May 2023 arXiv papers — page 152

Haonan Wang, Minbin Huang, Runhui Huang, Lanqing Hong

Contrastive Language-Image Pre-training (CLIP) has become the standard for cross-modal image-text representation learning. Improving CLIP typically requires additional data and retraining with new loss functions, but these demands raise resource and time costs, limiting practical use. In this work, we introduce HELIP, a cost-effective strategy that improves

Jiazhen Shao, Igor P. Ivanov

Multi-Higgs models equipped with global symmetry groups, either exact or softly broken, offer a rich framework for constructions beyond the Standard Model and lead to remarkable phenomenological consequences. Knowing all the symmetry options within each class of models can guide its phenomenological exploration, as confirmed by the vast literature on the two

Andrei Constantinescu, Diana Ghinea, Lioba Heimbach, Zilin Wang

Traditional blockchain design gives miners or validators full control over transaction ordering, i.e., they can freely choose which transactions to include or exclude, as well as in which order. While not an issue initially, the emergence of decentralized finance has introduced new transaction order dependencies allowing parties in control of the ordering to

Kacper Hulek, Mariusz Pawlicki, Adrian Ostrowski, Jakub Możaryn

The paper describes of the Ryze Tello drone to move autonomously using a basic vision system. The drone's position is determined by identifying AprilTags' position relative to the drone's built-in camera. The accuracy of the drone's position readings and distance calculations was tested under controlled conditions, and errors were analysed. The study showed

Jesse Geneson, Shen-Fu Tsai

We investigate random processes for generating task-dependency graphs of order $n$ with $m$ edges and a specified number of initial vertices and terminal vertices. In order to do so, we consider two random processes for generating task-dependency graphs that can be combined to accomplish this task. In the $(x, y)$ edge-removal process, we start with a maxima

Yuanhao Liu, Qi Cao, Huawei Shen, Yunfan Wu

Recommender systems often suffer from popularity bias, where popular items are overly recommended while sacrificing unpopular items. Existing researches generally focus on ensuring the number of recommendations exposure of each item is equal or proportional, using inverse propensity weighting, causal intervention, or adversarial training. However, increasing

Jingbei Li, Sipan Li, Ping Chen, Luwen Zhang

Automatic dubbing, which generates a corresponding version of the input speech in another language, could be widely utilized in many real-world scenarios such as video and game localization. In addition to synthesizing the translated scripts, automatic dubbing needs to further transfer the speaking style in the original language to the dubbed speeches to giv

S M Mostaq Hossain, Sohag Kumar Saha, Shampa Banik, Trapa Banik

Digital Twins (DTs) are virtual representations of physical objects or processes that can collect information from the real environment to represent, validate, and replicate the physical twin's present and future behavior. The DTs are becoming increasingly prevalent in a variety of fields, including manufacturing, automobiles, medicine, smart cities, and oth

Wen-Fan Feng, Jie-Wen Chen, Yan Wang, Soumya D. Mohanty

We evaluate the prospects for radio follow-up of the double neutron stars (DNSs) in the Galactic disk that could be detected through future space-borne gravitational wave (GW) detectors. We first simulate the DNS population in the Galactic disk that is accessible to space-borne GW detectors according to the merger rate from recent LIGO results. Using the ins

Takanori Ashihara, Takafumi Moriya, Kohei Matsuura, Tomohiro Tanaka

Self-supervised learning (SSL) has been dramatically successful not only in monolingual but also in cross-lingual settings. However, since the two settings have been studied individually in general, there has been little research focusing on how effective a cross-lingual model is in comparison with a monolingual model. In this paper, we investigate this fund

Shanshan Zhong, Wushao Wen, Jinghui Qin, Qiangpu Chen

In computer vision, the performance of deep neural networks (DNNs) is highly related to the feature extraction ability, i.e., the ability to recognize and focus on key pixel regions in an image. However, in this paper, we quantitatively and statistically illustrate that DNNs have a serious attention bias problem on many samples from some popular datasets: (1

Yaxian Chen, KF Lam, Zhonghua Liu

Feature screening is an important tool in analyzing ultrahigh-dimensional data, particularly in the field of Omics and oncology studies. However, most attention has been focused on identifying features that have a linear or monotonic impact on the response variable. Detecting a sparse set of variables that have a nonlinear or non-monotonic relationship with

Minh Duc Vu, Han Wang, Zhuang Li, Gholamreza Haffari

Nowadays, voice assistants help users complete tasks on the smartphone with voice commands, replacing traditional touchscreen interactions when such interactions are inhibited. However, the usability of those tools remains moderate due to the problems in understanding rich language variations in human commands, along with efficiency and comprehensibility iss

Albert Wai Kit Lau, Nurzhan Shaimoldin, Zhanat Maksut, Yan Yan Chan

This work presents an initial on-sky performance measurement of the Single-Photon Imager for Nanosecond Astrophysics (SPINA) system, part of our Ultra-Fast Astronomy (UFA) program. We developed the SPINA system based on the position-sensitive silicon photomultiplier (PS-SiPM) detector to record both photoelectron (P.E.) temporal and spatial information. The

Byung Gyu Chae

The expansion of viewing angle is a crucial factor in holographic displays implemented with a spatial light modulator having a finite space-bandwidth. The enhanced-NA Fresnel hologram reconstructs a holographic image at an angle larger than the diffraction angle by a hologram pixel, where it has a difficulty in achieving this without an interference of high-

Siddheswar Kundu, K. N. Raghavan, V. Sathish Kumar, Sankaran Viswanath

We define and study a generalization of the Littlewood-Richardson (LR) coefficients, which we call the flagged skew LR coefficients. These subsume several previously studied extensions of the LR coefficients. We establish the saturation property for these coefficients, generalizing work of Knutson-Tao and Kushwaha-Raghavan-Viswanath.

Seog-Jin Kim, Xiaopan Lian

The square of a graph $G$, denoted $G^2$, has the same vertex set as $G$ and has an edge between two vertices if the distance between them in $G$ is at most $2$. Thomassen (2018) and Hartke, Jahanbekam and Thomas (2016) proved that $\chi(G^2) \leq 7$ if $G$ is a subcubic planar graph. A natural question is whether $\chi_{\ell}(G^2) \leq 7$ or not if $G$ is a

Shloka V. Janapaty

Experimental work suggests that biological soil crusts, dominant primary producers in drylands and tundra, are particularly vulnerable to disturbances that cause reverse ecological succession. To model successional transitions in biocrust communities, we propose a resource-firing game that captures succession dynamics without specifying detailed function for

Uri Pierre Burmester, Lilia Ferrario, Rüdiger Pakmor, Ivo R. Seitenzahl

We present a series of high-resolution simulations generated with the moving-mesh code AREPO to model the merger of a $1.1 \, \mathrm{M_\odot}$ carbon-oxygen primary white dwarf with an outer helium layer and a $0.35\,\mathrm{M_\odot}$ secondary helium white dwarf. Our simulations lead to detonations that are consistent with the edge-lit scenario, where a he

Zhaowei Wang, Quyet V. Do, Hongming Zhang, Jiayao Zhang

Detecting commonsense causal relations (causation) between events has long been an essential yet challenging task. Given that events are complicated, an event may have different causes under various contexts. Thus, exploiting context plays an essential role in detecting causal relations. Meanwhile, previous works about commonsense causation only consider two

Binoy Krishna De, V. G. Sathe, S. B. Roy

We report an isothermal electric field-induced first-order phase transition from Mott-insulator to the metallic state in the epitaxial thin film of V$_2$O$_3$ in the temperature regime below its Mott transition temperature $\approx$ 180 K. This isothermal electric field induced transition is accompanied by interesting electro-thermal history effects, which d

Shanshan Zhong, Zhongzhan Huang, Wushao Wen, Jinghui Qin

Diffusion models, which have emerged to become popular text-to-image generation models, can produce high-quality and content-rich images guided by textual prompts. However, there are limitations to semantic understanding and commonsense reasoning in existing models when the input prompts are concise narrative, resulting in low-quality image generation. To im

Taehyeok Heo

We explain extremal weight crystals over affine Lie algebras of infinite rank using combinatorial models: a spinor model due to Kwon, and an infinite rank analogue of Kashiwara-Nakashima tableaux due to Lecouvey. In particular, we show that Lecouvey's tableau model is isomorphic to an extremal weight crystal of level zero. Using these combinatorial models, w

Myat Thu Linn Aung, Daniel Gerlinghoff, Chuping Qu, Liwei Yang

Brain-inspired spiking neural networks (SNNs) replace the multiply-accumulate operations of traditional neural networks by integrate-and-fire neurons, with the goal of achieving greater energy efficiency. Specialized hardware implementations of those neurons clearly have advantages over general-purpose devices in terms of power and performance, but exhibit p

Alexey Vylegzhanin, Dylan J. Brown, Aswathy Raj, Danil F. Kornovan

Cold Rydberg atoms are a promising platform for quantum technologies and combining them with optical waveguides has the potential to create robust quantum information devices. Here, we experimentally observe the excitation of cold rubidium atoms to a large range of Rydberg S and D states through interaction with the evanescent field of an optical nanofiber.

Masato Minamitsuji, Shinji Mukohyama

We investigate the linear stability of scalarized black holes (BHs) and neutron stars (NSs) in the Einstein-scalar-Gauss-Bonnet (GB) theories against the odd- and even-parity perturbations including the higher multipole modes. We show that the angular propagation speeds in the even-parity perturbations in the $\ell \to \infty$ limit, with $\ell$ being the an

Masoom Singh, Mauricio Bustamante, Sanjib Kumar Agarwalla

Discovering new neutrino interactions would represent evidence of physics beyond the Standard Model. We focus on new flavor-dependent long-range neutrino interactions mediated by ultra-light mediators, with masses below $10^{-10}$ eV, introduced by new lepton-number gauge symmetries $L_e-L_\mu$, $L_e-L_\tau$, and $L_\mu-L_\tau$. Because the interaction range

Shafiuddin Rehan Ahmed, Abhijnan Nath, James H. Martin, Nikhil Krishnaswamy

Event Coreference Resolution (ECR) is the task of linking mentions of the same event either within or across documents. Most mention pairs are not coreferent, yet many that are coreferent can be identified through simple techniques such as lemma matching of the event triggers or the sentences in which they appear. Existing methods for training coreference sy

Bo Sun, Baoxin Wang, Yixuan Wang, Wanxiang Che

Recently, much Chinese text error correction work has focused on Chinese Spelling Check (CSC) and Chinese Grammatical Error Diagnosis (CGED). In contrast, little attention has been paid to the complicated problem of Chinese Semantic Error Diagnosis (CSED), which lacks relevant datasets. The study of semantic errors is important because they are very common a

Feng Shao, Dongyi Wei, Zhifei Zhang

In this paper, we prove the existence of self-similar algebraic spiral solutions for 2-D incompressible Euler equations for the initial vorticity of the form $|y|^{-\frac1\mu}\ \mathring{\omega}(\theta)$ with $\mu>\frac12$ and $\mathring{\omega}\in L^1(\mathbb T)$ satisfying $m$-fold symmetry ($m\geq 2$) and a dominant condition. As an important application,

Çağlar Kutlu, Saebyeok Ahn, Sergey V. Uchaikin, Soohyung Lee

Many experiments operating at millikelvin temperatures with signal frequencies in the microwave regime are beginning to incorporate Josephson Parametric Amplifiers (JPA) as their first amplification stage. While there are implementations for a wideband frequency response with a minimal need for tuning, designs using resonant structures with small numbers of

Xiaonan Li, Xipeng Qiu

Large Language Models (LLMs) have shown impressive abilities in various tasks. However, fundamentally improving them depends on high-quality datasets or computationally expensive fine-tuning. On the contrary, humans can easily improve themselves by self-thinking and memory, without external resources. In this paper, we propose a framework, MoT, to let the LL

Xianyong Yang, Fukun Zhao

In this paper, we are concerned with a quasilinear Schrodinger equation with well-known Berestycki--Lions nonliearity. The existence of infinitely many normalized solutions is obtained via a minimax argument.

Thomas F Burns, Tomoki Fukai

Hopfield networks are artificial neural networks which store memory patterns on the states of their neurons by choosing recurrent connection weights and update rules such that the energy landscape of the network forms attractors around the memories. How many stable, sufficiently-attracting memory patterns can we store in such a network using $N$ neurons? The

Peng Li, Tongrui Li, Sen Liao, Zhipeng Cao

Using angle resolved photoemission spectroscopy measurements and first principle calculations, we report that the possible unconventional 2q antiferromagnetic (AFM) order in NdSb can induce unusual modulation on its electronic structure. The obvious extra bands observed in the AFM phase of NdSb are well reproduced by theoretical calculations, in which the Fe

Ming Cheng, Haoyu Ma, Qiufang Ma, Xiaopeng Sun

Multi-stage strategies are frequently employed in image restoration tasks. While transformer-based methods have exhibited high efficiency in single-image super-resolution tasks, they have not yet shown significant advantages over CNN-based methods in stereo super-resolution tasks. This can be attributed to two key factors: first, current single-image super-r

Lingjiao Chen, Matei Zaharia, James Zou

There is a rapidly growing number of large language models (LLMs) that users can query for a fee. We review the cost associated with querying popular LLM APIs, e.g. GPT-4, ChatGPT, J1-Jumbo, and find that these models have heterogeneous pricing structures, with fees that can differ by two orders of magnitude. In particular, using LLMs on large collections of

Jisu Han, Jaemin Na, Wonjun Hwang

Human intelligence gradually accepts new information and accumulates knowledge throughout the lifespan. However, deep learning models suffer from a catastrophic forgetting phenomenon, where they forget previous knowledge when acquiring new information. Class-Incremental Learning aims to create an integrated model that balances plasticity and stability to ove

Ara Tonoyan, Armen Sargsyan, Rodolphe Momier, Claude Leroy

Magnetically induced (MI) transitions (F${}_{g}$ = 1 $\rightarrow$ F${}_{e}$= 3) of ${}^{87}$Rb D${}_{2}$ line are among the most promising atomic transitions for applications in laser physics. They reach their maximum intensity in the 0.2--2 kG magnetic field range and are more intense than many conventional atomic transitions. An important feature of MI tr

A. Wong, E. Hatziminaoglou, A. Borkar, G. Popping

The Atacama Large Millimetre/submillimetre Array (ALMA) is the world's most advanced radio interferometric facility, producing science data with an average rate of about 1 TB per day. After a process of calibration, imaging and quality assurance, the scientific data are stored in the ALMA Science Archive (ASA), along with the corresponding raw data, making t

Adnan Darwiche

A central quest in explainable AI relates to understanding the decisions made by (learned) classifiers. There are three dimensions of this understanding that have been receiving significant attention in recent years. The first dimension relates to characterizing conditions on instances that are necessary and sufficient for decisions, therefore providing abst

Lesly Miculicich, Yujia Xie, Song Wang, Pengcheng He

Many applications of text generation such as summarization benefit from accurately controlling the text length. Existing approaches on length-controlled summarization either result in degraded performance or can only control the length approximately. In this work, we present a framework to generate summaries with precisely the specified number of tokens or s

H. Ueda, S. Katakami, S. Yoshida, Y. Nakai

We propose a data-driven technique to infer microscopic physical quantities from nuclear magnetic resonance(NMR) spectra, in which the data size and quality required for the Bayesian inference are investigated. The $^{59}$Co-NMR measurement of YbCo$_2$Zn$_{20}$ single crystal generates complex spectra with 28 peaks. By exploiting the site symmetry in the cry

Kirk A. Larsen, Kurtis Borne, Razib Obaid, Andrei Kamalov

The photon spectrum from free-electron laser (FEL) light sources offers valuable information in time-resolved experiments and machine optimization in the spectral and temporal domains. We have developed a compact single-shot photon spectrometer to diagnose soft X-ray spectra. The spectrometer consists of an array of off-axis Fresnel zone plates (FZP) that ac

Karol Kowalski, Nicholas P. Bauman

We conducted quantum simulations of strongly correlated systems using the quantum flow (QFlow) approach, which enables sampling large sub-spaces of the Hilbert space through coupled eigenvalue problems in reduced dimensionality active spaces. Our QFlow algorithms significantly reduce circuit complexity and pave the way for scalable and constant-circuit-depth

Siqi Liu, A-Li Luo, Wei Zhang, Yan-Xia Zhang

Green Pea galaxies are compact galaxies with high star formation rates. However, limited samples of Green Pea galaxies have HI 21 cm measurements. Whether the HI gas fraction f_{HI} = M_{HI}/M_{*} of Green Pea galaxies follows the existing scaling relations between the f_{HI} and NUV-r color or linear combinations of color and other physical quantities needs

Cong Ma, Yaping Zhang, Mei Tu, Yang Zhao

Text image machine translation (TIMT) aims to translate texts embedded in images from one source language to another target language. Existing methods, both two-stage cascade and one-stage end-to-end architectures, suffer from different issues. The cascade models can benefit from the large-scale optical character recognition (OCR) and MT datasets but the two

Dinh Hoa Nguyen, Andrew Chapman, Takeshi Tsuji

Building on the carbon reduction targets agreed in the Paris Agreements, many nations have renewed their efforts toward achieving carbon neutrality by the year 2050. In line with this ambitious goal, nations are seeking to understand the appropriate combination of technologies which will enable the required reductions in such a way that they are appealing to

Sagar Biswas

We revisit semiclassical strings, in particular we focus on rigidly rotating strings, in the near horizon geometry of two orthogonal stacks of NS5-branes (I-branes) using the string sigma model. We determine the conserved charges for the probe string moving in the resulting $\mathbb{R}_t \times S^3_{\theta_1}\times S^3_{\theta_2}$ background supported by NS-

Lu Ling, Washim Uddin Mondal, Satish V, Ukkusuri

This study explores the vaccine prioritization strategy to reduce the overall burden of the pandemic when the supply is limited. Existing methods conduct macro-level or simplified micro-level vaccine distribution by assuming the homogeneous behavior within subgroup populations and lacking mobility dynamics integration. Directly applying these models for micr

Guodong Liu

The clinical notes are usually typed into the system by physicians. They are typically required to be marked by standard medical codes, and each code represents a diagnosis or medical treatment procedure. Annotating these notes is time consuming and prone to error. In this paper, we proposed a multi-view attention based Neural network to predict medical code

Akash Godbole, Steven A. Grosz, Anil K. Jain

Effective distribution of nutritional and healthcare aid for children, particularly infants and toddlers, in some of the least developed and most impoverished countries of the world, is a major problem due to the lack of reliable identification documents. Biometric authentication technology has been investigated to address child recognition in the absence of

Bradley Boyd, Sid Becker, Yue Ling

The vaporization of a freely moving drop in a uniform, high-temperature gas stream is investigated through direct numerical simulation. The incompressible Navier-Stokes equations with surface tension and phase change are solved in conjunction with the energy equations of each phase. The sharp liquid-gas interface is tracked using the geometric Volume-of-Flui

Keyang He, Prashant Doshi, Bikramjit Banerjee

There is a prevalence of multiagent reinforcement learning (MARL) methods that engage in centralized training. But, these methods involve obtaining various types of information from the other agents, which may not be feasible in competitive or adversarial settings. A recent method, the interactive advantage actor critic (IA2C), engages in decentralized train

Yulei Wang, Heguo Liu

Let $p$ be a prime and $F$ be a finite field of characteristic $p$. Suppose that $FG$ is the group algebra of the finite $p$-group $G$ over the field $F$. Let $V(FG)$ denote the group of normalized units in $FG$ and let $V_*(FG)$ denote the unitary subgroup of $V(FG)$. If $p$ is odd, then the order of $V_*(FG)$ is $|F|^{(|G|-1)/2}$. However, the case when $p

Ben Langton, Netanel Raviv

The covering radius is a fundamental property of linear codes that characterizes the trade-off between storage and access in linear data-query protocols. The generalized covering radius was recently defined by Elimelech and Schwartz for applications in joint-recovery of linear data-queries. In this work we extend a known bound on the ordinary covering radius

Rikimaru Kurata, Keiichiro Toda, Genki Ishigane, Makoto Naruse

We present a single-image numerical phase retrieval method for Zernike phase-contrast microscopy (ZPM) that addresses halo and shade-off artifacts, as well as the weak phase condition, without requiring hardware modifications. By employing a rigorous physical model of ZPM and a gradient descent algorithm for its inversion, we achieve quantitative ZPM imaging

Katharena Christy, Jason Kumar, Pearl Sandick

We consider constraints on $p$-wave dark matter in a dark matter spike surrounding the supermassive black hole at the center of M87. Owing to the large mass of the black hole, and resulting large velocity dispersion for the dark matter particles in the spike, it is possible for Fermi-LAT and MAGIC data to place tight constraints on $p$-wave annihilation, whi

Tao Chen, Yazhou Yao, Jinhui Tang

Weakly supervised semantic segmentation (WSSS) models relying on class activation maps (CAMs) have achieved desirable performance comparing to the non-CAMs-based counterparts. However, to guarantee WSSS task feasible, we need to generate pseudo labels by expanding the seeds from CAMs which is complex and time-consuming, thus hindering the design of efficient

Xiaochen Zhou, Bosheng Li, Bedrich Benes, Songlin Fei

In this paper, we propose DeepTree, a novel method for modeling trees based on learning developmental rules for branching structures instead of manually defining them. We call our deep neural model situated latent because its behavior is determined by the intrinsic state -- encoded as a latent space of a deep neural model -- and by the extrinsic (environment

Yanzhen Ren, Hongcheng Zhu, Liming Zhai, Zongkun Sun

Voice conversion (VC), as a voice style transfer technology, is becoming increasingly prevalent while raising serious concerns about its illegal use. Proactively tracing the origins of VC-generated speeches, i.e., speaker traceability, can prevent the misuse of VC, but unfortunately has not been extensively studied. In this paper, we are the first to investi

Yaoqi Huang, Vineeth Chandran Suja, Menghao Yang, Andrey V. Malkovskiy

Response of lipid bilayers to external mechanical stimuli is an active area of research with implications for fundamental and synthetic cell biology. However, there is a lack of tools for systematically imposing mechanical strains and non-invasively mapping out interfacial (membrane) stress distributions on lipid bilayers. In this article, we report a miniat

Pu Ren, Chengping Rao, Hao Sun, Yang Liu

Estimating the material distribution of Earth's subsurface is a challenging task in seismology and earthquake engineering. The recent development of physics-informed neural network (PINN) has shed new light on seismic inversion. In this paper, we present a PINN framework for seismic wave inversion in layered (1D) semi-infinite domain. The absorbing boundary

Hezi Zhang, Keyi Yin, Anbang Wu, Hassan Shapourian

Chiplet architecture is an emerging architecture for quantum computing that could significantly increase qubit resources with its great scalability and modularity. However, as the computing scale increases, communication between qubits would become a more severe bottleneck due to the long routing distances. In this paper, we propose a multi-entry communicati

Seoktae Koh, Abbas M Sherif, Gansukh Tumurtushaa

In this work, we study the existence of gradient (proper) CKVs in locally rotationally symmetric spacetimes (LRS), those CKVs in the space spanned by the tangent to observers' congruence and the preferred spatial direction, allowing us to provide a (partial) characterization of gradient conformally static (GCSt) LRS solutions. Irrrotational solutions with no

Yonghong Zhong, Kai Fukami, Byungjin An, Kunihiko Taira

Reconstruction of unsteady vortical flow fields from limited sensor measurements is challenging. We develop machine learning methods to reconstruct flow features from sparse sensor measurements during transient vortex-airfoil wake interaction using only a limited amount of training data. The present machine learning models accurately reconstruct the aerodyna

Hu Gao, Jing Yang, Ying Zhang, Ning Wang

Image restoration is the task of aiming to obtain a high-quality image from a corrupt input image, such as deblurring and deraining. In image restoration, it is typically necessary to maintain a complex balance between spatial details and contextual information. Although a multi-stage network can optimally balance these competing goals and achieve significan

D. Avila Rojas, S. Hernández-Cadena, M. M. González, A. Pratts

GRB 221009A has posed a significant challenge to our current understanding of the mechanisms that produce TeV photons in gamma-ray bursts (GRB). On one hand, the Klein-Nishina (KN) effect of the inverse Compton scattering leads to less efficient energy losses of high-energy electrons. In the other hand, at a redshift of 0.151, the TeV spectrum of GRB 221009A

Shiyin Dong, Mingrui Zhu, Nannan Wang, Xinbo Gao

Zero-shot sketch-based image retrieval (ZS-SBIR) is challenging due to the cross-domain nature of sketches and photos, as well as the semantic gap between seen and unseen image distributions. Previous methods fine-tune pre-trained models with various side information and learning strategies to learn a compact feature space that is shared between the sketch a

Wenbo Huang, Kai Wan, Hua Sun, Mingyue Ji

This paper studies the master-worker distributed linearly separable computation problem, where the considered computation task, referred to as linearly separable function, is a typical linear transform model widely used in cooperative distributed gradient coding, real-time rendering, linear transformers, etc. %A master asks $\Nsf$ distributed workers to comp

Chaoyue Zhang, Zhiwen Zhou, Huizhi Wang, Yong Zeng

Integrated sensing and communication (ISAC) is a promising technology to simultaneously provide high-performance wireless communication and radar sensing services in future networks. In this paper, we propose the concept of \emph{integrated super-resolution sensing and communication} (ISSAC), which uses super-resolution algorithms in ISAC systems to achieve

Jia Zhang, Runxiong Wu, Xin Chen

We propose a novel sparse sliced inverse regression method based on random projections in a large $p$ small $n$ setting. Embedded in a generalized eigenvalue framework, the proposed approach finally reduces to parallel execution of low-dimensional (generalized) eigenvalue decompositions, which facilitates high computational efficiency. Theoretically, we prov

Boqiang Zhang, Hongtao Xie, Yuxin Wang, Jianjun Xu

Vision model have gained increasing attention due to their simplicity and efficiency in Scene Text Recognition (STR) task. However, due to lacking the perception of linguistic knowledge and information, recent vision models suffer from two problems: (1) the pure vision-based query results in attention drift, which usually causes poor recognition and is summa

Yu Cheng Hung, Jian-Jiun Ding

Onsets are a key factor to split audio into several notes. In this paper, we ensemble multiple temporal convolution network (TCN) based model and utilize a restricted frequency range spectrogram to achieve more robust onset detection. Different from the present onset detection of QBH system which is only available in a clean scenario, our proposal of onset d

Wei Qin, Zetong Chen, Lei Wang, Yunshi Lan

This paper proposes a new depression detection system based on LLMs that is both interpretable and interactive. It not only provides a diagnosis, but also diagnostic evidence and personalized recommendations based on natural language dialogue with the user. We address challenges such as the processing of large amounts of text and integrate professional diagn

Siqi Fan, Yuxin Zhong, I-Hong Hou, Clement Kam

In this paper, we address the optimization problem of moments of Age of Information (AoI) for active and passive users in a random access network. In this network, active users broadcast sensing data while passive users only receive signals. Collisions occur when multiple active users transmit simultaneously, and passive users are unable to receive signals w

Shamna Pootheri, Govindan V K

Mammographic image analysis requires accurate localisation of salient mammographic masses. In mammographic computer-aided diagnosis, mass or Region of Interest (ROI) is often marked by physicians and features are extracted from the marked ROI. In this paper, we present a novel mammographic mass localisation framework, based on the maximal class activations o

M. Harada, K. Abe, C. Bronner, Y. Hayato

We report the first search result for the flux of astrophysical electron antineutrinos for energies O(10) MeV in the gadolinium-loaded Super-Kamiokande (SK) detector. In June 2020, gadolinium was introduced to the ultra-pure water of the SK detector in order to detect neutrons more efficiently. In this new experimental phase, SK-Gd, we can search for electro

Huan Cai, Catherine Xu, Weiyu Xu

In the past several decades, the world's economy has become increasingly globalized. On the other hand, there are also ideas advocating the practice of ``buy local'', by which people buy locally produced goods and services rather than those produced farther away. In this paper, we establish a mathematical theory of real price that determines the optimal glob

Sayak Saha Roy, Krishna Vamsi Naragam, Shirin Nilizadeh

The ability of ChatGPT to generate human-like responses and understand context has made it a popular tool for conversational agents, content creation, data analysis, and research and innovation. However, its effectiveness and ease of accessibility makes it a prime target for generating malicious content, such as phishing attacks, that can put users at risk.

Zheng-Yan Sheng, Yang Ai, Zhen-Hua Ling

Lip-to-Speech (Lip2Speech) synthesis, which predicts corresponding speech from talking face images, has witnessed significant progress with various models and training strategies in a series of independent studies. However, existing studies can not achieve voice control under zero-shot condition, because extra speaker embeddings need to be extracted from nat

Yuwei Duan

The existence of cracks and other damages pose a significant threat to the safe operation of transportation infrastructure. Traditional manual detection and ultrasound equipment testing consume a lot of time and resources. With the development of deep learning technology, many deep learning models have been widely applied to practical visual segmentation tas

Shengkui Ye

We prove a general solvable subgroup theorem in terms of length functions. As applications, we obtain a solvable subgroup theorem in dynamical systems: any solvable group of finite Hirsch length acting on a smooth manifold with uniformly positive topological entropies must be virtually $\mathbb{Z}^n$.

Juhoon Chung

Our goal in this paper is to study the zero distribution of a sequence of polynomials whose coefficients satisfy a three-term recurrence. Equivalently, these polynomials are Taylor polynomials of a rational function with a polynomial denominator of degree 2. We will use complex analysis to find the bi-variate generating function for that sequence of Taylor p

Ruben Becker, Manuel Cáceres, Davide Cenzato, Sung-Hwan Kim

Wheeler nondeterministic finite automata (WNFAs) were introduced as a generalization of prefix sorting from strings to labeled graphs. WNFAs admit optimal solutions to classic hard problems on labeled graphs and languages. The problem of deciding whether a given NFA is Wheeler is known to be NP-complete. Recently, however, Alanko et al. showed how to side-st

Ziheng Geng, Chao Zhang, Yuhao Ren, Minxiang Zhu

A kriging-random forest hybrid model is developed for real-time ground property prediction ahead of the earth pressure balanced shield by integrating Kriging extrapolation and random forest, which can guide shield operating parameter selection thereby mitigate construction risks. The proposed KRF algorithm synergizes two types of information: prior informati

Ken'ichiro Tanaka

We consider problems of minimizing functionals $\mathcal{F}$ of probability measures on the Euclidean space. To propose an accelerated gradient descent algorithm for such problems, we consider gradient flow of transport maps that give push-forward measures of an initial measure. Then we propose a deterministic accelerated algorithm by extending Nesterov's ac

Brandon Duderstadt, Hayden S. Helm, Carey E. Priebe

Recent advances in self-supervised learning and neural network scaling have enabled the creation of large models, known as foundation models, which can be easily adapted to a wide range of downstream tasks. The current paradigm for comparing foundation models involves evaluating them with aggregate metrics on various benchmark datasets. This method of model

A. R. Caddell, V. V. Flambaum, B. M. Roberts

While most scintillation-based dark matter experiments search for Weakly Interacting Massive Particles (WIMPs), a sub-GeV WIMP-like particle may also be detectable in these experiments. While dark matter of this type and scale would not leave appreciable nuclear recoil signals, it may instead induce ionization of atomic electrons. Accurate modelling of the a

Masahiro Ikeda, Motohiro Sobajima, Koichi Taniguchi, Yuta Wakasugi

Lifespan estimates for semilinear damped wave equations of the form $\partial_t^2u-\Delta u+\partial_tu=|u|^p$ in a two dimensional exterior domain endowed with the Dirichlet boundary condition are dealt with. For the critical case of the semilinear heat equation $\partial_tv-\Delta v=v^2$ with the Dirichlet boundary condition and the initial condition $v(0)

Michiya Mori, Peter Šemrl

Wigner's theorem characterizes isometries of the set of all rank one projections on a Hilbert space. In metric geometry nonexpansive maps and noncontractive maps are well studied generalizations of isometries. We show that under certain conditions Wigner symmetries can be characterized as nonexpansive or noncontractive maps on the set of all projections of r

Jonathan Brundan

This article develops a practical technique for studying representations of $\Bbbk$-linear categories arising in the categorification of quantum groups. We work in terms of locally unital algebras which are $\mathbb{Z}$-graded with graded pieces that are finite-dimensional and bounded below, developing a theory of graded triangular bases for such algebras. T

Arjun Bhalla

Minimum Spanning Trees are a well-studied subset of graph problems. While classical algorithms have existed to solve these problems for decades, new variations and application areas are constantly being discovered. When dealing with large graph problems, however, memory constraints can often be limiting, especially when using these classical methods in memor

David T. Frazier, Christopher Drovandi, David J. Nott

Bayesian statistics is concerned with conducting posterior inference for the unknown quantities in a given statistical model. Conventional Bayesian inference requires the specification of a probabilistic model for the observed data, and the construction of the resulting likelihood function. However, sometimes the model is so complicated that evaluation of th

Runqing Wang, Gang Wang, Jian Sun, Fang Deng

Flexible manufacturing has given rise to complex scheduling problems such as the flexible job shop scheduling problem (FJSP). In FJSP, operations can be processed on multiple machines, leading to intricate relationships between operations and machines. Recent works have employed deep reinforcement learning (DRL) to learn priority dispatching rules (PDRs) for

Harshit Daga, Jaemin Shin, Dhruv Garg, Ada Gavrilovska

Distributed machine learning approaches, including a broad class of federated learning (FL) techniques, present a number of benefits when deploying machine learning applications over widely distributed infrastructures. The benefits are highly dependent on the details of the underlying machine learning topology, which specifies the functionality executed by t

Jialin Hong, Baohui Hou, Liying Sun, Xiaojing Zhang

Stochastic Klein--Gordon--Schr\"odinger (KGS) equations are important mathematical models and describe the interaction between scalar nucleons and neutral scalar mesons in the stochastic environment. In this paper, we propose novel structure-preserving schemes to numerically solve stochastic KGS equations with additive noise, which preserve averaged charge e

Lei Yuan, Feng Chen, Zhongzhang Zhang, Yang Yu

Communication can promote coordination in cooperative Multi-Agent Reinforcement Learning (MARL). Nowadays, existing works mainly focus on improving the communication efficiency of agents, neglecting that real-world communication is much more challenging as there may exist noise or potential attackers. Thus the robustness of the communication-based policies b

Yaxin Hu, Laura Stegner, Bilge Mutlu

Transactive Memory System (TMS) is a group theory that describes how communication can enable the combination of individual minds into a group. While this theory has been extensively studied in human-human groups, it has not yet been formally applied to socially assistive robot design. We demonstrate how the three-phase TMS group communication process-which

Zeming Sun, Darrah K. Dare, Zhaslan Baraissov, David A. Muller

Intermetallic Nb3Sn alloys have long been believed to form through Sn diffusion into Nb. However, our observations of significant oxygen content in Nb3Sn prompted an investigation of alternative formation mechanisms. Through experiments involving different oxide interfaces (clean HF-treated, native oxidized, and anodized), we demonstrate a thermodynamic rout