with the group velocity twice larger than the phase velocity, as opposed to the conventional case of Kelvin wakes. They

Sreetama Sarkar, Souvik Kundu, Peter A. Beerel

The growing concern about data privacy has led to the development of private inference (PI) frameworks in client-server applications which protects both data privacy and model IP. However, the cryptographic primitives required yield significant latency overhead which limits its wide-spread application. At the same time, changing environments demand the PI se

Konrad Aguilar, Katrine von Bornemann Hjelmborg, Frederic Latremoliere

Given a compact quantum metric space (A, L), we prove that the domain of L coincides with A if and only if A is finite dimensional. We then show how one can explicitly build many quantum metrics with distinct domains on infinite-dimensional AF algebras. In the last section, we provide a strategy for calculating the distance between certain states in these qu

Mike Thelwall

Purpose: Assess whether ChatGPT 4.0 is accurate enough to perform research evaluations on journal articles to automate this time-consuming task. Design/methodology/approach: Test the extent to which ChatGPT-4 can assess the quality of journal articles using a case study of the published scoring guidelines of the UK Research Excellence Framework (REF) 2021 to

Nestor Nina Zarate, Sergio Romaña

In this paper, we study rigidity problems between Lyapunov exponents along periodic orbits and geometric structures. More specifically, we prove that for a surface M without focal points, if the value of the Lyapunov exponents is constant over all periodic orbits, then $M$ is the flat 2-torus or a surface of constant negative curvature. We obtain the same re

Göktuğ Karpat, Barış Çakmak

We examine the emergence of dynamical memory effects in quantum processes having indefinite time direction and causal order. In particular, we focus on the class of phase-covariant qubit channels, which encompasses some of the most significant paradigmatic open quantum system models. In order to assess the memory in the time evolution of the system, we utili

Kiyu Fukui, Yasuyuki Kato, Yukitoshi Motome

Open quantum systems display unusual phenomena not seen in closed systems, such as new topological phases and unconventional phase transitions. An interesting example was studied for a quantum spin liquid in the Kitaev model [K. Yang, S. C. Morampudi, and E. J. Bergholtz, Phys. Rev. Lett. ${\bf 126}$, 077201 (2021)]; an effective non-Hermitian Kitaev model,

Yufeng Zhao, Yoshihiro Sakai, Naoya Inoue

In-Context Learning (ICL) is suffering from unsatisfactory performance and under-calibration due to high prior bias and unfaithful confidence. Some previous works fine-tuned language models for better ICL performance with enormous datasets and computing costs. In this paper, we propose NoisyICL, simply perturbing the model parameters by random noises to stri

Serena Dipierro, Edoardo Proietti Lippi, Caterina Sportelli, Enrico Valdinoci

We present a new functional setting for Neumann conditions related to the superposition of (possibly infinitely many) fractional Laplace operators. We will introduce some bespoke functional framework and present minimization properties, existence and uniqueness results, asymptotic formulas, spectral analyses, rigidity results, integration by parts formulas,

Linard Hoessly

Bayesian networks are widely utilised in various fields, offering elegant representations of factorisations and causal relationships. We use surjective functions to reduce the dimensionality of the Bayesian networks by combining states and study the preservation of their factorisation structure. We introduce and define corresponding notions, analyse their pr

Juhwan Choi, Eunju Lee, Kyohoon Jin, YoungBin Kim

Data annotation is an essential step for constructing new datasets. However, the conventional approach of data annotation through crowdsourcing is both time-consuming and expensive. In addition, the complexity of this process increases when dealing with low-resource languages owing to the difference in the language pool of crowdworkers. To address these issu

Cyrille Chenavier, Thomas Cluzeau, Adya Musson-Leymarie

We investigate formal power series ideals and their relationship to topological rewriting theory. Since commutative formal power series algebras are Zariski rings, their ideals are closed for the adic topology defined by the maximal ideal generated by the indeterminates. We provide a constructive proof of this result which, given a formal power series in the

Helena Cobo, M. J. Soto, José M. Tornero

We introduce a variation of the well-known Newton-Hironaka polytope for algebroid hypersurfaces. This combinatorial object is a perturbed version of the original one, parametrized by a real number. For well-chosen values of the parameter, the objects obtained are very close to the original, while at the same time presenting more (hopefully interesting) infor

Felix Sainsbury-Martinez, Catherine Walsh

Impacts from icy and rocky bodies have helped shape the composition of solar system objects, for example the Earth-Moon system, or the recent impact of comet Shoemaker-Levy 9 with Jupiter. It is likely that such impacts also shape the composition of exoplanetary systems. Here we investigate how cometary impacts might affect the atmospheric composition/chemis

Ryoto Kanegae, Masaki Kawamura

We theoretically evaluated the performance of our proposed associative watermarking method in which the watermark is not embedded directly into the image. We previously proposed a watermarking method that extends the zero-watermarking model by applying associative memory models. In this model, the hetero-associative memory model is introduced to the mapping

Nick Pepper, Francesco Montomoli, Kyriakos Kantarakias

This paper presents a method for performing Uncertainty Quantification in high-dimensional uncertain spaces by combining arbitrary polynomial chaos with a recently proposed scheme for sensitivity enhancement (1). Including available sensitivity information offers a way to mitigate the curse of dimensionality in Polynomial Chaos Expansions (PCEs). Coupling th

Valentina De Romeri, Dimitrios K. Papoulias, Christoph A. Ternes

Solar neutrinos induce elastic neutrino-electron scattering in dark matter direct detection experiments, resulting in detectable event rates at current facilities. We analyze recent data from the XENONnT, LUX-ZEPLIN, and PandaX-4T experiments and we derive stringent constraints on several $U(1)'$ extensions of the Standard Model, accommodating new neutrino-e

Xingsheng Li, Jing Li

The linear instability of Faraday waves in Hele-Shaw cells is investigated with consideration of the viscosity of fluids after gap-averaging the governing equations due to the damping from two lateral walls and the dynamic behavior of contact angle. A new hydrodynamic model is thus derived and solved semi-analytically. The contribution of viscosity to critic

Vineeth Chintala

We present an elementary combinatorial proof of the celebrated Friendship theorem. The proof involves looking at independent sets and constructing a bound on their size which forces a contradiction.

Stefan Kindermann

We consider infinite-dimensional generalized Hilbert matrices of the form $H_{i,j} = \frac{d_i d_j}{x_i + x_j}$, where $d_i$ are nonnegative weights and $x_i$ are pairwise disjoint positive numbers. We state sufficient and, for monotonically rearrangeable $x_i$, also necessary conditions for $d_i$, $x_i$ such that the induced operator from $\ell^2 \to \ell^2

Boyang Ti, Yongsheng Gao, Jie Zhao, Sylvain Calinon

Humans use tools to complete impact-aware tasks such as hammering a nail or playing tennis. The postures adopted to use these tools can significantly influence the performance of these tasks, where the force or velocity of the hand holding a tool plays a crucial role. The underlying motion planning challenge consists of grabbing the tool in preparation for t

Lara Scavuzzo, Karen Aardal, Andrea Lodi, Neil Yorke-Smith

Mixed Integer Linear Programming (MILP) is a pillar of mathematical optimization that offers a powerful modeling language for a wide range of applications. During the past decades, enormous algorithmic progress has been made in solving MILPs, and many commercial and academic software packages exist. Nevertheless, the availability of data, both from problem i

Alexis Aumonier

We show that the spaces of holomorphic and continuous maps from a smooth complex projective variety to a projective space have the same homology in a range depending on the degree of the maps.

Elisabeth Gutierrez, Natividad Llorca, Joaquin Sanchez-Soriano, Manuel A. Mosquera

In this paper we deal with production situations where a cap or limit to the amount of greenhouse gas emissions permitted is imposed. Fixing a tax for each ton of pollutant emitted is also considered. We use bankruptcy rules to define cooperative games with externalities associated with these situations and analyze the existence of coalitionally stable alloc

Phong Tran, Thong Nguyen, Long Chu, Nhi Tran

The rapid expansion of user medical records across global systems presents not only opportunities but also new challenges in maintaining effective application models that ensure user privacy, controllability, and the ability to commercialize patient medical records. Moreover, the proliferation of data analysis models in healthcare institutions necessitates t

Dimitrios Gousopoulos

In recent years there has been growing evidence that even after teaching designed to address the learning difficulties dictated by literature, many physics learners fail to create the proper reasoning chains that connect the fundamental principles and lead to reasoned predictions. Even though students have the required knowledge and skills, they are often ba

Anton Kuznietsov, Balint Gyevnar, Cheng Wang, Steven Peters

Artificial Intelligence (AI) shows promising applications for the perception and planning tasks in autonomous driving (AD) due to its superior performance compared to conventional methods. However, inscrutable AI systems exacerbate the existing challenge of safety assurance of AD. One way to mitigate this challenge is to utilize explainable AI (XAI) techniqu

Ivana Capan

In this paper, an overview of the wide bandgap (WBG) semiconductors for radiation detection applications is presented. The recent advancements in the fabrication of high-quality wafers have enabled the remarkable WBG semiconductor device applications. The most common 4H-SiC, GaN and \b{eta}-Ga2O3 devices used for radiation detection are described. The 4H-SiC

María Teresa García-Ordás, Martín Bayón-Gutiérrez, Carmen Benavides, Jose Aveleira-Mata

Cardiovascular diseases state as one of the greatest risks of death for the general population. Late detection in heart diseases highly conditions the chances of survival for patients. Age, sex, cholesterol level, sugar level, heart rate, among other factors, are known to have an influence on life-threatening heart problems, but, due to the high amount of va

Erika Rácz, Milan Malý, Ondřej Cejpek, Jan Jedelský

Rotary atomization is used in a wide variety of fields, exploiting the external control option of the spray while no high-pressure fluid is needed. Most papers on rotary atomization deal with liquid jet breakup, while external spray characteristics are rarely evaluated; this is performed currently. The water spray was measured by a two-component Phase Dopple

Mingyi Zhou, Xiang Gao, Jing Wu, Kui Liu

Numerous mobile apps have leveraged deep learning capabilities. However, on-device models are vulnerable to attacks as they can be easily extracted from their corresponding mobile apps. Existing on-device attacking approaches only generate black-box attacks, which are far less effective and efficient than white-box strategies. This is because mobile deep lea

Yingxiao Song, Qi Xiong, Yan Gong, Furen Deng

Void size function (VSF) contains information of the cosmic large-scale structure (LSS), and can be used to derive the properties of dark energy and dark matter. We predict the VSFs measured from the spectroscopic galaxy survey operated by the China Space Station Telescope (CSST), and study the strength of cosmological constraint. We employ a high-resolution

María Teresa García-Ordás, José Alberto Benítez-Andrades, Jose Aveleira-Mata, José-Manuel Alija-Pérez

Parkinson's disease is easy to diagnose when it is advanced, but it is very difficult to diagnose in its early stages. Early diagnosis is essential to be able to treat the symptoms. It impacts on daily activities and reduces the quality of life of both the patients and their families and it is also the second most prevalent neurodegenerative disorder after A

Chaoxiong He, Jinchuan Wang, Ying Dong, Shaochong Zhu

In optomechanical systems, the libration and rotation of nanoparticles offer profound insights for ultrasensitive torque measurement and macroscopic quantum superpositions. Achievements include transitioning libration to rotation up to 6 GHz and cooling libration to millikelvin temperatures. It is undoubted that the libration and rotation are respectively dr

María Teresa García-Ordás, Sergio Rubio-Martín, José Alberto Benítez-Andrades, Hector Alaiz-Moretón

This study proposes a method based on fully convolutional neural networks (FCNs) to identify migratory birds from their songs, with the objective of recognizing which birds pass through certain areas and at what time. To determine the best FCN architecture, extensive experimentation was conducted through a grid search, exploring the optimal depth, width, and

Gerold Alsmeyer, Alexander Iksanov, Zakhar Kabluchko

Let $S_{n}=\sum_{k=1}^{n}\xi_{k}$, $n\in\mathbb{N}$, be a standard random walk with i.i.d. nonnegative increments $\xi_{1},\xi_{2},\ldots$ and associated renewal counting process $N(t)=\sum_{n\ge 1}1_{\{S_{n}\le t\}}$, $t\ge 0$. A decoupling of $(S_{n})_{n\ge 1}$ is any sequence $\hat{S}_{1}$, $\hat{S}_{2},\ldots$ of independent random variables such that, f

A. Rybnikov, N. Anfimov, M. Qu, A. Chetverikov

Modern neutrino physics detectors often employ thousands, and sometimes even hundreds of thousands, of Silicon Photomultipliers (SiPMs). The TAO experiment is a notable example that utilizes a spherical scintillator barrel with a diameter of 1.8 meters, housing approximately 130,000 SiPMs organized into 4,100 tiles. Each tile with size of 5x5cm^2 consists of

Ziqi Wang, Yuan Zhong, Hui Wang

In this work, we consider a two-dimensional (2D) dilaton gravity model where the dilaton kinetic term $\mathcal{X}$ is modified by an additional derivative coupling term $\alpha\mathcal{X}^2$. In the case with a canonical scalar matter field, the field equations of this model have a simple first-order formalism, from which exact static kink solutions can be

Wei-Liang Qian, Qiyuan Pan, Bean Wang, Rui-Hong Yue

Damour-Solodukhin wormholes are intriguing theoretical constructs, closely mimicking many properties of black holes. This study delves into two distinct characteristics of the waveforms emitted from such wormholes, namely, the late-time tails and echoes, which can substantially be used to distinguish its identity. Notably, both features appear in the latter

Nhi Tran, Tan Tran, Nam Nguyen

This paper presents an extensive study on the application of AI techniques for software effort estimation in the past five years from 2017 to 2023. By overcoming the limitations of traditional methods, the study aims to improve accuracy and reliability. Through performance evaluation and comparison with diverse Machine Learning models, including Artificial N

José L. Risco-Martín, Saurabh Mittal, Juan Carlos Fabero, Marina Zapater

The Discrete Event System Specification formalism (DEVS), which supports hierarchical and modular model composition, has been widely used to understand, analyze and develop a variety of systems. DEVS has been implemented in various languages and platforms over the years. The DEVStone benchmark was conceived to generate a set of models with varied structure a

Cho-Yuan Lee, Kuan-Chen Wang, Kai-Chun Liu, Yu-Te Wang

In practical scenarios involving the measurement of surface electromyography (sEMG) in muscles, particularly those areas near the heart, one of the primary sources of contamination is the presence of electrocardiogram (ECG) signals. To assess the quality of real-world sEMG data more effectively, this study proposes QASE-net, a new non-intrusive model that pr

Arrate Antuñano, Leigh N. Fletcher, Glenn S. Orton, Henrik Melin

We use an infrared dataset captured between 1984 and 2017 using several instruments and observatories to report five rare equatorial disturbances that completely altered the appearance of Jupiter's Equatorial Zone (EZ): the clearance of tropospheric clouds revealed a new 5-$\mu$m-bright band encircling the planet at the equator, accompanied by large 5-$\mu$m

Friedrich Niemann, Christopher Reining

In a social networked industry, the focus is on collaboration between humans and technology. Communication is the basic prerequisite for synergetic collaboration between all players. It includes non-verbal as well as verbal interactions. To enable non-verbal interaction, machines must be able to detect and understand human movements. This article presents th

J. Anasagasti, A. Berciano, A. Izagirre

Over the last decades,it has been shown that teaching and learning statistics is complex, regardless of the teaching methodology. This research presents the different learning profiles identified in a group of future Primary Education (PE) teachers during the study of the Statistics blockdepending on the methodology used and gender, where the sample consists

Shishir Biswas, Rajaraman Ganesh

We provide a thorough comparison of the GMHD3D code and the PLUTO4.4 code for both two and three-dimensional hydrodynamic and magnetohydrodynamic problems. The open-source finite-volume solver PLUTO4.4 and the in-house developed pseudo-spectral multi-GPU solver GMHD3D both can be used to model the dynamics and turbulent motions of astrophysical plasmas. Alth

Mehmet Emre Tasgin, Hyunchul Nha

An optical lattice with cold trapped atoms represents a quantum system of fundamental importance as it enables the study of quantum many-body system in a controllable way. It is thus necessary to develop theoretical and experimental tools to explore quantum correlation in such systems to advance our understanding of many-body physics. While previous works ha

Talha Bozkus, Urbashi Mitra

Reinforcement learning (RL) is a classical tool to solve network control or policy optimization problems in unknown environments. The original Q-learning suffers from performance and complexity challenges across very large networks. Herein, a novel model-free ensemble reinforcement learning algorithm which adapts the classical Q-learning is proposed to handl

Alexander Kushpel

Let $X$ be a Banach space with the unit ball $B(X)$ and $A\subset X$ be a convex origin-symmetric compact in $X$. Let $\mathrm{j}:X\rightarrow \widetilde{X}$ be an isometric extension of $X$. It is well-known that linear widths $\lambda _{n}\left( \mathrm{j}\left( A\right) \text{,}% \widetilde{X}\right) $ may decrease in order when compared with $\lambda _{n

Gilad Gour

This book delves into the burgeoning field of quantum resource theories, a novel and vibrant area of research within quantum information science that seeks to unify diverse quantum phenomena under a single framework. By recognizing various attributes of physical systems as "resources," this approach offers a fresh perspective on quantum phenomena, transformi

Yihao Lin, Ji Feng

Our understanding of collective spin fluctuation in materials relies largely on Heisenberg-type spin Hamiltonians. Implicit in these spin models is the atomic moment picture that in transverse spin dynamics the magnetization around an atom undergoes precessional motion as a rigid moment, which has been challenged by emerging theoretical and experimental adva

Roy Ganz, Yair Kittenplon, Aviad Aberdam, Elad Ben Avraham

Vision-Language (VL) models have gained significant research focus, enabling remarkable advances in multimodal reasoning. These architectures typically comprise a vision encoder, a Large Language Model (LLM), and a projection module that aligns visual features with the LLM's representation space. Despite their success, a critical limitation persists: the vis

Qipeng Wang, Shiqi Jiang, Zhenpeng Chen, Xu Cao

Web applications have increasingly adopted Deep Learning (DL) through in-browser inference, wherein DL inference performs directly within Web browsers. The actual performance of in-browser inference and its impacts on the quality of experience (QoE) remain unexplored, and urgently require new QoE measurements beyond traditional ones, e.g., mainly focusing on

Donggeun Tak, Z. Lucas Uhm, James H. Gillanders

A kilonova, the electromagnetic emission produced by compact binary mergers, is formed through a delicate interplay of physical processes, involving r-process nucleosynthesis and interactions between heavy elements and photons through radiative transfer. This complexity makes it difficult to achieve a comprehensive understanding of kilonova spectra. In this

Mohamadreza Delbari, Robin Neuder, Alejandro Jiménez-Sáez, Arash Asadi

Liquid crystal (LC) technology offers a cost-effective, scalable, energy-efficient, and continuous phase tunable realization of extremely large reconfigurable intelligent surfaces (RISs). However, LC response time to achieve a desired differential phase is significantly higher compared to competing silicon-based technologies (RF switches, PIN diodes, etc). T

Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel

We present a new algorithm to optimize distributions defined implicitly by parameterized stochastic diffusions. Doing so allows us to modify the outcome distribution of sampling processes by optimizing over their parameters. We introduce a general framework for first-order optimization of these processes, that performs jointly, in a single loop, optimization

Guangyu Shen, Siyuan Cheng, Kaiyuan Zhang, Guanhong Tao

Large Language Models (LLMs) have become prevalent across diverse sectors, transforming human life with their extraordinary reasoning and comprehension abilities. As they find increased use in sensitive tasks, safety concerns have gained widespread attention. Extensive efforts have been dedicated to aligning LLMs with human moral principles to ensure their s

K. S. Viswanadh, Akshit Gureja, Nagesh Walchatwar, Rishabh Agrawal

Remote labs are a groundbreaking development in the education industry, providing students with access to laboratory education anytime, anywhere. However, most remote labs are costly and difficult to scale, especially in developing countries. With this as a motivation, this paper proposes a new remote labs (RLabs) solution that includes two use case experime

Ding Yu Shao, Yu Shi, Cheng Zhang, Jian Zhou

We explore the impact of initial state soft gluon radiations on the azimuthal angle asymmetries in photo-production of hard di-jet via coherent diffraction in ultraperipheral heavy ion collisions, as well as in electron-proton ($ep$) and electron-nucleus ($eA$) collisions. The primary production mechanism is identified as the diffractive production of two ha

Elona Agora, Jorge Antezana, María J. Carro

The main goal of this paper is to provide a complete characterization of the weak-type boundedness of the Hardy-Littlewood maximal operator, $M$, on weighted Lorentz spaces $\Lambda^p_u(w)$, whenever $p>1$. This solves a problem left open in \cite{crs:crs}. Moreover, with this result, we complete the program of unifying the study of the boundedness of $M$ on

O. P. Bychkov, G. A. Faranosov

It is shown that the velocity fluctuation spectra measured using a hot-wire in the potential flow region of a turbulent jet near field in the presence of a co-flow can be converted into the spectra of pressure fluctuations. The proposed conversion method is based on the fact that the structure of instability waves, which make a decisive contribution to the j

Abhishek Chakraborty, Angelia Nedić

This paper considers a variational inequality (VI) problem arising from a game among multiple agents, where each agent aims to minimize its own cost function subject to its constrained set represented as the intersection of a (possibly infinite) number of convex functional level sets. A direct projection-based approach or Lagrangian-based techniques for such

R. Sharma, B. S. Ratanpal, Rinkal Patel

A family of solutions defining the interior of a static, spherically symmetric, compact anisotropic star is described by considering a new form of the equation of state (EOS). The analytic solution is derived by using the Finch and Skea ansatz for the metric potential g_rr, which has a clear geometric interpretation for the related background spacetime. The

Panos Pantidis, Habiba Eldababy, Diab Abueidda, Mostafa E. Mobasher

In this paper, we demonstrate for the first time how the Integrated Finite Element Neural Network (I-FENN) framework, previously proposed by the authors, can efficiently simulate the entire loading history of non-local gradient damage propagation. To achieve this goal, we first adopt a Temporal Convolutional Network (TCN) as the neural network of choice to c

Jing Chen, Zhangpeng Sun, Kai Jiang, Jie Xu

We study four double-gyroid (DG) grain boundaries (GBs) with different orientations numerically using the Landau--Brazovskii free energy, including the (422) twin boundary studied recently, a network switching GB, and two tilt GBs. Topological variations and geometric deformations are investigated. It is found that deviations in strut lengths and dihedral an

Hui Gao

In this paper, we solve a conjecture by Szigeti in [Matroid-rooted packing of arborescences, submitted], which characterizes a mixed hypergraph $\mathcal{F}=(V, \mathcal{E} \cup \mathcal{A})$ having an orientation $\overrightarrow{\mathcal{E}}$ of $\mathcal{E}$ such that $e_{\overrightarrow{\mathcal{E}} \cup \mathcal{A}} (\mathcal{P}) \geq \sum_{X \in \mathc

Ali Shoker, Rehana Yasmin, Paulo Esteves-Verissimo

The increasing interest in Autonomous Vehicles (AV) is notable due to business, safety, and performance reasons. While there is salient success in recent AV architectures, hinging on the advancements in AI models, there is a growing number of fatal incidents that impedes full AVs from going mainstream. This calls for the need to revisit the fundamentals of b

Karim Helwani, Masahito Togami, Paris Smaragdis, Michael M. Goodwin

While neural network approaches have made significant strides in resolving classical signal processing problems, it is often the case that hybrid approaches that draw insight from both signal processing and neural networks produce more complete solutions. In this paper, we present a hybrid classical digital signal processing/deep neural network (DSP/DNN) app

Chen Chen, Ruizhe Li, Yuchen Hu, Sabato Marco Siniscalchi

Recent studies have successfully shown that large language models (LLMs) can be successfully used for generative error correction (GER) on top of the automatic speech recognition (ASR) output. Specifically, an LLM is utilized to carry out a direct mapping from the N-best hypotheses list generated by an ASR system to the predicted output transcription. Howeve

Ziyu Xiang, Hongyuan Li, Jianghan Xiao, Mit H. Naik

The behavior of two-dimensional electron gas (2DEG) in extreme coupling limits are reasonably well-understood, but our understanding of intermediate region remains limited. Strongly interacting electrons crystalize into a solid phase known as the Wigner crystal at very low densities, and these evolve to a Fermi liquid at high densities. At intermediate densi

Samuel Joseph Amouyal, Aya Meltzer-Asscher, Jonathan Berant

In psycholinguistics, the creation of controlled materials is crucial to ensure that research outcomes are solely attributed to the intended manipulations and not influenced by extraneous factors. To achieve this, psycholinguists typically pretest linguistic materials, where a common pretest is to solicit plausibility judgments from human evaluators on speci

Yasas Supeksala, Dinh C. Nguyen, Ming Ding, Thilina Ranbaduge

The rise of Artificial Intelligence (AI) has revolutionized numerous industries and transformed the way society operates. Its widespread use has led to the distribution of AI and its underlying data across many intelligent systems. In this light, it is crucial to utilize information in learning processes that are either distributed or owned by different enti

Behzad Tajahmad

This paper studies inflation and isotropization in the quintom model in the Bianchi I, Bianchi III, and Kantowski-Sachs backgrounds. First, we investigate inherent properties and generalize Heusler's proposition. Then by the use of the dynamical system approach, we consider the system in multiplicative and collective modes of potentials. The conclusions of C

Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao

Machine learning models are susceptible to membership inference attacks (MIAs), which aim to infer whether a sample is in the training set. Existing work utilizes gradient ascent to enlarge the loss variance of training data, alleviating the privacy risk. However, optimizing toward a reverse direction may cause the model parameters to oscillate near local mi

D. Glavan, S. P. Miao, T. Prokopec, R. P. Woodard

Dependence on the graviton gauge enters the conventional effective field equations because they fail to account for quantum gravitational correlations with the source which excites the effective field and with the observer who measures it. Including these correlations has been shown to eliminate gauge dependence in flat space background. We generalize the te

Jay Mardia, Kabir Aladin Verchand, Alexander S. Wein

We consider the problem of detecting a planted clique of size $k$ in a random graph on $n$ vertices. When the size of the clique exceeds $\Theta(\sqrt{n})$, polynomial-time algorithms for detection proliferate. We study faster -- namely, sublinear time -- algorithms in the high-signal regime when $k = \Theta(n^{1/2 + \delta})$, for some $\delta > 0$. To this

Kaixun Tu, Qing Wang

From the ancient Einstein-Podolsky-Rosen paradox to the recent Sorkin-type impossible measurements problem, the contradictions between relativistic causality, quantum non-locality, and quantum measurement have persisted. Based on quantum field theory, our work provides a framework that harmoniously integrates these three aspects. This framework consists of c

Shun-Cai Zhao, Qi-Xuan Wu

We perform the quantum yields in a multi-band quantum dot (QD) photocell via doping an intermediate band (IB) between the conduction band (CB) and valence band (VB). Under two different sub-band gap layouts, the output power has a prominent enhancement than the single-band gap photocell and the achieved peak photo-to-charge efficiency reaches to 74.9% as com

Deheng Song, Christopher Eckner, Chris Gordon, Francesca Calore

The gamma-ray Fermi-LAT Galactic centre excess (GCE) has puzzled scientists for over 15 years. Despite ongoing debates about its properties, and especially its spatial distribution, its nature remains elusive. We scrutinize how the estimated spatial morphology of this excess depends on models for the Galactic diffuse emission, focusing particularly on the ex

Bumsoo Kim, Sanghyun Byun, Yonghoon Jung, Wonseop Shin

In this paper, we first present the character texture generation system \textit{Minecraft-ify}, specified to Minecraft video game toward in-game application. Ours can generate face-focused image for texture mapping tailored to 3D virtual character having cube manifold. While existing projects or works only generate texture, proposed system can inverse the us

Qing-Geng Yang, Kai-Yue Jiang, Da Wang, Hong-Yan Lu

The recent discovery of bulk superconductivity in trilayer nickelate La$_4$Ni$_3$O$_{10}$ with the critical temperature $T_c$ near $30$K under high pressure is attracting a new wave of research interest, after the breakthrough of bilayer La$_3$Ni$_2$O$_7$ with $T_c$ near $80$K. The similarities and differences of electronic structure and superconducting mech

Jianzhao Wang, Weiming An, Rong Tang, Weiyu Meng

The Particle-in-Cell (PIC) simulation has been a widely used method for studying plasma physics. However, fully three-dimensional PIC simulations always require huge computational resources. For problems with near azimuthal symmetry, recent work has shown that expanding all the quantities defined on the grid in azimuthal harmonics and truncating the expansio

Haotong Qin, Xudong Ma, Xingyu Zheng, Xiaoyang Li

The LoRA-finetuning quantization of LLMs has been extensively studied to obtain accurate yet compact LLMs for deployment on resource-constrained hardware. However, existing methods cause the quantized LLM to severely degrade and even fail to benefit from the finetuning of LoRA. This paper proposes a novel IR-QLoRA for pushing quantized LLMs with LoRA to be h

Daria Shaydurova, Volker Kaibel, Sebastian Sager

The moment-sum of squares hierarchy by Lasserre has become an established technique for solving polynomial optimization problems. It provides a monotonically increasing series of tight bounds, but has well-known scalability limitations. For structured optimization problems, the term-sparsity SOS (TSSOS) approach scales much better due to block-diagonal matri

Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis, Aaron Wilson

Large Language Models' success on text generation has also made them better at code generation and coding tasks. While a lot of work has demonstrated their remarkable performance on tasks such as code completion and editing, it is still unclear as to why. We help bridge this gap by exploring to what degree auto-regressive models understand the logical constr

Jaemoo Choi, Jaewoong Choi, Myungjoo Kang

Wasserstein Gradient Flow (WGF) describes the gradient dynamics of probability density within the Wasserstein space. WGF provides a promising approach for conducting optimization over the probability distributions. Numerically approximating the continuous WGF requires the time discretization method. The most well-known method for this is the JKO scheme. In t

Dmitry Kolyaskin, Vladimir V Mangazeev

We study solutions of the reflection equation related to the quantum affine algebra $U_q(\widehat{sl_n})$. First, we explain how to construct a family of stochastic integrable vertex models with fixed boundary conditions. Then, we construct upper- and lower-triangular solutions of the reflection equation related to symmetric tensor representations of $U_q(\w

Yu Tian, Ahmed Alhammadi, Abdullah Quran, Abubakar Sani Ali

In this paper, we address the intricate issue of RF signal separation by presenting a novel adaptation of the WaveNet architecture that introduces learnable dilation parameters, significantly enhancing signal separation in dense RF spectrums. Our focused architectural refinements and innovative data augmentation strategies have markedly improved the model's

Zhenya Zang, Xingda Li, David Day Uei Li

We present a compact spiking convolutional neural network (SCNN) and spiking multilayer perceptron (SMLP) to recognize ten different gestures in dark and bright light environments, using a $9.6 single-photon avalanche diode (SPAD) array. In our hand gesture recognition (HGR) system, photon intensity data was leveraged to train and test the network. A vanilla

Jack Zhang

Enhancing AI systems with efficient communication skills for effective human assistance necessitates proactive initiatives from the system side to discern specific circumstances and interact aptly. This research focuses on a collective building assignment in the Minecraft dataset, employing language modeling to enhance task understanding through state-of-the

Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh

In reinforcement learning, temporal abstraction in the action space, exemplified by action repetition, is a technique to facilitate policy learning through extended actions. However, a primary limitation in previous studies of action repetition is its potential to degrade performance, particularly when sub-optimal actions are repeated. This issue often negat

Shiyuan He, Jianhua Z. Huang, Kejun He

This paper gives a comprehensive treatment of the convergence rates of penalized spline estimators for simultaneously estimating several leading principal component functions, when the functional data is sparsely observed. The penalized spline estimators are defined as the solution of a penalized empirical risk minimization problem, where the loss function b

Saveliy V. Skresanov

The famous Brauer-Fowler theorem states that the order of a finite simple group can be bounded in terms of the order of the centralizer of an involution. Using the classification of finite simple groups, we generalize this theorem and prove that if a simple locally finite group has an involution which commutes with at most $n$ involutions, then the group is

Qing-Song Chang, Guang-Peng Zhang

In this paper we calculate the fully differential cross sections for inclusive heavy quark production in deep-inelastic scattering. We construct proper projection operators to give all possible azimuthal angle distributions of the heavy quark for unpolarized and longitudinally polarized scatterings. These projection operators are expressed in terms of moment

Christopher J. Lynch, Erik Jensen, Madison H. Munro, Virginia Zamponi

Large Language Models (LLMs) play a pivotal role in generating vast arrays of narratives, facilitating a systematic exploration of their effectiveness for communicating life events in narrative form. In this study, we employ a zero-shot structured narrative prompt to generate 24,000 narratives using OpenAI's GPT-4. From this dataset, we manually classify 2,8

Zhengding Luo, Dongyuan Shi, Xiaoyi Shen, Woon-Seng Gan

Delayless noise control is achieved by our earlier generative fixed-filter active noise control (GFANC) framework through efficient coordination between the co-processor and real-time controller. However, the one-dimensional convolutional neural network (1D CNN) in the co-processor requires initial training using labelled noise datasets. Labelling noise data

Aparna M. P., P. Paramanathan

The fundamental aim of this paper is to provide the approximation and numerical integration of a discrete set of data points with Bernstein fractal approach. Using Bernstein polynomials in the iterated function system, the paper initially proposes the numerical integration formula for the data set corresponding to univariate functions. The proposed formula o

Diyath Pannipitiya

The goal of this paper is to discuss about the hyperbolicity of the non-wandering set $\mathcal{NW}(f_c)$ of real quadratic function $f_c(x)=x^2+c$ when $c\in (-\infty, -2]$. Even though the results we present here are not new, it is not easier to find the proofs of them. We present two different ways to prove the hyperbolicity of $\mathcal{NW}(f_c)$ for the