April 2024 arXiv papers — page 150

Richard Berkovits

The Anderson localization transition in quantum graphs has garnered significant recent attention due to its relevance to many-body localization studies. Typically, graphs are constructed using top-down methods. Here, we explore a bottom-up approach, employing a simple local rewriting rule to construct the graph. Through the use of ratio statistics for the en

Kunyao Lan, Cong Ming, Binwei Yao, Lu Chen

Chatbots can serve as a viable tool for preliminary depression diagnosis via interactive conversations with potential patients. Nevertheless, the blend of task-oriented and chit-chat in diagnosis-related dialogues necessitates professional expertise and empathy. Such unique requirements challenge traditional dialogue frameworks geared towards single optimiza

Alexandra Kogan, Roy Leizer, Szymon Wilk, David Glasspool

In this paper, we share our experience of developing a hybrid execution environment for computer-interpretable guidelines (CIGs) in PROforma. The proposed environment is part of the CAPABLE system which provides coaching for cancer patients and decision support for physicians. It extends a standard PROforma execution engine - Deontics Engine (DE) - with addi

Mihai-Silviu Lazorec

A finite group $G$ is said to be a $\mathcal{B}_{\psi}$-group if $\psi(H)<|G|$ for any proper subgroup $H$ of $G$, where $\psi(H)$ denotes the sum of element orders of $H$. In this paper, we characterize the $\mathcal{B}_{\psi}$-groups up to the class of finite nilpotent groups. We also study the above inequality in the case of finite $P$-groups and Schmidt

Yulong Lu, Wuzhe Xu

Solving partial differential equations (PDEs) on fine spatio-temporal scales for high-fidelity solutions is critical for numerous scientific breakthroughs. Yet, this process can be prohibitively expensive, owing to the inherent complexities of the problems, including nonlinearity and multiscale phenomena. To speed up large-scale computations, a process known

Yuzhen Zhan, Li Jin

Dynamic routing is one of the representative control scheme in transportation, production lines, and data transmission. In the modern context of connectivity and autonomy, routing decisions are potentially vulnerable to malicious attacks. In this paper, we consider the dynamic routing problem over parallel traffic links in the face of such threats. An attack

Takato Mizuho, Takuji Narumi, Hideaki Kuzuoka

Recall impairment in a different environmental context from learning is called context-dependent forgetting. Two learning methods have been proposed to prevent context-dependent forgetting: reinstatement and decontextualization. Reinstatement matches the environmental context between learning and retrieval, whereas decontextualization involves repeated learn

Yuta Koike

The recent seminal work of Chernozhukov, Chetverikov and Kato has shown that bootstrap approximation for the maximum of a sum of independent random vectors is justified even when the dimension is much larger than the sample size. In this context, numerical experiments suggest that third-moment matching bootstrap approximations would outperform normal approxi

Valentina Martelli, Amaury Anquetil, Lin Al Atik, J. Larrea Jiménez

The first-order phase transition between the liquid and gaseous phases ends at a critical point. Critical opalescence occurs at this singularity. Discovered in 1822, it is known to be driven by diverging fluctuations in the density. During the past two decades, boundaries between the gas-like and liquid-like regimes have been theoretically proposed and exper

Giampiero Esposito, Valeria Fionda

This paper considers the possibility that abstract thinking and advanced synthesis skills might encourage extraterrestrial civilizations to accept communication with mankind on Earth. For this purpose, a notation not relying upon the use of alphabet and numbers is proposed, in order to denote just some basic geometric structures of current physical theories:

Archana Arya, Kaushik Kalyanaraman

We propose an arbitrarily higher (even) order implicit leapfrog scheme for time discretization of a three-field formulation of Maxwell's equations. We use this in conjunction with an arbitrarily higher-order and compatible discretization using finite element spaces that form a de Rham complex. In doing so, we provide a generalization of an earlier work build

Jiankai Tang, Xinyi Li, Jiacheng Liu, Xiyuxing Zhang

Remote photoplethysmography (rPPG) emerges as a promising method for non-invasive, convenient measurement of vital signs, utilizing the widespread presence of cameras. Despite advancements, existing datasets fall short in terms of size and diversity, limiting comprehensive evaluation under diverse conditions. This paper presents an in-depth analysis of the V

Angela M. Coe, Guohong Li, Eva Y. Andrei

One of the daunting challenges in modern low temperature scanning tunneling microscopy (STM) is the difficulty of combining atomic resolution with cryogen free cooling. Further functionality needs, such as ultra-high vacuum (UHV), high magnetic field, and compatibility with {\mu}m-sized samples, pose additional challenges to an already ambitious build. We pr

Gang Qu, Ping Wang, Xin Yuan

Single-pixel imaging (SPI) is a potential computational imaging technique which produces image by solving an illposed reconstruction problem from few measurements captured by a single-pixel detector. Deep learning has achieved impressive success on SPI reconstruction. However, previous poor reconstruction performance and impractical imaging model limit its r

Wern Ng, Yongqiang Wen, Neil Alford, Daan M. Arroo

Masers have the potential to transform medical sensing and boost qubit readout detection due to their superb low-noise amplification. The negatively-charged nitrogen vacancy (NV-) diamond maser is the only continuous-wave solid-state maser discovered at room temperature, however it suffers from requiring large and bulky magnets which prevent its more widespr

Lin Huang, Deng-Shan Wang, Xiaodong Zhu

In this paper, the renowned Riemann-Hilbert method is employed to investigate the initial value problem of Tzitz\'eica equation on the line. Initially, our analysis focuses on elucidating the properties of two reflection coefficients, which are determined by the initial values. Subsequently, leveraging these reflection coefficients, we construct a Riemann-Hi

Jinpeng Wang, Bin Chen, Qiang Zhang, Zaiqiao Meng

Deep quantization methods have shown high efficiency on large-scale image retrieval. However, current models heavily rely on ground-truth information, hindering the application of quantization in label-hungry scenarios. A more realistic demand is to learn from inexhaustible uploaded images that are associated with informal tags provided by amateur users. Tho

Cangqing Wang, Yutian Yang, Ruisi Li, Dan Sun

The rapid advancement of Large Language Models (LLMs) has inaugurated a transformative epoch in natural language processing, fostering unprecedented proficiency in text generation, comprehension, and contextual scrutiny. Nevertheless, effectively handling extensive contexts, crucial for myriad applications, poses a formidable obstacle owing to the intrinsic

Pingping Zhang, Tianyu Yan, Yang Liu, Huchuan Lu

As an important pillar of underwater intelligence, Marine Animal Segmentation (MAS) involves segmenting animals within marine environments. Previous methods don't excel in extracting long-range contextual features and overlook the connectivity between discrete pixels. Recently, Segment Anything Model (SAM) offers a universal framework for general segmentatio

Mohammad Awwad, Sheikh Ifatur Rahman, Chandan Joishi, Betty Lise Anderson

This paper describes the design and characteristics of monolithically integrated three-terminal gated III-Nitride light emitting diodes (LEDs) devices. The impact of channel doping and thickness on the voltage penalty of the transistor-LED hybrid device is analyzed, and it is shown that with appropriate design, low voltage drop can be realized across integra

Barnaby van Straaten, Joseph Hickie, Lucas Schorling, Jonas Schuff

Semiconductor quantum dot arrays are a leading architecture for the development of quantum technologies. Over the years, the constant capacitance model has served as a fundamental framework for simulating, understanding, and navigating the charge stability diagrams of small quantum dot arrays. However, while the size of the arrays keeps growing, solving the

Gaojun Luo, Lin Sok, Martianus Frederic Ezerman, San Ling

Hermitian hulls of linear codes are interesting for theoretical and practical reasons alike. In terms of recent application, linear codes whose hulls meet certain conditions have been utilized as ingredients to construct entanglement-assisted quantum error correcting codes. This family of quantum codes is often seen as a generalization of quantum stabilizer

Haifeng Wang, Hao Xu, Jun Wang, Jian Zhou

Recognizing various surgical tools, actions and phases from surgery videos is an important problem in computer vision with exciting clinical applications. Existing deep-learning-based methods for this problem either process each surgical video as a series of independent images without considering their dependence, or rely on complicated deep learning models

Xiaoyan Zhou, Ying Zhang, Wenjia Niu, Jiqiang Liu

The open-source software (OSS) ecosystem suffers from security threats caused by malware.However, OSS malware research has three limitations: a lack of high-quality datasets, a lack of malware diversity, and a lack of attack campaign contexts. In this paper, we first build the largest dataset of 24,356 malicious packages from online sources, then propose a k

Zihao Wei, Jingcheng Deng, Liang Pang, Hanxing Ding

The extensive utilization of large language models (LLMs) underscores the crucial necessity for precise and contemporary knowledge embedded within their intrinsic parameters. Existing research on knowledge editing primarily concentrates on monolingual scenarios, neglecting the complexities presented by multilingual contexts and multi-hop reasoning. To addres

Jinchi Dong, Richard S. J. Tol, Fangzhi Wang

The majority of estimates of the social cost of carbon use preference parameters calibrated to data for North America and Europe. We here use representative data for attitudes to time and risk across the world. The social cost of carbon is substantially higher in the global north than in the south. The difference is more pronounced if we count people rather

Eva Miranda, Jonathan Weitsman

We establish analogs of the Darboux, Moser and Weinstein theorems for prequantum systems. We show that two prequantum systems on a manifold with vanishing first cohomology, with symplectic forms defining the same cohomology class and homotopic to each other within that class, differ only by a symplectomorphism and a gauge transformation. As an application, w

Andreas Björklund, Radu Curticapean, Thore Husfeldt, Petteri Kaski

In this paper we further explore the recently discovered connection by Bj\"{o}rklund and Kaski [STOC 2024] and Pratt [STOC 2024] between the asymptotic rank conjecture of Strassen [Progr. Math. 1994] and the three-way partitioning problem. We show that under the asymptotic rank conjecture, the chromatic number of an $n$-vertex graph can be computed determini

Demetris Lappas, Vasileios Argyriou, Dimitrios Makris

We introduce Dynamic Distinction Learning (DDL) for Video Anomaly Detection, a novel video anomaly detection methodology that combines pseudo-anomalies, dynamic anomaly weighting, and a distinction loss function to improve detection accuracy. By training on pseudo-anomalies, our approach adapts to the variability of normal and anomalous behaviors without fix

Rajat Verma, Mithun Debnath, Shagun Mittal, Satish V. Ukkusuri

Locational measures of accessibility are widely used in urban and transportation planning to understand the impact of the transportation system on influencing people's access to places. However, there is a considerable lack of measurement standards and publicly available data. We propose a generalized measure of locational accessibility that has a comprehens

Junping Li

This paper concentrates on the general birth-death processes with two different types of catastrophes. The Laplace transform of transition probability function for birth-death processes with two-type catastrophes are is successfully expressed with the Laplace transform of transition probability function of the birth-death processes without catastrophe. The f

Aurélie Beaufrère, Nora Ouzir, Paul Emile Zafar, Astrid Laurent-Bellue

The diagnosis of primary liver cancers (PLCs) can be challenging, especially on biopsies and for combined hepatocellular-cholangiocarcinoma (cHCC-CCA). We automatically classified PLCs on routine-stained biopsies using a weakly supervised learning method. Weak tumour/non-tumour annotations served as labels for training a Resnet18 neural network, and the netw

Hang Liu, Hong Guo, Ru Ling

It was recently found that the optical field fluctuations in self-defocusing media can be described by sound waves propagating in a two-dimensional photon-fluid. This photon-fluid is controlled by the driving beam and serves as the background in which the sound waves can experience an effective curved spacetime, such that it provides a new platform of studyi

Yichen You

We investigate the construction of $\pm1$-valued completely multiplicative functions that take the value $+1$ at at most $k$ consecutive integers, which we call length-$k$ functions. We introduce a way to extend the length based on the idea of the "rotation trick" and such an extension can be quantified by the number of modified primes. Under the assumption

Diego Turenne, Igor Vaskivskiy, Klaus Sokolowski-Tinten, Xijie Wang

Light-matter interaction at the nanoscale in magnetic alloys and heterostructures is a topic of intense research in view of potential applications in high-density magnetic recording. While the element-specific dynamics of electron spins is directly accessible to resonant x-ray pulses with femtosecond time structure, the possible element-specific atomic motio

Anirban Mukherjee, Hannah Hanwen Chang

Social science research often hinges on the relationship between categorical variables and outcomes. We introduce CAVIAR, a novel method for embedding categorical variables that assume values in a high-dimensional ambient space but are sampled from an underlying manifold. Our theoretical and numerical analyses outline challenges posed by such categorical var

Jie Liu, Yungui Gong, Zhu Yi

We investigate the constant-roll inflation with non-minimally kinetic coupling to the Einstein tensor. With the slow-roll parameter $\eta_\phi = -\ddot{\phi}/(H\dot{\phi})$ being a constant, we calculate the power spectra for scalar and tensor perturbations, and derive the expressions for the scalar spectral tilt $n_s$, the tensor spectral tilt $n_T$, and th

Enrico Savi

Let $L$ be the language of rings. We provide an axiomatization of the $L$-theories of quaternions and octonions and characterize their models: they coincide, up to isomorphism, with quaternion and octonion algebras over a real closed field, respectively. We bi-interpret these theories in terms of real closed fields and we prove they are complete, model compl

Osmery Hernández, Iñigo Liberal

Non-Hermitian (NH) photonic systems leverage gain and loss to open new directions for nanophotonic technologies. However, the quantum and thermal noise intrinsically associated with gain/loss affects the eigenvalue/eigenvector structure of NH systems, as well as its practical noise performance. Here, we present a comparative analysis of the impact of differe

Buda Bajić, Srđan Milićević, Aleksandar Antić, Slobodan Marković

For modeling the number of visits in Stopi\'{c}a cave (Serbia) we consider the classical Auto-regressive Integrated Moving Average (ARIMA) model, Machine Learning (ML) method Support Vector Regression (SVR), and hybrid NeuralPropeth method which combines classical and ML concepts. The most accurate predictions were obtained with NeuralPropeth which includes

Matheus Lohse, Rafael S. Castro, Aurelio T. Salton, Minyue Fu

This paper addresses the task of tracking Lissajous trajectories in the presence of quantized positioning sensors. To do so, theoretical results on tracking of continuous time periodic signals in the presence of output quantization are provided. With these results in hand, the application to Lissajous tracking is explored. The method proposed relies on the i

Yixuan Sun, Ololade Sowunmi, Romain Egele, Sri Hari Krishna Narayanan

Training an effective deep learning model to learn ocean processes involves careful choices of various hyperparameters. We leverage the advanced search algorithms for multiobjective optimization in DeepHyper, a scalable hyperparameter optimization software, to streamline the development of neural networks tailored for ocean modeling. The focus is on optimizi

Jianghao Wu, Dong Guo, Guotai Wang, Qiang Yue

Adapting a medical image segmentation model to a new domain is important for improving its cross-domain transferability, and due to the expensive annotation process, Unsupervised Domain Adaptation (UDA) is appealing where only unlabeled images are needed for the adaptation. Existing UDA methods are mainly based on image or feature alignment with adversarial

Jinyi Xu, Zuowei Zhang, Ze Lin, Yixiang Chen

It is still challenging to cluster multi-view data since existing methods can only assign an object to a specific (singleton) cluster when combining different view information. As a result, it fails to characterize imprecision of objects in overlapping regions of different clusters, thus leading to a high risk of errors. In this paper, we thereby want to ans

Bin Lu, Tingyan Ma, Xiaoying Gan, Xinbing Wang

Graph Neural Networks (GNNs) are widely deployed in vast fields, but they often struggle to maintain accurate representations as graphs evolve. We theoretically establish a lower bound, proving that under mild conditions, representation distortion inevitably occurs over time. To estimate the temporal distortion without human annotation after deployment, one

Djamel Benredjem, Jean-Christophe Pain

We propose a semi-empirical formula for the cross section of ionization by electron impact. The formula involves adjustable parameters which are determined by comparison with measured or numerically calculated cross sections. In the latter case, the ions are perturbed by their environment which is a high-density plasma. As a consequence, the cross section is

Francesco Fumagalli, Attila Maróti

If $A$, $B$, $C$ are subsets in a finite simple group of Lie type $G$ at least two of which are normal with $|A||B||C|$ relatively large, then we establish a stronger conclusion than $ABC = G$. This is related to a theorem of Gowers and is a generalization of a theorem of Larsen, Shalev, Tiep and the second author and Pyber.

Chen Yang, Junjie Chen, Bin Lin, Ziqi Wang

Automatic test generation plays a critical role in software quality assurance. While the recent advances in Search-Based Software Testing (SBST) and Large Language Models (LLMs) have shown promise in generating useful tests, these techniques still struggle to cover certain branches. Reaching these hard-to-cover branches usually requires constructing complex

John S. Russo, Tim Mahoney, Kirill Kokorin, Ashley Reynolds

Multiple Sclerosis (MS) is a severely disabling condition that leads to various neurological symptoms. A Brain-Computer Interface (BCI) may substitute some lost function; however, there is a lack of BCI research in people with MS. To progress this research area effectively and efficiently, we aimed to evaluate user needs and assess the feasibility and user-c

Jürgen Groß, Annette Möller

In this note the use of the zero degree non-central chi squared distribution as predictive distribution for ensemble postprocessing is investigated. It has a point mass at zero by definition, and is thus particularly suited for postprocessing weather variables naturally exhibiting large numbers of zeros, such as precipitation, solar radiation or lightnings.

Mael Jullien, Marco Valentino, André Freitas

Large Language Models (LLMs) are at the forefront of NLP achievements but fall short in dealing with shortcut learning, factual inconsistency, and vulnerability to adversarial inputs.These shortcomings are especially critical in medical contexts, where they can misrepresent actual model capabilities. Addressing this, we present SemEval-2024 Task 2: Safe Biom

Alessio Brini, Jimmie Lenz

The paper analyzes the cryptocurrency ecosystem at both the aggregate and individual levels to understand the factors that impact future volatility. The study uses high-frequency panel data from 2020 to 2022 to examine the relationship between several market volatility drivers, such as daily leverage, signed volatility and jumps. Several known autoregressive

Colin Defant, Dominic Searles

We extend the notion of ascent-compatibility from symmetric groups to all Coxeter groups, thereby providing a type-independent framework for constructing families of modules of $0$-Hecke algebras. We apply this framework in type $B$ to give representation-theoretic interpretations of a number of noteworthy families of type-$B$ quasisymmetric functions. Next,

Yutong Xie, Qi Chen, Sinuo Wang, Minh-Son To

Current vision-language pre-training (VLP) methodologies predominantly depend on paired image-text datasets, a resource that is challenging to acquire in radiology due to privacy considerations and labelling complexities. Data augmentation provides a practical solution to overcome the issue of data scarcity, however, most augmentation methods exhibit a limit

Hao Wang, Yanping Chen, Weizhe Yang, Yongbin Qin

Transforming a sentence into a two-dimensional (2D) representation (e.g., the table filling) has the ability to unfold a semantic plane, where an element of the plane is a word-pair representation of a sentence which may denote a possible relation representation composed of two named entities. The 2D representation is effective in resolving overlapped relati

Stephan Kucera, Christian Haen, Elena Arenskötter, Tobias Bauer

We report on the implementation of quantum entanglement distribution and quantum state teleportation over a 14.4-km urban dark-fiber link, which is partially underground, partially overhead, and patched in several stations. We characterize the link for its use as a quantum channel and realize its active polarization stabilization. Using a type-II cavity-enha

Zijin Yang, Kai Zeng, Kejiang Chen, Han Fang

Ethical concerns surrounding copyright protection and inappropriate content generation pose challenges for the practical implementation of diffusion models. One effective solution involves watermarking the generated images. However, existing methods often compromise the model performance or require additional training, which is undesirable for operators and

Dariusz Buraczewski, Alexander Iksanov, Alexander Marynych

For a right-continuous nondecreasing and unbounded function $V$ of at most exponential growth, which vanishes on the negative halfline, we investigate the asymptotic behavior of the Lebesgue-Stieltjes convolution powers $V^{\ast(j)}(t)$ as both $j$ and $t$ tend to infinity. We obtain a comprehensive asymptotic formula for $V^{\ast(j)}(t)$, which is valid acr

Safak Alpay, Svetlana Gorokhova

We study almost L(M) weakly compact and order L(M) weakly compact operators in Banach spaces. Several further topics related to these operators are investigated.

Yu Lei, Guoshuai Sheng, Fangfang Li, Quanxue Gao

Zero-shot learning(ZSL) aims to recognize new classes without prior exposure to their samples, relying on semantic knowledge from observed classes. However, current attention-based models may overlook the transferability of visual features and the distinctiveness of attribute localization when learning regional features in images. Additionally, they often ov

Victor R. Kebande

Virtual Laboratories (V Labs) have in the recent past become part and parcel of remote teaching in practical hands-on approaches, particularly in Cybersecurity distance courses. Their potential is meant to assist learners with hands-on practical laboratory exercises irrespective of geographical location. Nevertheless, adopting V Labs in didactic approaches i

Federico Manzoni

Gravitational solitons (gravisolitons) are particular exact solutions of Einstein field equation in vacuum build on a given background solution. Their interpretation is not yet fully clear but they contain many of the physically relevant solutions low $N$-solitons solutions. However, a systematic study and characterization of gravisolitons solution for every

Yanxiao Sun, Jiang Wu, Maosheng Jiang, Steven M. Wise

In this study, we have derived a thermodynamically consistent phase-field model for two-phase flows with thermocapillary effects. This model accommodates variations in physical properties such as density, viscosity, heat capacity, and thermal conductivity between the two components. The model equations encompass a Cahn-Hilliard equation with the volume fract

Yuhang Zhou, Zeping Li, Siyu Tian, Yuchen Ni

Large language models (LLMs) are increasingly being applied across various specialized fields, leveraging their extensive knowledge to empower a multitude of scenarios within these domains. However, each field encompasses a variety of specific tasks that require learning, and the diverse, heterogeneous data across these domains can lead to conflicts during m

Arian Baloochestani, Hanish Gogada, Leander Jehl, Hein Meling

Many blockchain platforms use committee-based consensus for scalability, finality, and security. In this consensus scheme, a committee decides which blocks get appended to the chain, typically through several voting phases. Platforms typically leverage the committee members' recorded votes to reward, punish, or detect failures. A common approach is to let th

Yi Luo, Jianwei Yu, Hangting Chen, Rongzhi Gu

We introduce Gull, a generative multifunctional audio codec. Gull is a general purpose neural audio compression and decompression model which can be applied to a wide range of tasks and applications such as real-time communication, audio super-resolution, and codec language models. The key components of Gull include (1) universal-sample-rate modeling via sub

Yuanfeng Xu, Yuhao Chen, Zhongzhan Huang, Zijian He

Recent video editing advancements rely on accurate pose sequences to animate subjects. However, these efforts are not suitable for cross-species animation due to pose misalignment between species (for example, the poses of a cat differs greatly from that of a pig due to differences in body structure). In this paper, we present AnimateZoo, a zero-shot diffusi

Yueliang Duan, Can Zhang

Given an equidistributed set in the whole Euclidean space, we have established in [1] that there exists a constant positive $C$ such that the observability inequality of diffusion equations holds for all $T\in]0,1[$, with an observability cost being of the form $Ce^{C/T}$. In this paper, for any small constant $\varepsilon>0$, we prove that there exists a no

A. N. Panov

The general linear group GL(n) acts on the direct sum of $m$ copies of Mat(n) by the adjoint action. The action of GL(n) induces the action of the unitriangular subgroup U. We present the system of free generators of the field of U-invariants.

Jan Held, Hani Itani, Anthony Cioppa, Silvio Giancola

The rapid advancement of artificial intelligence has led to significant improvements in automated decision-making. However, the increased performance of models often comes at the cost of explainability and transparency of their decision-making processes. In this paper, we investigate the capabilities of large language models to explain decisions, using footb

Zhihui Deng, Yuanyuan Duan, Leilai Shao, Xiaolei Zhu

Chiplet-based systems, integrating various silicon dies manufactured at different integrated circuit technology nodes on a carrier interposer, have garnered significant attention in recent years due to their cost-effectiveness and competitive performance. The widespread adoption of reinforcement learning as a sequential placement method has introduced a new

Umut Nefta Kanilmaz, Bernd Resch, Roland Holzinger, Christian Wasner

The emergence of the COVID-19 pandemic, followed by policy measures to combat the virus, evoked public protest movements world-wide. These movements emerged through virtual social networks as well as local protest gatherings. Prior research has studied such movements solely in the virtual space through social network analysis, thereby disregarding the role o

Sanwoo Lee, Yida Cai, Desong Meng, Ziyang Wang

Advances in automated essay scoring (AES) have traditionally relied on labeled essays, requiring tremendous cost and expertise for their acquisition. Recently, large language models (LLMs) have achieved great success in various tasks, but their potential is less explored in AES. In this paper, we show that our zero-shot prompting framework, Multi Trait Speci

Yichen Bao, Han Lu, Quanxue Gao

Fuzzy K-Means clustering is a critical technique in unsupervised data analysis. Unlike traditional hard clustering algorithms such as K-Means, it allows data points to belong to multiple clusters with varying degrees of membership, determined through iterative optimization to establish optimal cluster centers and memberships, thereby achieving fuzzy partitio

Francesco Veneziano, Solomon Vishkautsan

We study how the field of definition of a rational function changes under iteration. We provide a complete classification of polynomials with the property that the field of definition of one of their iterates drops in degree (over a given base field). We show with families of examples that this characterization does not hold for rational functions. Finally,

Harbir Antil, Paul Manns

Motivated by many applications, optimal control problems with integer controls have recently received a significant attention. Some state-of-the-art work uses perimeter-regularization to derive stationarity conditions and trust-region algorithms. However, the discretization is difficult in this case because the perimeter is concentrated on a set of dimension

Esa Ollila

We propose greedy Capon beamformer (GCB) for direction finding of narrow-band sources present in the array's viewing field. After defining the grid covering the location search space, the algorithm greedily builds the interference-plus-noise covariance matrix by identifying a high-power source on the grid using Capon's principle of maximizing the signal to i

Jiana Liao, Jinbo Wen, Jiawen Kang, Yang Zhang

Artificial Intelligence-Generated Content (AIGC) is a rapidly evolving field that utilizes advanced AI algorithms to generate content. Through integration with mobile edge networks, mobile AIGC networks have gained significant attention, which can provide real-time customized and personalized AIGC services and products. Since blockchains can facilitate decen

Weiwei Cao, Jianpeng Zhang, Yingda Xia, Tony C. W. Mok

Radiologists highly desire fully automated versatile AI for medical imaging interpretation. However, the lack of extensively annotated large-scale multi-disease datasets has hindered the achievement of this goal. In this paper, we explore the feasibility of leveraging language as a naturally high-quality supervision for chest CT imaging. In light of the limi

Aofan Jiang, Chaoqin Huang, Qing Cao, Yuchen Xu

The electrocardiogram (ECG) is an essential tool for diagnosing heart disease, with computer-aided systems improving diagnostic accuracy and reducing healthcare costs. Despite advancements, existing systems often miss rare cardiac anomalies that could be precursors to serious, life-threatening issues or alterations in the cardiac macro/microstructure. We add

J. Birch, S. Stendah, S. Dorri, A. Zubayer

We introduce a novel type of neutron interference mirrors based on a chemically homogeneous BxC (x>4) matrix with internal high precision 10B/11B isotope modulation. Simulations predict that these mirrors exhibit very high neutron reflectivities for a small number of bilayer periods. This is experimentally confirmed by neutron reflectivity measurements of mi

Yingsen Zeng, Yujie Zhong, Chengjian Feng, Lin Ma

Temporal Action Detection (TAD) focuses on detecting pre-defined actions, while Moment Retrieval (MR) aims to identify the events described by open-ended natural language within untrimmed videos. Despite that they focus on different events, we observe they have a significant connection. For instance, most descriptions in MR involve multiple actions from TAD.

Bowen Qin, Duanyu Feng, Xi Yang

Reinforcement Learning from Human Feedback (RLHF) is a widely used framework for the training of language models. However, the process of using RLHF to develop a language model that is well-aligned presents challenges, especially when it comes to optimizing the reward model. Our research has found that existing reward models, when trained using the tradition

Roi Livni

We analyze the sample complexity of full-batch Gradient Descent (GD) in the setup of non-smooth Stochastic Convex Optimization. We show that the generalization error of GD, with common choice of hyper-parameters, can be $\tilde \Theta(d/m + 1/\sqrt{m})$, where $d$ is the dimension and $m$ is the sample size. This matches the sample complexity of \emph{worst-

A. Zubayer, N. Ghafoor, A. Glavic, J. Stahn

Polarized neutron scattering is a very important analysis technique for studies of magnetism, spintronics, and high-sensitivity measurements, among others, offering invaluable information. Yet, the efficiency of such experiments rely on the performance of the polarizing neutron optics to provide high reflectivity and polarization. Presently, state-of-the-art

Qi Lv, Hao Li, Xiang Deng, Rui Shao

Multimodal Large Language Models (MLLMs) have shown impressive reasoning abilities and general intelligence in various domains. It inspires researchers to train end-to-end MLLMs or utilize large models to generate policies with human-selected prompts for embodied agents. However, these methods exhibit limited generalization capabilities on unseen tasks or sc

Vasile Berinde, Mădălina Păcurar

The aim of this note is threefold: first, to present a few relevant facts about the way in which the technique of enriching contractive mappings was introduced; secondly, to expose the main contributions in the area of enriched mappings established by the authors and their collaborators by using this technique; and third, to survey some related developments

Qingxiao Huang, Jie Hu, Yizhe Zhao, Kun Yang

Thanks to the application of metamaterials, holographic multiple-input multiple-output (H-MIMO) is expected to achieve a higher spatial diversity gain by enabling the ability to generate any current distribution on the surface. With the aid of electromagnetic (EM) manipulation capability of H-MIMO, integrated data and energy transfer (IDET) system can fully

Chen Zhang, Shi-Hao Zhang, Bowen Fu, Jing-Fei Zhang

We demonstrate that Debye shielding cannot be employed to constrain the cosmological abundance of magnetic monopoles, contrary to what is stated in the previous literature. Current model-independent bounds on the monopole abundance are then revisited for unit Dirac magnetic charge. We find that the Andromeda Parker bound can be employed to set an upper limit

Libo Qin, Qiguang Chen, Yuhang Zhou, Zhi Chen

Multilingual Large Language Models are capable of using powerful Large Language Models to handle and respond to queries in multiple languages, which achieves remarkable success in multilingual natural language processing tasks. Despite these breakthroughs, there still remains a lack of a comprehensive survey to summarize existing approaches and recent develo

Dongjing Shan, guiqiang chen

Vision Transformers (ViTs) have achieved impressive results in large-scale image classification. However, when training from scratch on small datasets, there is still a significant performance gap between ViTs and Convolutional Neural Networks (CNNs), which is attributed to the lack of inductive bias. To address this issue, we propose a Graph-based Vision Tr

Samuel L. Jacob, John Goold, Gabriel T. Landi, Felipe Barra

Quantum scattering is used ubiquitously in both experimental and theoretical physics across a wide range of disciplines, from high-energy physics to mesoscopic physics. In this work, we uncover universal relations for the energy fluctuations of a quantum system scattering inelastically with a particle at arbitrary kinetic energies. In particular, we prove a

Yigang Zhao Chaowei Zheng, Jiannan Su, GuangyongChen, MinGan

Non-Local Attention (NLA) is a powerful technique for capturing long-range feature correlations in deep single image super-resolution (SR). However, NLA suffers from high computational complexity and memory consumption, as it requires aggregating all non-local feature information for each query response and recalculating the similarity weight distribution fo

Michael Vogl

The Loschmidt echo is a popular quantity that allows making predictions about the stability of quantum states under time evolution. In our work, we present an approach that allows us to find a differential equation that can be used to compute the Loschmidt echo. This approach, while in essence perturbative, has the advantage that it converges at finite order

Xudong Yu, Chenjia Bai, Haoran He, Changhong Wang

Sequential decision-making is desired to align with human intents and exhibit versatility across various tasks. Previous methods formulate it as a conditional generation process, utilizing return-conditioned diffusion models to directly model trajectory distributions. Nevertheless, the return-conditioned paradigm relies on pre-defined reward functions, facin

Eva Boneš, Dawar Khan, Ciril Bohak, Benjamin A. Barad

In the field of volumetric data processing and analysis, extracting mid-surfaces from thinly bounded compartments is crucial for tasks such as surface area estimation and accurate modeling of biological structures, yet it has lacked a standardized approach. To bridge this gap, we introduce MidSurfer--a novel parameter-free method for extracting mid-surfaces

Natalia Osiadala, Marcin Kolakowski

In the paper a ballistocardiographic sensor for remote monitoring of activity and vital parameters is presented. The sensor is mainly intended for use in monitoring systems supporting care of older people. It allows to detect occupancy of a piece of furniture, to which it is attached and to estimate basic vital parameters (heart and respiration rates) of the

Gang Chen, Fanyi Yang, Zheyuan Zhang

In this paper we provide some error estimates for the div least-squares finite element method on elliptic problems. The main contribution is presenting a complete error analysis, which improves the current \emph{state-of-the-art} results. The error estimates for both the scalar and the flux variables are established by specially designed dual arguments with

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We search for the hadronic decay $\eta_c(2S)\to 2(\pi^+\pi^-)$ in the $\psi(3686)\to\gamma\eta_c(2S)$ radiative decay using $(27.12\pm 0.14)\times 10^8$ $\psi(3686)$ events collected by the BESIII detector at the BEPCII collider. No significant signal is found, and the upper limit of $\mathcal{B}[\psi(3686)\to\gamma\eta_c(2S)]\mathcal{B}[\eta_c(2S)\to 2(\pi^

Saeyoon Oh, Shin Yoo

When applying the Transformer architecture to source code, designing a good self-attention mechanism is critical as it affects how node relationship is extracted from the Abstract Syntax Trees (ASTs) of the source code. We present Code Structure Aware Transformer (CSA-Trans), which uses Code Structure Embedder (CSE) to generate specific PE for each node in A