May 2023 arXiv papers — page 138

Eve Fleisig, Rediet Abebe, Dan Klein

Though majority vote among annotators is typically used for ground truth labels in natural language processing, annotator disagreement in tasks such as hate speech detection may reflect differences in opinion across groups, not noise. Thus, a crucial problem in hate speech detection is determining whether a statement is offensive to the demographic group tha

Benedikt Lütke Schwienhorst, Lucas Kock, Nadja Klein, David J. Nott

Even though dropout is a popular regularization technique, its theoretical properties are not fully understood. In this paper we study dropout regularization in extended generalized linear models based on double exponential families, for which the dispersion parameter can vary with the features. A theoretical analysis shows that dropout regularization prefer

Amra Omanović, Polona Oblak, Tomaž Curk

Tropical semiring has proven successful in several research areas, including optimal control, bioinformatics, discrete event systems, or solving a decision problem. In previous studies, a matrix two-factorization algorithm based on the tropical semiring has been applied to investigate bipartite and tripartite networks. Tri-factorization algorithms based on s

Shane Chern, Lin Jiu

The $q$-analogs of Bernoulli and Euler numbers were introduced by Carlitz. Similar to the recent results on the Hankel determinants for the $q$-Bernoulli numbers established by Chapoton and Zeng, we determine parallel evaluations for the $q$-Euler numbers. It is shown that the associated Favard-type orthogonal polynomials for $q$-Euler numbers are given by a

Sichun Luo, Yuanzhang Xiao, Xinyi Zhang, Yang Liu

Federated recommendation systems employ federated learning techniques to safeguard user privacy by transmitting model parameters instead of raw user data between user devices and the central server. Nevertheless, the current federated recommender system faces challenges such as heterogeneity and personalization, model performance degradation, and communicati

Honghui Yang, Wenxiao Wang, Minghao Chen, Binbin Lin

Recent Transformer-based 3D object detectors learn point cloud features either from point- or voxel-based representations. However, the former requires time-consuming sampling while the latter introduces quantization errors. In this paper, we present a novel Point-Voxel Transformer for single-stage 3D detection (PVT-SSD) that takes advantage of these two rep

Wenzheng Zhao, Yuanning Cui, Wei Hu

Continual relation extraction (RE) aims to learn constantly emerging relations while avoiding forgetting the learned relations. Existing works store a small number of typical samples to re-train the model for alleviating forgetting. However, repeatedly replaying these samples may cause the overfitting problem. We conduct an empirical study on existing works

Akın Alkan, Mehmet Önder

A new kind of partner curve called osculating mate of a Frenet curve is introduced. Some characterizations for osculating mate are obtained and using the obtained results some special curves such as slant helix, spherical helix, $C$-slant helix and rectifying curve are constructed.

Xuan Guang, Ruze Zhang

In this paper, we put forward the model of zero-error distributed function compression system of two binary memoryless sources X and Y, where there are two encoders En1 and En2 and one decoder De, connected by two channels (En1, De) and (En2, De) with the capacity constraints C1 and C2, respectively. The encoder En1 can observe X or (X,Y) and the encoder En2

Ke Ma, Hongkai Chen, Shan Lin

Type 1 diabetes is a serious disease in which individuals are unable to regulate their blood glucose levels, leading to various medical complications. Artificial pancreas (AP) systems have been developed as a solution for type 1 diabetic patients to mimic the behavior of the pancreas and regulate blood glucose levels. However, current AP systems lack detecti

Alessandro Giovannelli, Marco Lippi, Tommaso Proietti

The paper deals with the construction of a synthetic indicator of economic growth, obtained by projecting a quarterly measure of aggregate economic activity, namely gross domestic product (GDP), into the space spanned by a finite number of smooth principal components, representative of the medium-to-long-run component of economic growth of a high-dimensional

Andrea Tonini, Christian Vergara, Francesco Regazzoni, Luca Dede'

Impaired cardiac function has been described as a frequent complication of COVID-19-related pneumonia. To investigate possible underlying mechanisms, we represented the cardiovascular system by means of a lumped-parameter 0D mathematical model. The model was calibrated using clinical data, recorded in 58 patients hospitalized for COVID-19-related pneumonia,

Xinyi Wang, Zitao Wang, Wei Hu

Continual few-shot relation extraction (RE) aims to continuously train a model for new relations with few labeled training data, of which the major challenges are the catastrophic forgetting of old relations and the overfitting caused by data sparsity. In this paper, we propose a new model, namely SCKD, to accomplish the continual few-shot RE task. Specifica

Nikolay Mikhaylovskiy, Ilya Churilov

We show that the laws of autocorrelations decay in texts are closely related to applicability limits of language models. Using distributional semantics we empirically demonstrate that autocorrelations of words in texts decay according to a power law. We show that distributional semantics provides coherent autocorrelations decay exponents for texts translated

Julian D. Schiller, Matthias A. Müller

We consider a moving horizon estimation (MHE) scheme involving a discounted least squares objective for general nonlinear continuous-time systems. Provided that the system is detectable (incrementally integral input/output-to-state stable, i-iIOSS), we show that there exists a sufficiently long estimation horizon that guarantees robust global exponential sta

Apurba Biswas, R. Rajesh

Mpemba effect refers to the counterintuitive phenomenon of a hotter system equilibrating faster than a colder system when both are quenched to the same low temperature. For a Brownian particle trapped in a piece-wise linear single well potential that is devoid of any other metastable minima we show the existence of Mpemba effect for a wide range of parameter

Florian Kogelbauer, Ilya Karlin

We perform a complete spectral analysis of the linearized Shakhov model involving two relaxation times $\tau_{\rm fast}$ and $\tau_{\rm slow}$. Our results are based on spectral functions derived from the theory of finite-rank perturbations, which allows us to infer the existence of a critical wave number $k_{\rm crit}$ limiting the number of discrete eigenv

Pascal Mettes, Mina Ghadimi Atigh, Martin Keller-Ressel, Jeffrey Gu

Deep representation learning is a ubiquitous part of modern computer vision. While Euclidean space has been the de facto standard manifold for learning visual representations, hyperbolic space has recently gained rapid traction for learning in computer vision. Specifically, hyperbolic learning has shown a strong potential to embed hierarchical structures, le

Xin-Yi Fan, Hai-Jun Zhou

We introduce a planted vertex cover problem on regular random graphs and study it by the cavity method of statistical mechanics. Different from conventional Ising models, the equilibrium ferromagnetic phase transition of this binary-spin two-body interaction system is discontinuous, as the paramagnetic phase is separated from the ferromagnetic phase by an ex

Federico Malizia, Alessandra Corso, Lucia Valentina Gambuzza, Giovanni Russo

Higher-order interactions play a key role for the stability and function of a complex system. However, how to identify them is still an open problem. Here, we propose a method to fully reconstruct the structural connectivity of a system of coupled dynamical units, identifying both pairwise and higher-order interactions from the system time evolution. Our met

Boris Culina

This article informally presents a solution to the paradoxes of truth and shows how the solution solves classical paradoxes (such as the original Liar) as well as the paradoxes that were invented as counterarguments for various proposed solutions (the revenge of the Liar). This solution complements the classical procedure of determining the truth values of s

Zhao Yuanxi, Duan Wenrui, Li Huanglong

In conventional digital computers, data and information are represented in binary form and encoded in the steady states of transistors. They are then processed in a quasi-static way. However, with transistors approaching their physical limits and the von Neumann bottleneck, the rate of improvement in computing efficiency has slowed down. Therefore, drawing i

Huanfeng Zhu, Jialin Li, Qiang Chen, Wei Tang

As basic building blocks for next-generation information technologies devices, high-quality p-n junctions based on van der Waals (vdW) materials have attracted widespread interest.Compared to traditional two dimensional (2D) heterojunction diodes, the emerging homojunctions are more attractive owing to their intrinsic advantages, such as continuous band alig

Neil Lu, Susan M. Scott, Karl Wette

Neutron stars are one of the most mysterious wonders in the Universe. Their extreme densities hint at new and exotic physics at work within. Gravitational waves could be the key to unlocking their secrets. In particular, a first detection of gravitational waves from rapidly-spinning, deformed neutron stars could yield new insights into the physics of matter

Cheongho Han, Youn Kil Jung, Doeon Kim, Andrew Gould

We inspect the microlensing data of the KMTNet survey collected during the 2018--2020 seasons in order to find lensing events produced by binaries with brown-dwarf companions. In order to pick out binary-lens events with candidate BD lens companions, we conduct systematic analyses of all anomalous lensing events observed during the seasons. By applying the s

Muhammad Yameen

Consider the configuration spaces of manifolds. We give a precise formula for the integral cohomological dimension (the degree of top non-trivial integral cohomology group) of unordered configuration spaces of manifolds with non-trivial co-dimension one cohomology group, and show that the the sequence of cohomological dimensions is arithmetic. This arithmeti

Ping Zhang, Lingfeng Ming, Tingyi Yuan, Cong Qiu

The simulation-based testing of Autonomous Driving Systems (ADSs) has gained significant attention. However, current approaches often fall short of accurately assessing ADSs for two reasons: over-reliance on expert knowledge and the utilization of simplistic evaluation metrics. That leads to discrepancies between simulated scenarios and naturalistic driving

Jialin Li, Lizhen Wang, Yuzhong Chen, Yujie Li

Interface interactions in 2D vertically stacked heterostructures play an important role in optoe-lectronic applications, photodetectors based on graphene/InSe heterostructures had shown promising performance nowadays. However, nonlinear optical properties studies based on the graphene/InSe heterostructure was insufficient. Here, we fabricated graphene/InSe h

P. G. Meyer, A. G. Cherstvy, H. Seckler, R. Hering

How predictable is the next move of an animal? Specifically, which factors govern the short- and long-term motion patterns and the overall dynamics of landbound, plant-eating animals and ruminants in particular? To answer this question, we here study the movement dynamics of springbok antelopes Antidorcas marsupialis. We propose complementary statistical ana

Arnab Mukherjee, Sunandan Gangopadhyay, A. S. Majumdar

We investigate the transition rates of uniformly accelerated two-level single and entangled atomic systems in empty space as well as inside a cavity. We take into account the interaction between the systems and a massless scalar field from the viewpoint of an instantaneously inertial observer and a coaccelerated observer, respectively. The upward transition

Thi Xinh Dinh, Serdar Boztas, Son Hoang Dau, Emanuele Viterbo

Motivated by the application of Reed-Solomon codes to recently emerging decentralized storage systems such as Storj and Filebase/Sia, we study the problem of designing compact repair groups for recovering multiple failures in a decentralized manner. Here, compactness means that the corresponding trace repair schemes of these groups of helpers can be generate

Jia Li, Ge Li, Yongmin Li, Zhi Jin

Large Language Models (LLMs) (e.g., ChatGPT) have shown impressive performance in code generation. LLMs take prompts as inputs, and Chain-of-Thought (CoT) prompting is the state-of-the-art prompting technique. CoT prompting asks LLMs first to generate CoTs (i.e., intermediate natural language reasoning steps) and then output the code. However, CoT prompting

Deepak, Arpita Chatterjee

In the present paper, we have studied the higher as well as the lower-order nonclassicalities of photon-added-then-subtracted and photon-subtracted-then-added thermal and even coherent states. Different criteria such as Mandel's function ($Q_M^{(l)}$), higher-order antibunching ($d_h^{(l-1)}$), sub-Poissonian photon statistics ($D_h^{(l-1)}$), higher-order s

Paritosh Ghosh, Hemangi Madhusudan Shah, Arindam Bhattacharyya

In this research, we study the nature of $\eta$-Einstein and gradient $\eta$-Einstein soliton in the framework of almost coK\"{a}hler manifolds and $(\kappa, \mu)$-almost coK\"{a}hler manifolds. We find some expressions for scalar curvature of the almost coK\"{a}hler manifold admitting $\eta$-Einstein soliton in various cases. We also prove that if a $(\kapp

Sadashige Matsuo, Takaya Imoto, Tomohiro Yokoyama, Yosuke Sato

A Josephson junction (JJ) is a key device in the development of superconducting circuits, wherein a supercurrent in the JJ is controlled by the phase difference between the two superconducting electrodes. Recently, it has been shown that the JJ current is nonlocally controlled by the phase difference of another nearby JJ via coherent coupling. Here, we use t

Mohsinul Kabir, Obayed Bin Mahfuz, Syed Rifat Raiyan, Hasan Mahmud

The analysis of consumer sentiment, as expressed through reviews, can provide a wealth of insight regarding the quality of a product. While the study of sentiment analysis has been widely explored in many popular languages, relatively less attention has been given to the Bangla language, mostly due to a lack of relevant data and cross-domain adaptability. To

Kun Su, Judith Yue Li, Qingqing Huang, Dima Kuzmin

Video-to-music generation demands both a temporally localized high-quality listening experience and globally aligned video-acoustic signatures. While recent music generation models excel at the former through advanced audio codecs, the exploration of video-acoustic signatures has been confined to specific visual scenarios. In contrast, our research confronts

V. Ugrinovskii, I. R. Petersen, I. Shames

Among first order optimization methods, Polyak's heavy ball method has long been known to guarantee the asymptotic rate of convergence matching Nesterov's lower bound for functions defined in an infinite-dimensional space. In this paper, we use results on the robust gain margin of linear uncertain feedback control systems to show that the heavy ball method i

Naoyuki Haba, Yasuhiro Shimizu, Toshifumi Yamada

We investigate vacuum stability and Q-ball formation in the Type II seesaw model by considering the effective potential for scalar fields, taking into account renormalization effects. We find that the quartic coupling for the triplet Higgs can vanish at a high energy scale, creating a flat direction where Q-ball formation can occur. If Q-balls are produced,

Yuwei Wu, Weixiao Liu, Zhiyang Liu, Gregory S. Chirikjian

Robotic grasping is an essential and fundamental task and has been studied extensively over the past several decades. Traditional work analyzes physical models of the objects and computes force-closure grasps. Such methods require pre-knowledge of the complete 3D model of an object, which can be hard to obtain. Recently with significant progress in machine l

Jiho Kim, Sungjin Park, Yeonsu Kwon, Yohan Jo

In real world applications, knowledge graphs (KG) are widely used in various domains (e.g. medical applications and dialogue agents). However, for fact verification, KGs have not been adequately utilized as a knowledge source. KGs can be a valuable knowledge source in fact verification due to their reliability and broad applicability. A KG consists of nodes

Hanyu Xue

This study explores the specific structure of 1D SPT phases with $G\times H$ symmetry ($G, H$ are finite non-Abelian groups) and constructs an order parameter. We demonstrate that this order parameter can comprehensively describe this specific structure. Utilizing this order parameter, we prove that when the SPT phase theory of symmetry $G$ is extended to mi

Haoran Luo, Haihong E, Yuhao Yang, Yikai Guo

Link Prediction on Hyper-relational Knowledge Graphs (HKG) is a worthwhile endeavor. HKG consists of hyper-relational facts (H-Facts), composed of a main triple and several auxiliary attribute-value qualifiers, which can effectively represent factually comprehensive information. The internal structure of HKG can be represented as a hypergraph-based represent

Ming Jin, Guangsi Shi, Yuan-Fang Li, Bo Xiong

Time series forecasting has remained a focal point due to its vital applications in sectors such as energy management and transportation planning. Spectral-temporal graph neural network is a promising abstraction underlying most time series forecasting models that are based on graph neural networks (GNNs). However, more is needed to know about the underpinni

Besnik Fetahu, Sudipta Kar, Zhiyu Chen, Oleg Rokhlenko

We present the findings of SemEval-2023 Task 2 on Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2). Divided into 13 tracks, the task focused on methods to identify complex fine-grained named entities (like WRITTENWORK, VEHICLE, MUSICALGRP) across 12 languages, in both monolingual and multilingual scenarios, as well as noisy settings. The tas

Tuhin Khare, Ritajit Majumdar, Rajiv Sangle, Anupama Ray

Quantum computers are the next evolution of computing hardware. Quantum devices are being exposed through the same familiar cloud platforms used for classical computers, and enabling seamless execution of hybrid applications that combine quantum and classical components. Quantum devices vary in features, e.g., number of qubits, quantum volume, CLOPS, noise p

Mo Liu, Paul Grigas, Heyuan Liu, Zuo-Jun Max Shen

We develop the first active learning method for contextual linear optimization. Specifically, we introduce a label acquisition algorithm that sequentially decides whether to request the ``labels'' of feature samples from an unlabeled data stream, where the labels correspond to the coefficients of the objective in the linear optimization. Our method is the fi

Masahiro Yabuno, Fumihiro China, Hirotaka Terai, Shigehito Miki

Superconducting strip single-photon detectors offer excellent photon detection performance and are indispensable tools for cutting-edge optical science and technologies, including photonic quantum computation and quantum networks. Ultra-wide superconducting strips with widths of tens of micrometers are desirable to achieve high polarization-independent detec

Junxue Yang, Xin Liao

Unlike hiding bit-level messages, hiding image-level messages is more challenging, which requires large capacity, high imperceptibility, and high security. Although recent advances in hiding image-level messages have been remarkable, existing schemes are limited to lossless spatial images as covers and cannot be directly applied to JPEG images, the ubiquitou

Henniart Guy, Vignéras Marie-France

For a central division algebra $D$ of dimension $d^2$ over a finite extension $F$ of $\mathbb Q_p$ or of $\mathbb F_p((t))$, a field $R$ of characteristic prime to $p$, and an irreducible smooth $R$-representation $\pi$ of $G=GL_n(D)$, we show that for small enough compact open pro-$p$ subgroup $K$ of $G$, the restriction of $\pi$ to $K$ is the same as that

Yi C. Huang, Li Liu

In proving Rellich inequalities in the framework of equalities, N. Bez, S. Machihara, and T. Ozawa obtained some interesting norm inequalities in the spirit of Evans and Lewis that compare the standard Laplacian with its radial and spherical components. In this paper we give a simple unified proof and a strict improvement of these Evans-Lewis inequalities in

Keitaro Anai, Yutaro Enomoto, Hiroto Omura, Koji Nagano

Optical phase-insensitive heterodyne (beat-note) detection, which measures the relative phase of two beams at different frequencies through their interference, is a key sensing technology for various spatial/temporal measurements, such as frequency measurements in optical frequency combs. However, its sensitivity is limited not only by shot noise from the si

Xue-Ru Zhang, Min-Qian Liu, Dennis K. J. Lin, Yong-Dao Zhou

Sequential Latin hypercube designs have recently received great attention for computer experiments. Much of the work has been restricted to invariant spaces. The related systematic construction methods are inflexible while algorithmic methods are ineffective for large designs. For such designs in space contraction, systematic construction methods have not be

Daniel Byrne, Lawrence Ong, Parastoo Sadeghi, Badri N. Vellambi

We propose and study a variant of pliable index coding (PICOD) where receivers have preferences for their unknown messages and give each unknown message a preference ranking. We call this the preferential pliable index-coding (PPICOD) problem and study the Pareto trade-off between the code length and overall satisfaction metric among all receivers. We derive

Katsuki Fukumoto, Koki Yamada, Yuichi Tanaka, Hoi-To Wai

We propose a node clustering method for time-varying graphs based on the assumption that the cluster labels are changed smoothly over time. Clustering is one of the fundamental tasks in many science and engineering fields including signal processing, machine learning, and data mining. Although most existing studies focus on the clustering of nodes in static

Hongyuan Lu, Haoran Yang, Haoyang Huang, Dongdong Zhang

Large language models (LLMs) have shown surprisingly good performance in multilingual neural machine translation (MNMT) even when trained without parallel data. Yet, despite the fact that the amount of training data is gigantic, they still struggle with translating rare words, particularly for low-resource languages. Even worse, it is usually unrealistic to

Jianheng Tang, Kangfei Zhao, Jia Li

Entity alignment is the task of identifying corresponding entities across different knowledge graphs (KGs). Although recent embedding-based entity alignment methods have shown significant advancements, they still struggle to fully utilize KG structural information. In this paper, we introduce FGWEA, an unsupervised entity alignment framework that leverages t

Juan Carlos Fernández, Oscar Palmas, Jonatán Torres Orozco

We study the optimal partition problem for the prescribed constant $Q$-curvature equation induced by the higher order conformal operators under the effect of cohomogeneity one actions on Einstein manifolds with positive scalar curvature. This allows us to give a precise description of the solution domains and their boundaries in terms of the orbits of the ac

Hailiang Zhao, Shuiguang Deng, Zhengzhe Xiang, Xueqiang Yan

Multi-server jobs that request multiple computing resources and hold onto them during their execution dominate modern computing clusters. When allocating the multi-type resources to several co-located multi-server jobs simultaneously in online settings, it is difficult to make the tradeoff between the parallel computation gain and the internal communication

Guihong Wang, Yuqing Li, Tao Luo, Zheng Ma

In this work, we systematically investigate linear multi-step methods for differential equations with memory. In particular, we focus on the numerical stability for multi-step methods. According to this investigation, we give some sufficient conditions for the stability and convergence of some common multi-step methods, and accordingly, a notion of A-stabili

Satyadev Nandakumar, Subin Pulari, Akhil S

Finite-state dimension (Dai, Lathrop, Lutz, and Mayordomo (2004)) quantifies the information rate in an infinite sequence as measured by finite-state automata. In this paper, we define a relative version of finite-state dimension. The finite-state relative dimension $dim_{FS}^Y(X)$ of a sequence $X$ relative to $Y$ is the finite-state dimension of $X$ measur

Wenyue Hua, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang

Recommendation foundation model utilizes large language models (LLM) for recommendation by converting recommendation tasks into natural language tasks. It enables generative recommendation which directly generates the item(s) to recommend rather than calculating a ranking score for each and every candidate item as in traditional recommendation models, simpli

Yixin Zhang, Maciej A. Mazurowski

Shape learning, or the ability to leverage shape information, could be a desirable property of convolutional neural networks (CNNs) when target objects have specific shapes. While some research on the topic is emerging, there is no systematic study to conclusively determine whether and under what circumstances CNNs learn shape. Here, we present such a study

Anna Nadtochiy, Peter Luu, Scott E. Fraser, Thai V. Truong

Summary: In functional imaging studies, accurately synchronizing the time course of experimental manipulations and stimulus presentations with resulting imaging data is crucial for analysis. Current software tools lack such functionality, requiring manual processing of the experimental and imaging data, which is error-prone and potentially non-reproducible.

Chuang Zhang, Rulei Guo, Meng Lian, Junichiro Shiomi

The electron-phonon coupling in ultrafast heating systems is studied within the framework of Boltzmann transport equation (BTE) with coupled electron and phonon transport. A discrete unified gas kinetic scheme is developed to solve the BTE, in which the electron/phonon advection, scattering and electron-phonon interactions are coupled together within one tim

Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu

Personalized content-based recommender systems have become indispensable tools for users to navigate through the vast amount of content available on platforms like daily news websites and book recommendation services. However, existing recommenders face significant challenges in understanding the content of items. Large language models (LLMs), which possess

Bhavya Sehgal, Vaishnavi Mendu, Aparna Mendu

This research paper explores the application of style transfer in computer vision using RGB images and their corresponding depth maps. We propose a novel method that incorporates the depth map and a heatmap of the RGB image to generate more realistic style transfer results. We compare our method to the traditional neural style transfer approach and find that

Sanjay Saha, Rashindrie Perera, Sachith Seneviratne, Tamasha Malepathirana

The recent renaissance in generative models, driven primarily by the advent of diffusion models and iterative improvement in GAN methods, has enabled many creative applications. However, each advancement is also accompanied by a rise in the potential for misuse. In the arena of the deepfake generation, this is a key societal issue. In particular, the ability

Wenwu Gong, Zhejun Huang, Lili Yang

In intelligent transportation systems, traffic data imputation, estimating the missing value from partially observed data is an inevitable and challenging task. Previous studies have not fully considered traffic data's multidimensionality and spatiotemporal correlations, but they are vital to traffic data recovery, especially for high-level missing scenarios

Lina Liu, Dongning Guo

This paper studies the performance of a transmission and reception scheme for massive access under some practical challenges. One challenge is the near-far problem, i.e., an access point often receives signals from different transmitting devices at vastly different signal strengths. Another challenge is that the signals from different devices may be subject

Tyler Richey-Yowell, Evgenya L. Shkolnik, Adam C. Schneider, Sarah Peacock

Low mass stars ($\leq 1$ M$_{\odot}$) are some of the best candidates for hosting planets with detectable life because of these stars' long lifetimes and relative planet to star mass and radius ratios. An important aspect of these stars to consider is the amount of ultraviolet (UV) and X-ray radiation incident on planets in the habitable zones due to the abi

Yi Liu, Xin-Lei Zhang, Guowei He

This paper presents a neural network-based turbulence modeling approach for transonic flows based on the ensemble Kalman method. The approach adopts a tensor basis neural network for the Reynolds stress representation, with modified inputs to consider fluid compressibility. The normalization of input features is also investigated to avoid feature collapsing

Junrui Xiao, Zhikai Li, Lianwei Yang, Qingyi Gu

As emerging hardware begins to support mixed bit-width arithmetic computation, mixed-precision quantization is widely used to reduce the complexity of neural networks. However, Vision Transformers (ViTs) require complex self-attention computation to guarantee the learning of powerful feature representations, which makes mixed-precision quantization of ViTs s

Yangming Cheng, Liulei Li, Yuanyou Xu, Xiaodi Li

This report presents a framework called Segment And Track Anything (SAMTrack) that allows users to precisely and effectively segment and track any object in a video. Additionally, SAM-Track employs multimodal interaction methods that enable users to select multiple objects in videos for tracking, corresponding to their specific requirements. These interactio

Yi Dai, Hao Lang, Yinhe Zheng, Fei Huang

Real-world data often have an open long-tailed distribution, and building a unified QA model supporting various tasks is vital for practical QA applications. However, it is non-trivial to extend previous QA approaches since they either require access to seen tasks of adequate samples or do not explicitly model samples from unseen tasks. In this paper, we def

Kyle T. Yoshida, Joel X. Kiernan, Rachel A. G. Adenekan, Steven H. Trinh

Vibration feedback is common in everyday devices, from virtual reality systems to smartphones. However, cognitive and physical activities may impede our ability to sense vibrations from devices. In this study, we develop and characterize a smartphone platform to investigate how a shape-memory task (cognitive activity) and walking (physical activity) impair h

Yi Dai, Hao Lang, Yinhe Zheng, Bowen Yu

Lifelong learning (LL) is an important ability for NLP models to learn new tasks continuously. Architecture-based approaches are reported to be effective implementations for LL models. However, it is non-trivial to extend previous approaches to domain incremental LL scenarios since they either require access to task identities in the testing phase or cannot

Roni Muslim, Sasfan A. Wella, Ahmad R. T. Nugraha

Independence and anticonformity are two types of social behaviors known in social psychology literature and the most studied parameters in the opinion dynamics model. These parameters are responsible for continuous (second-order) and discontinuous (first-order) phase transition phenomena. Here, we investigate the majority rule model in which the agents adopt

Mingliang Zhang, Zhen Cao, Juntao Liu, Liqiang Niu

In this paper, we introduce WeLayout, a novel system for segmenting the layout of corporate documents, which stands for WeChat Layout Analysis System. Our approach utilizes a sophisticated ensemble of DINO and YOLO models, specifically developed for the ICDAR 2023 Competition on Robust Layout Segmentation. Our method significantly surpasses the baseline, sec

Gurmeet Singh Punia

The connection between bulk and boundary thermodynamics in Einstein-Maxwell theory is well established using AdS/CFT correspondence. In the context of general higher derivative gravity coupled to a U(1) gauge field, we examine the resemblance of the first law of thermodynamics between bulk and boundary, followed by an extended phase space description on both

Pham Thi Hong, Hung Q. Nguyen, H. T. M. Nghiem

Poly(methyl methacrylate), PMMA, is a popular polymer for optical applications due to its superior transmission and reflection. However, its optical properties in the ultraviolet regime still need to be thoroughly studied. Using the reflection-transmission method, we determine its complex refractive index by numerically analyzing the measured data from thin

Hai-Liang Chen, Thomas M. Tauris, Xuefei Chen, Zhanwen Han

The formation path to ultra-compact X-ray binaries (UCXBs) with black hole (BH) accretors is still unclear. In the classical formation scenario, it is difficult to eject the massive envelope of the progenitor star of the BH via common envelope process. Given that some neutron stars (NSs) in binary systems evidently have birth masses close to $\sim 2.0\;M_\od

Amanul Islam, Fazidah Othman, Nazmus Sakib, Hafiz Md. Hasan Babu

Graphical passwords are implemented as an alternative scheme to replace alphanumeric passwords to help users to memorize their password. However, most of the graphical password systems are vulnerable to shoulder-surfing attack due to the usage of the visual interface. In this research, a method that uses shifting condition with digraph substitution rules is

Yu-Wen Lin, Tsz Ling Elaine Tang, Stefano Schiavon, Costas J. Spanos

The electronic design industry has undergone a significant transformation, transitioning from traditional hand-drawn designs to modern automated design processes. While Computer-Aided Design (CAD) tools emerged alongside the electronic industry, the current building design process has little to no automation. There is a need for a unified platform to address

Jason Z. S. Hu, Brigitte Pientka

We introduce layers to modal type theories, which subsequently enables type theories for pattern matching on code in meta-programming and clean and straightforward semantics.

Junlin Wu, Andrew Clark, Yiannis Kantaros, Yevgeniy Vorobeychik

While ensuring stability for linear systems is well understood, it remains a major challenge for nonlinear systems. A general approach in such cases is to compute a combination of a Lyapunov function and an associated control policy. However, finding Lyapunov functions for general nonlinear systems is a challenging task. To address this challenge, several me

A. V. Sadakov, V. A. Vlasenko, I. A. Troyan, O. A. Sobolevskiy

A comprehensive study of the vortex phases and vortex dynamics is presented for a recently discovered high-temperature superconductor YH$_6$ with T$_C$ (onset) of 215 K under pressure of 200 GPa.Thermal activation energy (U$_0$) is derived in the framework of thermally activated flux flow (TAFF) theory. The activation energy yields a power law dependence U$_

Dongyang Li, Ruixue Ding, Qiang Zhang, Zheng Li

With a fast developing pace of geographic applications, automatable and intelligent models are essential to be designed to handle the large volume of information. However, few researchers focus on geographic natural language processing, and there has never been a benchmark to build a unified standard. In this work, we propose a GeoGraphic Language Understand

Ekaterina O. Smolina, Lev A. Smirnov, Daniel Leykam, Daria A. Smirnova

Localized nonlinear modes at valley-Hall interfaces in staggered photonic graphene can be described in the long-wavelength limit by a nonlinear Dirac-like model including spatial dispersion terms. It leads to a modified nonlinear Schr\"odinger equation for the wave field amplitude that remarkably incorporates a nonlinear velocity term. We show that this nonl

Lei Yan, Zhijin Qin, Chunfeng Li, Rui Zhang

By transmitting task-related information only, semantic communications yield significant performance gains over conventional communications. However, the lack of mature semantic theory about semantic information quantification and performance evaluation makes it challenging to perform resource allocation for semantic communications, especially when multiple

Hao Yu, Bin Xue, Yanpeng Zhu, Jianlin Zhang

Social networks have provided a platform for the effective exchange of ideas or opinions but also served as a hotbed of polarization. While much research attempts to explore different causes of opinion polarization, the effect of perception bias caused by the network structure itself is largely understudied. To this end, we propose a threshold model that sim

Timothy Chu, Gary Miller, Noel Walkington

Spectral clustering is one of the most popular clustering algorithms that has stood the test of time. It is simple to describe, can be implemented using standard linear algebra, and often finds better clusters than traditional clustering algorithms like $k$-means and $k$-centers. The foundational algorithm for two-way spectral clustering, by Shi and Malik, c

Junpei Liao, Zhikai Chen, Liang Yi, Wenyuan Yang

Deep learning based video frame interpolation (VIF) method, aiming to synthesis the intermediate frames to enhance video quality, have been highly developed in the past few years. This paper investigates the adversarial robustness of VIF models. We apply adversarial attacks to VIF models and find that the VIF models are very vulnerable to adversarial example

Ron Eliav, Anya Ji, Yoav Artzi, Robert D. Hawkins

A long tradition of studies in psycholinguistics has examined the formation and generalization of ad hoc conventions in reference games, showing how newly acquired conventions for a given target transfer to new referential contexts. However, another axis of generalization remains understudied: how do conventions formed for one target transfer to completely d

Maomin Qing, Wei Xie

Quantum computing has emerged as a promising technology for solving problems that are intractable for classical computers. In this study, we introduce quantum computing and implement the Variational Quantum Eigensolver (VQE) algorithm using Qiskit on the IBM Quantum platform to calculate the ground state energy of a hydrogen molecule. We provide a theoretica

Shoujie Li, Mingshan He, Wenbo Ding, Linqi Ye

Manual oropharyngeal (OP) swab sampling is an intensive and risky task. In this article, a novel OP swab sampling device of low cost and high compliance is designed by combining the visuo-tactile sensor and the pneumatic actuator-based gripper. Here, a concave visuo-tactile sensor called CoTac is first proposed to address the problems of high cost and poor r

Ryo Watanabe, Keisuke Fujii, Hiroshi Ueda

In this paper, we introduce a tensor network (TN) scheme into the entanglement augmentation process of the synergistic optimization framework by Rudolph et al. [arXiv:2208.13673] to build its process systematically for inhomogeneous systems. Our synergistic approach first embeds the variational optimal solution of the TN state with the entropic area law, whi

Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng

Recent legislation of the "right to be forgotten" has led to the interest in machine unlearning, where the learned models are endowed with the function to forget information about specific training instances as if they have never existed in the training set. Previous work mainly focuses on computer vision scenarios and largely ignores the essentials of unlea

Anom Trenggana, Freddy P. Zen, Getbogi Hikmawan

We have investigated the decoherence induced by the primordial graviton, using the influence functional method, to show whether this method is still effective in detecting graviton if the initial state is not a Bunch-Davies vacuum but rather a minimum uncertainty state. This minimum uncertainty condition allows the initial state of the primordial graviton to

Yijun Fan, Yanxiao Liu, Yi Chen, Shenghao Yang

We consider a generalized collision channel model for general multi-user communication systems, an extension of Massey and Mathys' collision channel without feedback for multiple access communications. In our model, there are multiple transmitters and receivers sharing the same communication channel. The transmitters are not synchronized and arbitrary time o