December 2023 arXiv papers — page 27

Xiangyuan Xue, Kailing Wang, Jiazi Bu, Qirui Li

In this work, we propose MetaScript, a novel Chinese content generation system designed to address the diminishing presence of personal handwriting styles in the digital representation of Chinese characters. Our approach harnesses the power of few-shot learning to generate Chinese characters that not only retain the individual's unique handwriting style but

Mouhamed Naby Ndiaye, El Houcine Bergou, Hajar El Hammouti

Unmanned aerial vehicles (UAVs) are a highly promising technology with diverse applications in wireless networks. One of their primary uses is the collection of time-sensitive data from Internet of Things (IoT) devices. In UAV-assisted networks, the Age-of-Information (AoI) serves as a fundamental metric for quantifying data timeliness and freshness. In this

Parinya Karndumri, Patharadanai Nuchino

We continue our study of gaugings the maximal $N=(2,2)$ supergravity in six dimensions with gauge groups obtained from decomposing the embedding tensor under $\mathbb{R}^+\times SO(4,4)$ subgroup of the global symmetry $SO(5,5)$. Supersymmetry requires the embedding tensor to transform in $\mathbf{144}_c$ representation of $SO(5,5)$. Under $\mathbb{R}^+\time

Jiawei Yan, Philipp Werner

We present a nonequilibrium steady-state implementation of the two-particle self-consistent method. This approach respects the Mermin-Wagner theorem and incorporates non-local spatial fluctuations through self-consistent static vertices. The real-frequency implementation allows to compute spectral properties without analytical continuation in both equilibriu

Paul Gustafson, Mee Seong Im, Mikhail Khovanov

Any finite state automaton gives rise to a Boolean one-dimensional TQFT with defects and inner endpoints of cobordisms. This paper extends the correspondence to Boolean TQFTs where defects accumulate toward inner endpoints, relating such TQFTs and topological theories to sofic systems and $\omega$-automata.

Anqi Yi, Nantheera Anantrasirichai

Accurate object tracking in low-light environments is crucial, particularly in surveillance and ethology applications. However, achieving this is significantly challenging due to the poor quality of captured sequences. Factors such as noise, color imbalance, and low contrast contribute to these challenges. This paper presents a comprehensive study examining

Kamila Dębowska, Irina L. Nizhnik

The paper considers the general form of self-adjoint boundary value problems for momentum operators with nonlocal potentials. We give an analysis of the eigenvalue distribution as zeros of the characteristic functions, for which their explicit representations are obtained in terms of nonlocal potentials.

Yueqi Sheng, Qiang Wu

The Ghatak-Sherrington (GS) spin glass model is a random probability measure defined on the configuration space $\{0,\pm1,\pm2,\ldots, \pm \mathcal{S} \}^N$ with system size $N$ and $\mathcal{S}\ge1$ finite. This generalizes the classical Sherrington-Kirkpatrick (SK) model on the boolean cube $\{-1,+1\}^N$ in order to capture more complex behaviors, includin

Boris Shklovskii

A macroion with a strongly charged negative surface in 3:1 salt water solution becomes net positive due to adsorption of an excessive number of positive 3-ions. The widely accepted theory of such charge inversion is based on the idea that adsorbed at the macroion surface 3-ions form a two-dimensional strongly correlated liquid which attracts excessive 3-ions

Anna Balci, Lars Diening, Mikhail Surnachev

We present a general procedure to construct examples of convex scalar variational problems which admit a minimizers with large singular sets. The dimension of the set of singularities is maximal and the minimizer has no higher integrability property (failure of Meyers property).

Adwait Verulkar, Corina Sandu, Adrian Sandu, Daniel Dopico

Real-world multibody systems are often subject to phenomena like friction, joint clearances, and external events. These phenomena can significantly impact the optimal design of the system and its controller. This work addresses the gradient-based optimization methodology for multibody dynamic systems with joint friction using a direct sensitivity approach fo

Xiang Wang, Shiwei Zhang, Hangjie Yuan, Zhiwu Qing

Diffusion-based text-to-video generation has witnessed impressive progress in the past year yet still falls behind text-to-image generation. One of the key reasons is the limited scale of publicly available data (e.g., 10M video-text pairs in WebVid10M vs. 5B image-text pairs in LAION), considering the high cost of video captioning. Instead, it could be far

Sepehr Nourmohammadi, Shervin Rahimzadeh Arashloo

Classifier fusion is established as an effective methodology for boosting performance in different settings and one-class classification is no exception. In this study, we consider the one-class classifier fusion problem by modelling the sparsity/uniformity of the ensemble. To this end, we formulate a convex objective function to learn the weights in a linea

Yuanjing Ji

Hypernuclei are bound states of nuclei with one or more hyperons. Precise measurements of hypernuclei properties and their production yields in heavy ion collisions are crucial for the understanding of their production mechanisms. The second phase of the Beam Energy Scan at RHIC (BES-II) offers us a great opportunity to investigate collision energy and syste

Spyros Basilakos, Andreas Lymperis, Maria Petronikolou, Emmanuel N. Saridakis

We construct Barrow holographic dark energy with varying exponent. Such an energy-scale-dependent behavior is typical in quantum field theory and quantum gravity under renormalization group considerations, however in the present scenario it has an additional justification, since in realistic cases one expects that Barrow entropy quantum-gravitational effects

Kamil Mudrunka, Kazunori Nakayama

The low energy effective action of quantum gravity may include the higher curvature terms such as the Gauss-Bonnet term. The inflaton dynamics may be affected by the Gauss-Bonnet term if there is an inflaton-Gauss-Bonnet coupling. We show that an inflation model with a simple power law potential is made viable if it is coupled to the Gauss-Bonnet term since

S. Frey, Y. Zhang, K. Perger, T. An

The existence of accreting supermassive black holes up to billions of solar masses at early cosmological epochs (in the context of this work, redshifts z>=6) requires very fast growth rates which is challenging to explain. The presence of a relativistic jet can be a direct indication of activity and accretion status in active galactic nuclei (AGN), constrain

Alex Buchel

Conformal order are isotropic and translationary invariant thermal states of a conformal theory with nonzero expectation value of certain operators. While ubiquitous in bottom-up models of holographic CFTs, conformal order states are unstable in theories dual to bulk two-derivative gravity. We explore conformal order in strongly coupled theories with gravita

Rasagna Chigullapally, Harshithanjani Athi, Nikhil Karamchandani, V. Lalitha

We consider a distributed multi-user secret sharing (DMUSS) setting in which there is a dealer, $n$ storage nodes, and $m$ secrets. Each user demands a $t$-subset of $m$ secrets. Earlier work in this setting dealt with the case of $t=1$; in this work, we consider general $t$. The user downloads shares from the storage nodes based on the designed access struc

Xu Wang, Jiawei Huang, Qingyuan Yang, Jinpeng Zhang

The Wasserstein barycenter problem is to compute the average of $m$ given probability measures, which has been widely studied in many different areas; however, real-world data sets are often noisy and huge, which impedes its applications in practice. Hence, in this paper, we focus on improving the computational efficiency of two types of robust Wasserstein b

Soumak Maitra

Higher order clustering statistics of Ly$\alpha$ forest provide a unique probe to study non-gaussianity in Intergalactic matter distribution up to high redshifts and from large to small scales. The author presents a brief review of his work studying the spatial clustering properties of Ly$\alpha$ absorbers, with emphasis on 3-point statistics. The observatio

Yi-Gao Liu, Chen-Kai Qiao, Jun Tao

The gravitational lensing of supermassive black holes surrounded by dark matter halo has attracted a great number of interests in recent years. However, many studies employed simplified dark matter density models, which makes it very hard to give a precise prediction on the dark matter effects in real astrophysical galaxies. In this work, to more accurately

Minh Le

The objective is to investigate the global existence of solutions for a degenerate chemotaxis system with logistic sources in a two-dimensional domain. It is demonstrated that the inclusion of logistic sources can exclude the occurrence of blow-up solutions, even in the presence of superlinear growth in the cross-diffusion rate. Our proof relies on the appli

Tomohiro Shitara, Yosuke Mitsuhashi, Hiroyasu Tajima

We identify exact and approximate conversion rates between i.i.d. pure states under covariant operations in the resource theory of asymmetry for symmetries described by finite groups. We establish the formula for the exact conversion rate by completely specifying the relevant set of resource measures. The exact conversion is generally asymptotically irrevers

Zheng Zhang, Yuanwei Liu, Zhaolin Wang, Jian Chen

A novel dynamic hybrid beamforming architecture is proposed to achieve the spatial multiplexing-power consumption tradeoff for near-field multiple-input multiple-output (MIMO) networks, where each radio frequency (RF) chain is connected to each antenna using a couple of independent phase shifters to reduce the number of required RF chains. Based on this arch

Baoshan Xi

In these proceedings, we present new measurements from STAR of the global spin alignment($\rho_{00}$) of $\phi$ mesons in Au+Au collisions at $\sqrt{s_{\mathrm{NN}}}$ = 19.6, 14.6 GeV using BES-II data and of $J/\psi$ mesons in isobar collisions ${ }_{44}^{96} \mathrm{Ru}+{ }_{44}^{96} \mathrm{Ru}$ and ${ }_{40}^{96} \mathrm{Zr}+{ }_{40}^{96} \mathrm{Zr}$ at

Rong Zhang, Long-Xing Huang, Yong-Qiang Wang

In this paper, we construct the rotating multistate Proca stars (RMPSs) composed of two coexisting Proca fields including the ground state and first excited state. We consider the solution families of RMPSs in synchronized frequency and non-synchronized frequency scenarios, respectively. We discuss the characteristics of the matter fields changing with the s

Ryoya Arimoto

We prove that if a totally disconnected locally compact group admits a topologically free boundary, then the reduced crossed product of continuous functions on its Furstenberg boundary by the group is simple. We also prove a partial converse of this result.

Julia Zotova, Shtefan Sanduleanu, Gleb Fedorov, Rui Wang

We demonstrate control and readout of a superconducting artificial atom based on a transmon qubit using a compact lumped-element resonator. The resonator consists of a parallel-plate capacitor (PPC) with a wire geometric inductor. The footprint of the resonators is about 200 {\mu}m by 200 {\mu}m, which is similar to the standard transmon size and one or two

Shuocheng Xu, Ruiyu Zhou, Wei Cheng, Xuewen Liu

We investigate the temperature-dependent production of feebly interacting massive dark matter particle (FIMP DM) within a $Z_2$ model, incorporating two $Z_2$-odd scalar fields. In specific parameter regions, three distinct mechanisms individually dominate the production of the FIMP DM. These mechanisms include the semi-production process, commonly known as

Dong Pham, Xanh Ho, Quang-Thuy Ha, Akiko Aizawa

Scientific Information Extraction (ScientificIE) is a critical task that involves the identification of scientific entities and their relationships. The complexity of this task is compounded by the necessity for domain-specific knowledge and the limited availability of annotated data. Two of the most popular datasets for ScientificIE are SemEval-2018 Task-7

Partha Nandi, Frederik G. Scholtz

This paper introduces a systematic algorithm for deriving a new unitary representation of the Lorentz algebra ($so(1,3)$) and an irreducible unitary representation of the extended (anti) de-Sitter algebra ($so(2,4)$) on $\mathcal{L}^{2}(\mathcal{R}^{3},\frac{1}{r})$. This representation is equivalent to a representation on $\mathcal{L}^{2}(\mathcal{R}^{3})$,

Kenichi Nagaoka, Haruhisa Nakano, Taiga Hamajima, Ryoya Nakamoto

Beam-focusing characteristics of negative ion beams have been experimentally investigated with a superimposition of a controlled perturbation of RF field in a filament-arc discharge negative ion source. Oscillations of a negative-ion beamlet width and axis responding to the RF perturbation were observed, which may be a cause of the larger beam divergence ang

Erin Carmody

This paper analyzes infinitary nondeterministic computability theory. The main result is D $\ne$ ND $\cap$ coND where D is the class of sets decidable by infinite time Turing machines and ND is the class of sets recognizable by a nondeterministic infinite time Turing machine. Nondeterministic infinite time Turing machines are introduced, along with relevant

Michael Souza, Luiz M. Carvalho, Douglas Augusto, Jairo Panetta

Within high-performance computing (HPC), solving large sparse linear systems efficiently remains paramount, with iterative methods being the predominant choice. However, the performance of these methods is tightly coupled to the aptness of the chosen preconditioner. The multifaceted nature of sparse matrices makes the universal prescription of preconditioner

Yuri G. Zarhin

Let $\ell$ be an odd prime and $K$ a field of characteristic different from $\ell$. Let $\bar{K}$ be an algebraic closure of $K$. Assume that $K$ contains a primitive $\ell$th root of unity. Let $n \ne \ell$ be another odd prime. Let $f(x)$ and $h(x)$ be degree $n$ polynomials with coefficients in $K$ and without repeated roots. Let us consider superelliptic

Tianhui Ma, Yuan Cheng, Hengshu Zhu, Hui Xiong

With the significant successes of large language models (LLMs) in many natural language processing tasks, there is growing interest among researchers in exploring LLMs for novel recommender systems. However, we have observed that directly using LLMs as a recommender system is usually unstable due to its inherent position bias. To this end, we introduce explo

Karamat Beigi, Hamed Shah-Mansouri

Indoor positioning plays a pivotal role in a wide range of applications, from smart homes to industrial automation. In this paper, we propose a comprehensive approach for accurate positioning in indoor environments through the integration of existing Wi-Fi and Bluetooth Low Energy (BLE) devices. The proposed algorithm involves acquiring the received signal s

R. A. Konoplya

During the ringdown phase of a gravitational signal emitted by a black hole, the least damped quasinormal frequency dominates. If modifications to Einstein's theory induce noticeable deformations of the black-hole geometry only near the event horizon, the fundamental mode remains largely unaffected. However, even a small change near the event horizon can sig

Wenzhang Liu, Wenzhe Cai, Kun Jiang, Guangran Cheng

In this paper, we present XuanCe, a comprehensive and unified deep reinforcement learning (DRL) library designed to be compatible with PyTorch, TensorFlow, and MindSpore. XuanCe offers a wide range of functionalities, including over 40 classical DRL and multi-agent DRL algorithms, with the flexibility to easily incorporate new algorithms and environments. It

Yifan Qi, Xingyu Jia, Jingyi Wang, Weiwei Yang

Artificial intelligence empowered autonomous vehicles and robotics have to sense the fast-changing three-dimensional environment with high precision and speed. However, it is challenging for the state-of-the-art ambiguity-free light detection and ranging (LiDAR) techniques to achieve absolute distance measurement with simultaneous high precision and high acq

Li Xiang, Junbo Yin, Wei Li, Cheng-Zhong Xu

Vehicle-to-Everything (V2X) collaborative perception has recently gained significant attention due to its capability to enhance scene understanding by integrating information from various agents, e.g., vehicles, and infrastructure. However, current works often treat the information from each agent equally, ignoring the inherent domain gap caused by the utili

Wenlong Liao, Fernando Porte-Agel, Jiannong Fang, Birgitte Bak-Jensen

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecasted errors are severely limited by the local optimal weight issue in optimization algorithms, and their forecasted behavior also lacks interpretability. To address these two

Lin Sun, Weijun Wang, Tingting Yuan, Liang Mi

High-definition (HD) cameras for surveillance and road traffic have experienced tremendous growth, demanding intensive computation resources for real-time analytics. Recently, offloading frames from the front-end device to the back-end edge server has shown great promise. In multi-stream competitive environments, efficient bandwidth management and proper sch

Xingyong Zhang, Xiaoli Yu

This paper is mainly concerned with the existence of ground state sign-changing solutions for a class of second order quasilinear elliptic equations in bounded domains which derived from nonlinear optics models. Combining a non-Nehari manifold method due to Tang and Cheng [31] and a quantitative deformation lemma with Miranda theorem, we obtain that the prob

Raihan Kabir, Yutaka Watanobe, Md. Rashedul Islam, Keitaro Naruse

An efficient robot path-planning model is vulnerable to the number of search nodes, path cost, and time complexity. The conventional A-star (A*) algorithm outperforms other grid-based algorithms for its heuristic search. However it shows suboptimal performance for the time, space, and number of search nodes, depending on the robot motion block (RMB). To addr

Constantia Alexandrou, Giannis Koutsou, Yan Li, Marcus Petschlies

We investigate contributions of excited states to nucleon matrix elements by studying the two- and three-point functions using nucleon and pion-nucleon interpolating fields. This study is carried out using twisted mass fermion ensembles with pion masses 346 MeV and 131 MeV. We compare the results obtained using these two ensembles and show preliminary result

Xiaoxu Chen, Jingfan Tan, Tao Wang, Kaihao Zhang

Blind face restoration is an important task in computer vision and has gained significant attention due to its wide-range applications. Previous works mainly exploit facial priors to restore face images and have demonstrated high-quality results. However, generating faithful facial details remains a challenging problem due to the limited prior knowledge obta

Yuxuan Zhou, Wenming Zou

In this paper, we establish several improved Caffarelli-Kohn-Nirenberg and Hardy-type inequalities. Our main results are divided into two parts. In the first part, we consider the following Caffarelli-Kohn-Nirenberg inequality: \begin{equation*} \left(\int_{\mathbb{R}^n}|x|^{-pa}|\nabla u|^pdx\right)^{\frac{1}{p}}\geq S(p,a,b)\left(\int_{\mathbb{R}^n}|x|^{-q

Ilya Chevyrev, Alexey Korepanov, Ian Melbourne

We consider deterministic fast-slow dynamical systems of the form \[ x_{k+1}^{(n)} = x_k^{(n)} + n^{-1} A(x_k^{(n)}) + n^{-1/\alpha} B(x_k^{(n)}) v(y_k), \quad y_{k+1} = Ty_k, \] where $\alpha\in(1,2)$ and $x_k^{(n)}\in{\mathbb R}^m$. Here, $T$ is a slowly mixing nonuniformly hyperbolic dynamical system and the process $W_n(t)=n^{-1/\alpha}\sum_{k=1}^{[nt]}v

Yu-Li Lee

We study the physics of dilute magnetic impurities in a two-dimensional altermagnetic metal. For the single impurity case, although the spin degeneracy is broken in an altermagnetic metal, we show that the antiferromagnetic Kondo coupling still flows to the strong coupling regime at low energies in terms of the one-loop renormalization-group equation. Moreov

Christian De Nicola Larsen

Jones' technology, developed by Vaughan Jones during his exploration of the connections between conformal field theory and subfactors, is a powerful mechanism for generating actions of groups coming from categories, notably Richard Thompson's groups $F \subseteq T \subseteq V$. We give a structure theorem for the isomorphisms between split extensions of Thom

Jing Wang, Jinagyun Li, Chen Chen, Yisi Zhang

The Few-Shot Segmentation (FSS) aims to accomplish the novel class segmentation task with a few annotated images. Current FSS research based on meta-learning focus on designing a complex interaction mechanism between the query and support feature. However, unlike humans who can rapidly learn new things from limited samples, the existing approach relies solel

Maochun Xu, Zixun Lan, Zheng Tao, Jiawei Du

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the domain of Quantitative Trading (QT) through the deployment of advanced algorithms capable of sifting through extensive financial datasets to pinpoint lucrative investment openings. AI-driven models, particularly those employing ML techniques such as deep learning and reinforcement le

Abdalaziz Sawwan, Jie Wu

This paper explores mobile crowdsensing, which leverages mobile devices and their users for collective sensing tasks under the coordination of a central requester. The primary challenge here is the variability in the sensing capabilities of individual workers, which are initially unknown and must be progressively learned. In each round of task assignment, th

Yiming Xia, Zixian Hu, Da Wei, Ke Chen

Direct mechanical coupling is known to be critical for establishing synchronization among cilia. However, the actual role of the connections is still elusive - partly because controlled experiments in live samples are challenging. Here, we employ an artificial ciliary system to address this issue. Two cilia are formed by chains of self-propelling robots and

Zehao Dong, Mengwu Huo, Jie Li, Jingyuan Li

The recent discovery of superconductivity in La3Ni2O7-{\delta} under high pressure with a transition temperature around 80 K has sparked extensive experimental and theoretical efforts. Several key questions regarding the pairing mechanism remain to be answered, such as the most relevant atomic orbitals and the role of atomic deficiencies. Here, we develop a

Krzysztof Bartosz, Pawel Szafraniec

In this work, we analyse a simplified frictional contact problem and its variational formulation that has a form of the elliptic variational inequality of the second kind. For this problem, we consider a numerical approximation based on virtual element method (VEM). The novelty of our approach consists in the fact that we deal with a discontinuous version of

Reza Sameni

Multimodality and multichannel monitoring have become increasingly popular and accessible in engineering, Internet of Things, wearable devices, and biomedical applications. In these contexts, given the diverse and complex nature of data modalities, the relevance of sensor fusion and sensor selection is heightened. In this note, we study the problem of channe

Hiroyuki Tajima, Yuta Sekino, Daisuke Inotani, Akira Dohi

We theoretically investigate non-Hermitian $p$-wave Fermi superfluidity in one-dimensional spin-polarized Fermi gases which is relevant to recent ultracold atomic experiments. Considering an imaginary atom-dimer coupling responsible for the three-body recombination process in the Lindblad formalism, we discuss the stability of the superfluid state against th

Krzysztof Bartosz, Paweł Szafraniec

In this paper we deal with a second order evolution inclusion involving a multivalued term generated by a Clarke subdifferential of a locally Lipschitz potential. For this problem we construct a double step time-semidiscrete approximation, known as the Rothe scheme. We study a sequence of solutions of the semidiscrete approximate problems and provide its wea

Mohamed Abdalmoaty, Jared Miller, Mingzhou Yin, Roy S. Smith

We propose a computationally tractable method for the identification of stable canonical discrete-time rational transfer function models, using frequency domain data. The problem is formulated as a global non-convex optimization problem whose objective function is the sum of weighted squared residuals at each observed frequency datapoint. Stability is enforc

Yian Zhu, Ziye Jia, Qihui Wu, Chao Dong

With the increasing use of autonomous unmanned aerial vehicles (UAVs), it is critical to ensure that they are continuously tracked and controlled, especially when UAVs operate beyond the communication range of ground stations (GSs). Conventional surveillance methods for UAVs, such as satellite communications, ground mobile networks and radars are subject to

Yifan Lu, Ziqi Zhang, Chunfeng Yuan, Peng Li

Diverse video captioning aims to generate a set of sentences to describe the given video in various aspects. Mainstream methods are trained with independent pairs of a video and a caption from its ground-truth set without exploiting the intra-set relationship, resulting in low diversity of generated captions. Different from them, we formulate diverse caption

Zhifan Zhu, Dima Damen

We propose the task of Hand-Object Stable Grasp Reconstruction (HO-SGR), the reconstruction of frames during which the hand is stably holding the object. We first develop the stable grasp definition based on the intuition that the in-contact area between the hand and object should remain stable. By analysing the 3D ARCTIC dataset, we identify stable grasp du

Yuqia Wu, Shaohua Pan, Xiaoqi Yang

We are concerned with structured $\ell_0$-norms regularization problems, with a twice continuously differentiable loss function and a box constraint. This class of problems have a wide range of applications in statistics, machine learning and image processing. To the best of our knowledge, there is no effective algorithm in the literature for solving them. I

Safal Choudhary, Princy Randhawa, Sampath Kumar P Jinka, Shiva Prasad H. C

Juvenile Idiopathic Arthritis (JIA) is a widespread and chronic condition that affects children and adolescents worldwide. The person suffering from JIA is characterized by chronic joint inflammation leading to pain, swelling, stiffness, and limited body movements. Individuals suffering from JIA require ongoing treatment for their lifetime. Beyond inflammati

Zhaofan Zhang, Yanan Xiao, Lu Jiang, Dingqi Yang

In the realm of human mobility, the decision-making process for selecting the next-visit location is intricately influenced by a trade-off between spatial and temporal constraints, which are reflective of individual needs and preferences. This trade-off, however, varies across individuals, making the modeling of these spatial-temporal dynamics a formidable c

Manzi Nan, Pengcheng Li, Yongjia Wang, Qingfeng Li

In heavy-ion collisions at intermediate energies, the production and propagation of $\Delta$ particles are crucial to understanding the nuclear equation of state and inferring the properties of nuclear matter at high densities. Based on the self-consistent relativistic Boltzmann-Uehling-Uhlenbeck (RBUU) transport theory, by introducing the isovector $\rho$ m

Li Xin Jed Lim, Ziming Qiu

Muon scattering tomography utilises muons, typically originating from cosmic rays to image the interiors of dense objects. However, due to the low flux of cosmic ray muons at sea-level and the highly complex interactions that muons display when travelling through matter, existing reconstruction algorithms often suffer from low resolution and high noise. In t

Jiannan Wu, Yi Jiang, Bin Yan, Huchuan Lu

The reference-based object segmentation tasks, namely referring image segmentation (RIS), few-shot image segmentation (FSS), referring video object segmentation (RVOS), and video object segmentation (VOS), aim to segment a specific object by utilizing either language or annotated masks as references. Despite significant progress in each respective field, cur

Yi Zhang, Hong Liu, Dan Wen, Hongsheng Zhang

For the first time, we use the Event Horizon Telescope (EHT) data to constrain the parameters of braneworld black holes which constrain $\epsilon=0.0285^{+0.0888+0.1456}_{-0.0895-0.1475}$ for the anisotropic black hole and $q=-0.0305^{+0.1034+0.1953}_{-0.0895-0.1470}$ for the tidal Reissner-Nordstr$\ddot{o}$m (RN) black hole. Based on the fitted data and phy

Mohammad Amin Abbasi, Arash Ghafouri, Mahdi Firouzmandi, Hassan Naderi

Despite the widespread use of the Persian language by millions globally, limited efforts have been made in natural language processing for this language. The use of large language models as effective tools in various natural language processing tasks typically requires extensive textual data and robust hardware resources. Consequently, the scarcity of Persia

Yongguang Xing, Zhenping Yi, Zengxu Liang, Hao Su

Low-surface-brightness galaxies (LSBGs), fainter members of the galaxy population, are thought to be numerous. However, due to their low surface brightness, the search for a wide-area sample of LSBGs is difficult, which in turn limits our ability to fully understand the formation and evolution of galaxies as well as galaxy relationships. Edge-on LSBGs, due t

Thomson TG, Jeppe Revall Frisvad, Ravi Ramamoorthi, Henrik Wann Jensen

Monte Carlo rendering of translucent objects with heterogeneous scattering properties is often expensive both in terms of memory and computation. If we do path tracing and use a high dynamic range lighting environment, the rendering becomes computationally heavy. We propose a compact and efficient neural method for representing and rendering the appearance o

Shi Guo, Jianqi Ma, Xi Yang, Zhengqiang Zhang

Denoising and demosaicking are two fundamental steps in reconstructing a clean full-color video from raw data, while performing video denoising and demosaicking jointly, namely VJDD, could lead to better video restoration performance than performing them separately. In addition to restoration accuracy, another key challenge to VJDD lies in the temporal consi

Yue Zhang, Leyang Cui, Wei Bi, Shuming Shi

Despite their impressive capabilities, large language models (LLMs) have been observed to generate responses that include inaccurate or fabricated information, a phenomenon commonly known as ``hallucination''. In this work, we propose a simple \textit{Induce-then-Contrast} Decoding (ICD) strategy to alleviate hallucinations. We first construct a factually we

Jiexi Liu, Songcan Chen

Learning universal time series representations applicable to various types of downstream tasks is challenging but valuable in real applications. Recently, researchers have attempted to leverage the success of self-supervised contrastive learning (SSCL) in Computer Vision(CV) and Natural Language Processing(NLP) to tackle time series representation. Neverthel

Andong Lu, Chenglong Li, Tianrui Zha, Jin Tang

Prevalent nighttime person re-identification (ReID) methods typically combine image relighting and ReID networks in a sequential manner. However, their performance (recognition accuracy) is limited by the quality of relighting images and insufficient collaboration between image relighting and ReID tasks. To handle these problems, we propose a novel Collabora

Luca Barberi, Karsten Kruse

From cytoskeletal networks to tissues, many biological systems behave as active materials. Their composition and stress-generation is affected by chemical reaction networks. In such systems, the coupling between mechanics and chemistry enables self-organization, for example, into waves. Recently, contractile mechanochemical systems were shown to be able to s

Chen Hou, Guoqiang Wei, Zhibo Chen

Diffusion models have attained remarkable success in the domains of image generation and editing. It is widely recognized that employing larger inversion and denoising steps in diffusion model leads to improved image reconstruction quality. However, the editing performance of diffusion models tends to be no more satisfactory even with increasing denoising st

Christian Kanzow, Felix Weiß

We consider the general nonlinear optimization problem where the objective function has an additional term defined by the $ \ell_0 $-quasi-norm in order to promote sparsity of a solution. This problem is highly difficult due to its nonconvexity and discontinuity. We generalize some recent work and present a whole class of reformulations of this problem consi

Priya Ghosh, Chirag Srivastava, Swati Choudhary, Ujjwal Sen

Two important ingredients necessary for obtaining Bell nonlocal correlations between two spatially separated parties are an entangled state shared between them and an incompatible set of measurements employed by each of them. We focus on the relation of Bell nonlocality with incompatibility of the set of measurements employed by both the parties, in the two-

Roozbeh Hazrat, Tran Giang Nam

In this article, we describe the endomorphism ring of a finitely generated progenerator module of a weighted Leavitt path algebra $L_{K}(E, w)$ of a finite vertex weighted graph $(E, w)$. Contrary to the case of Leavitt path algebras, we show that a (full) corner of a weighted Leavitt path algebra is, in general, not isomorphic to a weighted Leavitt path alg

Rimma Dzhusupova, Jan Bosch, Helena Holmstrom Olsson

The Engineering, Procurement and Construction (EPC) businesses operating within the energy sector are recognizing the increasing importance of Artificial Intelligence (AI). Many EPC companies and their clients have realized the benefits of applying AI to their businesses in order to reduce manual work, drive productivity, and streamline future operations of

Shaonwita Pal, Dibyendu Nandy

The solar cycle is generated by a magnetohydrodynamic dynamo mechanism which involves the induction and recycling of the toroidal and poloidal components of the Sun's magnetic field. Recent observations indicate that the Babcock-Leighton mechanism -- mediated via the emergence and evolution of tilted bipolar active regions -- is the primary contributor to th

Chengcheng Ma, Ismail Elezi, Jiankang Deng, Weiming Dong

We address the challenging problem of Long-Tailed Semi-Supervised Learning (LTSSL) where labeled data exhibit imbalanced class distribution and unlabeled data follow an unknown distribution. Unlike in balanced SSL, the generated pseudo-labels are skewed towards head classes, intensifying the training bias. Such a phenomenon is even amplified as more unlabele

Jiahong Fu, Qi Xie, Deyu Meng, Zongben Xu

The deep unfolding approach has attracted significant attention in computer vision tasks, which well connects conventional image processing modeling manners with more recent deep learning techniques. Specifically, by establishing a direct correspondence between algorithm operators at each implementation step and network modules within each layer, one can rat

Yunhao Du, Cheng Lei, Zhicheng Zhao, Fei Su

Referring multi-object tracking (RMOT) aims to track multiple objects based on input textual descriptions. Previous works realize it by simply integrating an extra textual module into the multi-object tracker. However, they typically need to retrain the entire framework and have difficulties in optimization. In this work, we propose an insertable Knowledge U

Eqab. M. Rabei, Mohamed Ghaleb Al-Masaeed, Sami I. Muslih, Dumitru Baleanu

In this work, we extend the time-dependent conformable Schr\"odinger equation for a fractional dimensional system of N spatial coordinates to be used as an effective description of anisotropic and confined systems. A specific example is looked at in free particle conformable Schr\"odinger wave mechanics, particularly in N-Polar coordinates and N-Cartesian co

Weicheng Huang, Tian Yu, Dominic Vella, K. Jimmy Hsia

In this paper, we systematically study the dynamic snap-through behavior of a pre-deformed elastic ribbon by combining theoretical analysis, discrete numerical simulations, and experiments. By rotating one of its clamped ends with controlled angular speed, we observe two snap-through transition paths among the multiple stable configurations of a ribbon in th

André Silva, Sen Fang, Martin Monperrus

Automated Program Repair (APR) has evolved significantly with the advent of Large Language Models (LLMs). Fine-tuning LLMs for program repair is a recent avenue of research, with many dimensions which have not been explored. Existing work mostly fine-tune LLMs with naive code representations and does not scale to frontier models. To address this problem, we

I. V. Voronchikhin, D. V. Kirpichnikov

We discuss the thermal target curves of Majorana, Dirac, scalar and vector light dark matter (DM) that are associated with the freeze-out mechanism via the annihilation into $e^+e^-$ pair through the electron-specific spin-0 mediator of dark matter. We also discuss the mechanism to produce the regarding DM mediator in the electron (positron) fixed-target exp

Andong Lu, Jiacong Zhao, Chenglong Li, Jin Tang

Current RGBT tracking research relies on the complete multi-modal input, but modal information might miss due to some factors such as thermal sensor self-calibration and data transmission error, called modality-missing challenge in this work. To address this challenge, we propose a novel invertible prompt learning approach, which integrates the content-prese

Shirong Ma, Shen Huang, Shulin Huang, Xiaobin Wang

Large Language Models (LLMs) pre-trained on massive corpora have exhibited remarkable performance on various NLP tasks. However, applying these models to specific domains still poses significant challenges, such as lack of domain knowledge, limited capacity to leverage domain knowledge and inadequate adaptation to domain-specific data formats. Considering th

Mohamed Erraoui, Michael Röckner, José Luís da Silva

In this paper, we study the quasi-invariant property of a class of non-Gaussian measures. These measures are associated with the family of generalized grey Brownian motions. We identify the Cameron--Martin space and derive the explicit Radon-Nikodym density in terms of the Wiener integral with respect to the fractional Brownian motion. Moreover, we show an i

Smriti Mahajan, Kulinderpal Singh, Somak Raychaudhury

(abridged) We present the newly acquired data for an AstroSat/UVIT field centered on a face-on spiral starburst galaxy UGC 10420, located in the cluster Abell 2199. We have analysed the FUV data for this field along with the archival data from the Galex mission, optical photometric data from the SDSS, and low-frequency radio data from the LoTSS survey, respe

Shyam Dhamapurkar, Yuhang Dang, Saniya Wagh, Xiu-Hao Deng

Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science. The mixing property is necessary for Markov chains to approach stationary distributions and is facilitated by walks. Quantum walks show promise for faster mixing times than classical methods but lack universal proof, especially

Songming Zhang, Yuxiao Luo, Qizhou Wang, Haoang Chi

Deep neural networks often face generalization problems to handle out-of-distribution (OOD) data, and there remains a notable theoretical gap between the contributing factors and their respective impacts. Literature evidence from in-distribution data has suggested that generalization error can shrink if the size of mixture data for training increases. Howeve

Weidong Guo, Jiuding Yang, Kaitong Yang, Xiangyang Li

The fine-tuning of Large Language Models (LLMs) specialized in code generation has seen notable advancements through the use of open-domain coding queries. Despite the successes, existing methodologies like Evol-Instruct encounter performance limitations, impeding further enhancements in code generation tasks. This paper examines the constraints of existing