October 2024 arXiv papers — page 89

Stanley Mugisha, Lynn tar Gutu, P Nagabhushan

Chicken swarm optimization is a new meta-heuristic algorithm which mimics the foraging hierarchical behavior of chicken. In this paper, we describe the preprocessing of handwritten document by contrast enhancement while preserving detail with an improved chicken swarm optimization algorithm.The results of the algorithm are compared with other existing meta h

Xin Zhou, Ping Nie, Yiwen Guo, Haojie Wei

Retrieval-Augmented Generation (RAG) significantly improved the ability of Large Language Models (LLMs) to solve knowledge-intensive tasks. While existing research seeks to enhance RAG performance by retrieving higher-quality documents or designing RAG-specific LLMs, the internal mechanisms within LLMs that contribute to the effectiveness of RAG systems rema

Omar Hesham Khater, Abdullahi Sani Shuaib, Sami Ul Haq, Abdul Jabbar Siddiqui

Chest X-rays (X-ray images) have been proven to be effective for the diagnosis of chest diseases, including Pneumonia, Lung Opacity, and COVID-19. However, relying on traditional medical methods for diagnosis from X-ray images is prone to delays and inaccuracies because the medical personnel who evaluate the X-ray images may have preconceived biases. For thi

Nitish Yadav

Understanding the large-scale structure of the universe remains a fundamental challenge in cosmology, with computational simulations providing critical insights into non-linear structure growth. Particularly, computational simulations critical information about the non-linear growth processes behind the observed large-scale structures. Inspired by the simila

N. Diaz-Naufal, L. Deeg, D. Zoepfl, C. M. F. Schneider

Dynamical backaction cooling has been demonstrated to be a successful method for achieving the motional quantum ground state of a mechanical oscillator in the resolved sideband regime, where the mechanical frequency is significantly larger than the cavity decay rate. Nevertheless, as mechanical systems increase in size, their frequencies naturally decrease,

Jean-Luc Baril, José L. Ramírez

We examine the distribution and popularity of different parameters (such as the number of descents, runs, valleys, peaks, right-to-left minima, and more) on the sets of increasing and flattened permutations. For each parameter, we provide an exponential generating function for its corresponding distribution and popularity.Additionally, we present one-to-one

Jenelle Feather, David Lipshutz, Sarah E. Harvey, Alex H. Williams

Image representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have strikingly different local geometries. Here, we propose a framework for comparing a set of image representations in terms of their local geometries. We quantify the local geometry of

Yongrui Yu, Yannian Gu, Shaoting Zhang, Xiaofan Zhang

Diffusion models have achieved significant success in both natural image and medical image domains, encompassing a wide range of applications. Previous investigations in medical images have often been constrained to specific anatomical regions, particular applications, and limited datasets, resulting in isolated diffusion models. This paper introduces a diff

Ming-Ming Long

We present an analytic calculation of three-loop four-point Feynman integrals with two off-shell legs of equal mass. We provide solutions to the canonical differential equations of two integral families in both Euclidean and physical regions. They are validated numerically against independent computations. A total of 170 master integrals are expressed in ter

Taolin Zhang, Jinpeng Wang, Hang Guo, Tao Dai

Adaptation of pretrained vision-language models such as CLIP to various downstream tasks have raised great interest in recent researches. Previous works have proposed a variety of test-time adaptation (TTA) methods to achieve strong generalization without any knowledge of the target domain. However, existing training-required TTA approaches like TPT necessit

Maor Biton Dor, Yisroel Mirsky

This paper introduces a novel data-free model extraction attack that significantly advances the current state-of-the-art in terms of efficiency, accuracy, and effectiveness. Traditional black-box methods rely on using the victim's model as an oracle to label a vast number of samples within high-confidence areas. This approach not only requires an extensive n

Chung Shue Chen, Wing Shing Wong, Yuan-Hsun Lo, Tsai-Lien Wong

We investigate coding schemes that map source symbols into multisets of an alphabet set. Such a formulation of source coding is an alternative approach to the traditional framework and is inspired by an object tracking problem over proximity sensor networks. We define a \textit{multiset combinatorial Gray code} as a mulitset code with fixed multiset cardinal

Laura Koesten, Jude Yew, Kathleen Gregory

Having greater access to data leads to many benefits, from advancing science to promoting accountability in government to boosting innovation. However, merely providing data access does not make data easy to use; even when data is openly available online, people may struggle to work with it. In this article, we draw on prior work, including our own, and a ca

Madhusudan Manjunath

We study the theory of equations in one variable over polyhedral semirings. The article revolves around a notion of solution to a polynomial equation over a polyhedral semiring. Our main results are a characterisation of local solutions in terms of the coefficients, a local-global principle, and the basics of multiplicity and discriminants. Our primary sourc

Mogens Plessen

This paper addresses two tasks: (i) fixed-size objects such as hay bales are to be identified in an aerial image for a given reference image of the object, and (ii) variable-size patches such as areas on fields requiring spot spraying or other handling are to be identified in an image for a given small-scale reference image. Both tasks are related. The secon

Panagiotis Dimakis, Frédéric Rochon

Using an approach developed by Melrose to study the geometry at infinity of the Nakajima metric on the reduced Hilbert scheme of points on $\mathbb{C}^2$, we show that the Nakajima metric on a quiver variety is quasi-asymptotically conical (QAC) whenever its defining parameters satisfy an appropriate genericity assumption. As such, it is of bounded geometry

Abdur Rashid, Parag Biswas, abdullah al masum, MD Abdullah Al Nasim

The integration of machine learning into smart grid systems represents a transformative step in enhancing the efficiency, reliability, and sustainability of modern energy networks. By adding advanced data analytics, these systems can better manage the complexities of renewable energy integration, demand response, and predictive maintenance. Machine learning

Csanád Hajdú, Cătălin Paşcu Moca, Balázs Dóra, Ireneusz Weymann

We investigate the critical behavior of the Kondo compensation in the presence of a power-law pseudogap in the density of states, $\varrho(\omega)\sim |\omega|^\epsilon$. For $\epsilon<1$, this model exhibits a quantum phase transition from a partially screened doublet ground state to a fully screened many-body singlet ground state with increasing Kondo coup

Yijia Ma, Wei Wu

Function registration, also referred to as alignment, has been one of the fundamental problems in the field of functional data analysis. Classical registration methods such as the Fisher-Rao alignment focus on estimating optimal time warping function between functions. In recent studies, a model on time warping has attracted more attention, and it can be use

Gavin Ruan, Ziqi Guo, Guang Lin

Over 44 million Americans currently suffer from food insecurity, of whom 13 million are children. Across the United States, thousands of food banks and pantries serve as vital sources of food and other forms of aid for food insecure families. By optimizing food bank and pantry locations, food would become more accessible to families who desperately require i

Aaryen Mehta, Gagan Aryan

The most common method to auto-grade a student's submission in a CS1 or a CS2 course is to run it against a pre-defined test suite and compare the results against reference results. However, this technique cannot be used if the correctness of the solution goes beyond simple output, such as the algorithm used to obtain the result. There is no convenient metho

Mouli Chakraborty, Anshu Mukherjee, Ioannis Krikidis, Avishek Nag

This paper significantly advances the application of Quantum Key Distribution (QKD) in Free- Space Optics (FSO) satellite-based quantum communication. We propose an innovative satellite quantum channel model and derive the secret quantum key distribution rate achievable through this channel. Unlike existing models that approximate the noise in quantum channe

Sajad Fathi Hafshejani, Daya Gaur, Arundhati Dasgupta, Robert Benkoczi

We develop a hybrid classical-quantum method for solving the Lorenz system. We use the forward Euler method to discretize the system in time, transforming it into a system of equations. This set of equations is solved using the Variational Quantum Linear Solver (VQLS) algorithm. We present numerical results comparing the hybrid method with the classical appr

Yunchuan Zhang, Sangwoo Park, Osvaldo Simeone

Radio resource allocation often calls for the optimization of black-box objective functions whose evaluation is expensive in real-world deployments. Conventional optimization methods apply separately to each new system configuration, causing the number of evaluations to be impractical under constraints on computational resources or timeliness. Toward a remed

Yun-Hua Chen, Zi-Wei Li

The chromopolarizability of a charm-beauty quarkonium characterizes its interaction with soft gluonic fields and can be probed through heavy quarkonium decays. Using the dispersion theory which considers the $\pi\pi$ final state interaction model-independently, we analyze the transition $B_c(2S) \rightarrow B_c\pi^+\pi^-$ and determine the chromopolarizabili

Jianhang Jia, Hao Zhou, Xin Zhang

Teleoperation can transfer human perception and cognition to a slave robot to cope with some complex tasks, in which the agility and flexibility of the interface play an important role in mapping human intention to the robot. In this paper, we developed an agile large-workspace teleoperation interface by estimating human arm behavior. Using the wearable sens

Simon Malberg, Roman Poletukhin, Carolin M. Schuster, Georg Groh

We present a large-scale evaluation of 30 cognitive biases in 20 state-of-the-art large language models (LLMs) under various decision-making scenarios. Our contributions include a novel general-purpose test framework for reliable and large-scale generation of tests for LLMs, a benchmark dataset with 30,000 tests for detecting cognitive biases in LLMs, and a

N. S. Manton

We recalculate the force exerted by an antikink on a kink when their overlapping tail fields are close to either a quadratic or quartic minimum of the field theory potential. Our uniform method of calculation exploits the modified Bogomolny equation satisfied by an accelerating kink. This method has been used before in special cases, but is shown here to hav

Junwei Hu, Michael Bewong, Selasi Kwashie, Wen Zhang

Drug-target interaction (DTI) prediction is crucial for drug development and repositioning. Methods using heterogeneous graph neural networks (HGNNs) for DTI prediction have become a promising approach, with attention-based models often achieving excellent performance. However, these methods typically overlook edge features when dealing with heterogeneous bi

Ziliang Xiong, Mingyu Xiao

The Directed Feedback Vertex Set problem (DFVS) asks whether it is possible to remove at most $k$ vertices from a directed graph to make it acyclic. Whether DFVS is fixed-parameter tractable was a long-standing open problem in parameterized complexity until it was solved by Chen et al. in 2008 (STOC 2008). Now the running-time bound of this problem is improv

Pierfrancesco Di Cintio, Alessandro Alberto Trani

Recent numerical results seem to suggest that in certain regimes of typical particle velocities the gravitational $N-$body problem (for $3\leq N\lesssim 10^3$) is intrinsically less chaotic when the post-Newtonian (PN) force terms are included, with respect to its classical counterpart that exhibits a slightly larger maximal Lyapunov exponent $\Lambda_{\rm m

Bar Avraham, Yisroel Mirsky

Black box attacks, where adversaries have limited knowledge of the target model, pose a significant threat to machine learning systems. Adversarial examples generated with a substitute model often suffer from limited transferability to the target model. While recent work explores ranking perturbations for improved success rates, these methods see only modest

Shashank Kanade, Jeremy Lovejoy

We show how Bailey pairs can be used to give a simple proof of an identity of Chern, Li, Stanton, Xue, and Yee. The same method yields a number of related identities as well as false theta companions.

Daniel O. R. Azevedo, Oswaldo Del Cima, Thadeu D. S. Dias, Daniel H. T. Franco

It is shown how spin one vector matter fields can be coupled to a Yang-Mills theory. Such matter fields are defined as belonging to a representation $R$ of this Yang-Mills gauge algebra $\mathfrak{g}$. It is also required that these fields together with the original gauge fields be the gauge fields of an embedding total gauge algebra $\mathfrak{g}_{\rm tot}$

Menna Helmy, Alaa Awad Abdellatif, Naram Mhaisen, Amr Mohamed

The forthcoming 6G networks will embrace a new realm of AI-driven services that requires innovative network slicing strategies, namely slicing for AI, which involves the creation of customized network slices to meet Quality of service (QoS) requirements of diverse AI services. This poses challenges due to time-varying dynamics of users' behavior and mobile n

V. V. Obukhov

In this paper the final stage of the Petrov classification is carried out. As it is known, the Killing vector fields specify infinitesimal transformations of the group of motions of space $V_4$. In the case when in the homogeneous space $V_4$ the group of motions $G_3$ acts simply transitive, the geometry of the non-isotropic hypersurface is determined by th

Sazid Nazat, Mustafa Abdallah

The rapid advancement of autonomous vehicle (AV) technology has introduced significant challenges in ensuring transportation security and reliability. Traditional AI models for anomaly detection in AVs are often opaque, posing difficulties in understanding and trusting their decision making processes. This paper proposes a novel feature ensemble framework th

Antoine Cavagna, Milo Eder, Enam Chowdhury, André Kalouguine

We report on continuous high-harmonic generation at 1 kHz repetition rate from a liquid-sheet plasma mirror driven by relativistic-intensity near-single-cycle light transients. Through precise control of both the surface plasma density gradient and the driving light waveform, we can produce highly stable and reproducible extreme ultraviolet spectral quasi-co

Yi Ren, HanZhi Zhang, Weibin Li, Jun Fu

We present MMDS, a system capable of recognizing medical images and patient facial details, and providing professional medical diagnoses. The system consists of two core components:The first component is the analysis of medical images and videos. We trained a specialized multimodal medical model capable of interpreting medical images and accurately analyzing

M. J. D. Hamilton, D. Kotschick, P. N. Pilatus

We propose a simple definition of a Born geometry in the framework of K\"unneth geometry. While superficially different, this new definition is equivalent to the known definitions in terms of para-quaternionic or generalized geometries. We discuss integrability of Born structures and their associated connections. In particular we find that for integrable Bor

A. Lowe

Quantum game theory has emerged as a promising candidate to further the understanding of quantum correlations. Motivated by this, it is demonstrated that pure strategy Nash equilibria can be utilised as a mechanism to witness and determine quantum correlation. By combining quantum theory with Bayesian game theory, a constant-sum game is designed in which the

Stefano Profumo, Lucas Brown, Christopher Ewasiuk, Sean Ricarte

Primordial black holes can be the entirety of the dark matter in a broad, approximately five-orders-of-magnitude-wide mass range, the ``asteroid mass range'', between $10^{-16}\ M_{\rm Sun}$ -- where constraints originate from evaporation -- and $10^{-11}\ M_{\rm Sun}$ -- from microlensing. A direct detection in this mass range is very challenging with any k

Tien-Quang Nguyen, Nghia-Hieu Cong, Ngoc-Minh Quach, Hieu Dinh Vo

REST (Representational State Transfer) APIs have become integral for data communication and exchange due to their simplicity, scalability, and compatibility with web standards. However, ensuring REST APIs' reliability through rigorous testing poses significant challenges, given the complexities of operations, parameters, inputs, dependencies, and call sequen

Julien Mellet, Mike Allenspach, Eugenio Cuniato, Claudio Pacchierotti

Most telemanipulation systems for aerial robots provide the operator with only 2D screen visual information. The lack of richer information about the robot's status and environment can limit human awareness and, in turn, task performance. While the pilot's experience can often compensate for this reduced flow of information, providing richer feedback is expe

Yingjun Du, Wenfang Sun, Cees G. M. Snoek

Pre-trained vision-language models like CLIP have remarkably adapted to various downstream tasks. Nonetheless, their performance heavily depends on the specificity of the input text prompts, which requires skillful prompt template engineering. Instead, current approaches to prompt optimization learn the prompts through gradient descent, where the prompts are

Daniel Ayzenshteyn, Roy Weiss, Yisroel Mirsky

As large language models (LLMs) continue to evolve, their potential use in automating cyberattacks becomes increasingly likely. With capabilities such as reconnaissance, exploitation, and command execution, LLMs could soon become integral to autonomous cyber agents, capable of launching highly sophisticated attacks. In this paper, we introduce novel defense

Longwen Zhou, Jiangbin Gong, Xue-Jia Yu

Topologically protected edge states exactly at topological phase boundaries challenge the conventional belief that topological states must be associated with a bulk energy gap. Because periodically driven (Floquet) systems host unusually intricate topological phase boundaries, topological edge states can be prolific at such Floquet quantum criticality. Worki

Jue Xiao, Tingting Deng, Shuochen Bi

In recent fast-paced financial markets, investors constantly seek ways to gain an edge and make informed decisions. Although achieving perfect accuracy in stock price predictions remains elusive, artificial intelligence (AI) advancements have significantly enhanced our ability to analyze historical data and identify potential trends. This paper takes AI driv

Zhengqin Liu, Jinlong Lei, Peng Yi

This paper designs a novel trajectory planning approach to resolve the computational efficiency and safety problems in uncoordinated methods by exploiting vehicle-to-everything (V2X) technology. The trajectory planning for connected and autonomous vehicles (CAVs) is formulated as a game with coupled safety constraints. We then define interaction-fair traject

Haitao Li, Junjie Chen, Qingyao Ai, Zhumin Chu

The use of large language models (LLMs) as automated evaluation tools to assess the quality of generated natural language, known as LLMs-as-Judges, has demonstrated promising capabilities and is rapidly gaining widespread attention. However, when applied to pairwise comparisons of candidate responses, LLM-based evaluators often exhibit selection bias. Specif

Bohao Liao, Wei Zhai, Zengyu Wan, Zhixin Cheng

Scene reconstruction from casually captured videos has wide applications in real-world scenarios. With recent advancements in differentiable rendering techniques, several methods have attempted to simultaneously optimize scene representations (NeRF or 3DGS) and camera poses. Despite recent progress, existing methods relying on traditional camera input tend t

Junwei Zhou, Xueting Li, Lu Qi, Ming-Hsuan Yang

We present Layout-Your-3D, a framework that allows controllable and compositional 3D generation from text prompts. Existing text-to-3D methods often struggle to generate assets with plausible object interactions or require tedious optimization processes. To address these challenges, our approach leverages 2D layouts as a blueprint to facilitate precise and p

Dongdong Hu

We define the preprojective algebra of a finite EI quiver. We prove that it is isomorphic to a centain tensor algebra. For a finite EI quiver of Cartan type, we prove that the corresponding preprojective algebra is isomorphic to the generalized preprojective algebra.

Zhijie Cheng, Yukai Wu, Shijiao Li, Quanxin Mei

Topological defects are discontinuities of a system protected by global properties, with wide applications in mathematics and physics. While previous experimental studies mostly focused on their classical properties, it has been predicted that topological defects can exhibit quantum superposition. Despite the fundamental interest and potential applications i

Carles Roch I Carceller, Armin Tavakoli

We show that bipartite bound entangled states make possible violations of correlation inequalities in the prepare-and-measure scenario. These inequalities are satisfied by all classical models as well as by all quantum models that do not feature entanglement. In contrast to the known Bell inequality violations from bound entangled states, we find that the vi

Hao Chen, Lei Zhu, Xinghui Zhu

Deep hashing, due to its low cost and efficient retrieval advantages, is widely valued in cross-modal retrieval. However, existing cross-modal hashing methods either explore the relationships between data points, which inevitably leads to intra-class dispersion, or explore the relationships between data points and categories while ignoring the preservation o

Tetsuya Sato, Yasuhiko Minamide

Differential privacy is a statistical definition of privacy that has attracted the interest of both academia and industry. Its formulations are easy to understand, but the differential privacy of databases is complicated to determine. One of the reasons for this is that small changes in database programs can break their differential privacy. Therefore, forma

Ronan Docherty, Antonis Vamvakeros, Samuel J. Cooper

The features of self-supervised vision transformers (ViTs) contain strong semantic and positional information relevant to downstream tasks like object localization and segmentation. Recent works combine these features with traditional methods like clustering, graph partitioning or region correlations to achieve impressive baselines without finetuning or trai

Yuang Ai, Huaibo Huang, Ran He

Prompt-based all-in-one image restoration (IR) frameworks have achieved remarkable performance by incorporating degradation-specific information into prompt modules. Nevertheless, handling the complex and diverse degradations encountered in real-world scenarios remains a significant challenge. To tackle this, we propose LoRA-IR, a flexible framework that dyn

Sakaé Fuchino, Takehiko Gappo, Francesco Parente

The present paper is concerned with the relation between recurrence axioms and Laver-generic large cardinal axioms in light of principles of generic absoluteness and the Ground Axiom. M. Viale proved that Martin's Maximum$^{++}$ together with the assumption that there are class many Woodin cardinals implies $\mathcal{H}(\aleph_2)^{\mathsf{V}}\prec_{\Sigma_2}

Pavlina K. Jordanova

In 2017-2020 Jordanova and co-authors investigate probabilities for p-outside values and determine them in many particular cases. They show that these probabilities are closely related to the concept for heavy tails. Tukey's boxplots are very popular and useful in practice. Analogously to the chi-square-criterion, the relative frequencies of the events an ob

Mengzhou Liao, Andrea Silva, Luojun Du, Paolo Nicolini

Van der Waals (vdW) homo-/hetero-structures are ideal systems for studying interfacial tribological properties such as structural superlubricity. Previous studies concentrated on the mechanism of translational motion in vdW interfaces. However, detailed mechanisms and general properties of the rotational motion are barely explored. Here, we combine experimen

The Tien Mai

Count data is prevalent in various fields like ecology, medical research, and genomics. In high-dimensional settings, where the number of features exceeds the sample size, feature selection becomes essential. While frequentist methods like Lasso have advanced in handling high-dimensional count data, Bayesian approaches remain under-explored with no theoretic

Xinyu Liang, Ziheng Wang, Hao Wang

Generating synthetic residential load data that can accurately represent actual electricity consumption patterns is crucial for effective power system planning and operation. The necessity for synthetic data is underscored by the inherent challenges associated with using real-world load data, such as privacy considerations and logistical complexities in larg

Kazuto Ichimaru, Diego Thomas, Takafumi Iwaguchi, Hiroshi Kawasaki

Active 3D measurement, especially structured light (SL) has been widely used in various fields for its robustness against textureless or equivalent surfaces by low light illumination. In addition, reconstruction of large scenes by moving the SL system has become popular, however, there have been few practical techniques to obtain the system's precise pose in

Jingjing Hu, Dengfeng Li, Yufan Qie, Zelong Yin

In quantum computing, precise control of system-environment coupling is essential for high-fidelity gates, measurements, and networking. We present an architecture that employs an artificial giant atom from waveguide quantum electrodynamics to tailor the interaction between a superconducting qubit and its environment. This frequency-tunable giant atom exhibi

Kazuto Ichimaru, Takaki Ikeda, Diego Thomas, Takafumi Iwaguchi

3D-shape reconstruction in extreme environments, such as low illumination or scattering condition, has been an open problem and intensively researched. Active stereo is one of potential solution for such environments for its robustness and high accuracy. However, active stereo systems usually consist of specialized system configurations with complicated algo

Yiming Zhao, Libo Chen, Yong Wang, Hongyang Ma

We introduce a novel strategy employing an adaptive genetic algorithm (GA) for iterative optimization of control sequences to generate quantum nonclassical states. Its efficacy is demonstrated by preparing spin-squeezed states in an open collective spin model governed by a linear control field. Inspired by Darwinian evolution, the algorithm iteratively refin

Seyed Mohammad Ahmadi, Koorosh Aslansefat, Ruben Valcarce-Dineiro, Joshua Barnfather

In today's world, the significance of explainable AI (XAI) is growing in robotics and point cloud applications, as the lack of transparency in decision-making can pose considerable safety risks, particularly in autonomous systems. As these technologies are integrated into real-world environments, ensuring that model decisions are interpretable and trustworth

Seungwon Song, Hyungtae Lim, Alex Junho Lee, Hyun Myung

Despite extensive research in robust visual-inertial navigation systems~(VINS) in dynamic environments, many approaches remain vulnerable to objects that suddenly start moving, which are referred to as \textit{abruptly dynamic objects}. In addition, most approaches have considered the effect of dynamic objects only at the feature association level. In this s

Jiangtao Kong, Jiacheng Shi, Ashley Gao, Shaohan Hu

Incremental learning (IL) aims to acquire new knowledge from current tasks while retaining knowledge learned from previous tasks. Replay-based IL methods store a set of exemplars from previous tasks in a buffer and replay them when learning new tasks. However, there is usually a size-limited buffer that cannot store adequate real exemplars to retain the know

Yuji Wang, Zehua Chen, Xiaoyu Chen, Yixiang Wei

Diffusion models have achieved remarkable progress on image-to-video (I2V) generation, while their noise-to-data generation process is inherently mismatched with this task, which may lead to suboptimal synthesis quality. In this work, we present FrameBridge. By modeling the frame-to-frames generation process with a bridge model based data-to-data generative

Dennis Eriksson, Lars Halvard Halle, Johannes Nicaise

We perform a systematic study of the base change conductor for Jacobians. Through the lens of intersection theory and Deligne's Riemann-Roch theorem, we present novel computational approaches for both the tame and wild parts of the base change conductor. Our key results include a general formula of the tame part, as well as a computation of the wild part in

Anthonette Adanyin

The adoption of artificial intelligence (AI) in retail has significantly transformed the industry, enabling more personalized services and efficient operations. However, the rapid implementation of AI technologies raises ethical concerns, particularly regarding consumer privacy and fairness. This study aims to analyze the ethical challenges of AI application

Wojciech Anyszka, Kaja Gruntkowska, Alexander Tyurin, Peter Richtárik

We revisit FedExProx - a recently proposed distributed optimization method designed to enhance convergence properties of parallel proximal algorithms via extrapolation. In the process, we uncover a surprising flaw: its known theoretical guarantees on quadratic optimization tasks are no better than those offered by the vanilla Gradient Descent (GD) method. Mo

Ali Saadat, Jacques Fellay

Identification of causal genes and pathways is a critical step for understanding the genetic underpinnings of rare diseases. We propose novel approaches to gene prioritization and pathway identification using DNA language model, graph neural networks, and genetic algorithm. Using HyenaDNA, a long-range genomic foundation model, we generated dynamic gene embe

Francesco Scardino

Recently, the short-distance asymptotics of the generating functional of $n$-point correlators of twist-$2$ operators in SU($N$) Yang-Mills (YM) theory has been worked out in [1]. The above computation relies on a basis change of renormalized twist-$2$ operators, where $-\gamma(g)/ \beta(g)$ reduces to $\gamma_0/ (\beta_0\,g)$ to all orders of perturbation t

Nikitas Theodoropoulos, Giorgos Filandrianos, Vassilis Lyberatos, Maria Lymperaiou

We describe our contribution to the Strict and Strict-Small tracks of the 2nd iteration of the BabyLM Challenge. The shared task is centered around efficient pre-training given data constraints motivated by human development. In response, we study the effect of synthetic story data in language pre-training using TinyStories: a recently introduced dataset of

Guikun Chen, Jin Li, Wenguan Wang

Current approaches for open-vocabulary scene graph generation (OVSGG) use vision-language models such as CLIP and follow a standard zero-shot pipeline -- computing similarity between the query image and the text embeddings for each category (i.e., text classifiers). In this work, we argue that the text classifiers adopted by existing OVSGG methods, i.e., cat

Amílcar Branquinho, Juan EF Díaz, Ana Foulquié-Moreno, Hélder Lima

This paper demonstrates how to explicitly construct a bidiagonal factorization of the banded recurrence matrix that appears in mixed multiple orthogonality on the step-line in terms of the coeffcients of the mixed multiple orthogonal polynomials. The construction is based on the \(LU\) factorization of the moment matrix and Christoffel transformations applie

Han Zhou, Jordy Van Landeghem, Teodora Popordanoska, Matthew B. Blaschko

The selective classifier (SC) has been proposed for rank based uncertainty thresholding, which could have applications in safety critical areas such as medical diagnostics, autonomous driving, and the justice system. The Area Under the Risk-Coverage Curve (AURC) has emerged as the foremost evaluation metric for assessing the performance of SC systems. In thi

Daniya Najiha Abdul Kareem, Mustansar Fiaz, Noa Novershtern, Jacob Hanna

Volumetric medical image segmentation is a fundamental problem in medical image analysis where the objective is to accurately classify a given 3D volumetric medical image with voxel-level precision. In this work, we propose a novel hierarchical encoder-decoder-based framework that strives to explicitly capture the local and global dependencies for volumetric

Sergey G. Fedosin

The scalar and vector potentials of the acceleration field and the pressure field are calculated for the first time for a rotating relativistic uniform system, and the dependence of the potentials on the angular velocity is found. These potentials are compared with the potentials for the non-rotating uniform system that have been found previously. The rotati

Wei Lan, Wenyi Chen, Qingfeng Chen, Shirui Pan

The Large Visual Language Models (LVLMs) enhances user interaction and enriches user experience by integrating visual modality on the basis of the Large Language Models (LLMs). It has demonstrated their powerful information processing and generation capabilities. However, the existence of hallucinations has limited the potential and practical effectiveness o

Jiageng Wu, Bo Jiang, Xinxin Li, Ya-Feng Liu

In this paper, we consider a class of convex programming problems with linear equality constraints, which finds broad applications in machine learning and signal processing. We propose a new adaptive balanced augmented Lagrangian (ABAL) method for solving these problems. The proposed ABAL method adaptively selects the stepsize parameter and enjoys a low per-

Yuki Kanto, Kohei Watabe

In recent years, various services have been provided through high-speed and high-capacity wireless networks on mobile communication devices, necessitating stable communication regardless of indoor or outdoor environments. To achieve stable communication, it is essential to implement proactive measures, such as switching to an alternative path and ensuring da

Usman Ali, Iffat Fida Hussain

We define an independence system associated with simple graphs. We prove that the independence system is a matroid for certain families of graphs, including trees, with bases as minimal resolving sets. Consequently, the greedy algorithm on the matroid can be used to find the minimum-cost resolving set of weighted graphs, wherein the independent system is a m

Zhenyu Lin, Hongzheng Li, Yingxia Shao, Guanhua Ye

Graph Contrastive Learning frameworks have demonstrated success in generating high-quality node representations. The existing research on efficient data augmentation methods and ideal pretext tasks for graph contrastive learning remains limited, resulting in suboptimal node representation in the unsupervised setting. In this paper, we introduce LAC, a graph

Armengol Gasull, Luiz F. S. Gouveia, Paulo Santana

This paper studies the number of centers and limit cycles of the family of planar quartic polynomial vector fields that has the invariant algebraic curve $(4x^2-1)(4y^2-1)=0.$ The main interest for this type of vector fields comes from their appearance in some mathematical models in Game Theory composed by two players. In particular, we find examples with fi

Zhen Cao, F. Aharonian, Axikegu, Y. X. Bai

The nearby radio galaxy M87 is a very-high-energy (VHE) gamma-ray emitter established by observations with ground-based gamma-ray detectors. Here we report the long-term monitoring of M87 from 2021 to 2024 with Large High Altitude Air Shower Observatory (LHAASO). M87 has been detected by LHAASO with a statistical significance $\sim 9\sigma$. The observed ene

Yara Shamshoum, Nitzan Hodos, Yuval Sieradzki, Assaf Schuster

We introduce CompAct, a technique that reduces peak memory utilization on GPU by 25-30% for pretraining and 50% for fine-tuning of LLMs. Peak device memory is a major limiting factor in training LLMs, with various recent works aiming to reduce model memory. However most works don't target the largest component of allocated memory during training: the model's

Kestutis Staliunas

There is no simple and universal analytical description of various micro-optical systems related with Fano resonances. This especially concern modulated thin films, which, when coupled to external fields, show Fano resonances. Usually, such micro-optic circuits are simulated numerically, frequently by the use of commercial software. We fill this gap of the l

Qifan Yang, Jing Xu, Xiao Fu, Jingchen Lian

In solid-state batteries (SSBs), improving the physical contact at the electrode-electrolyte interface is essential for achieving better performance and durability. On the one hand, it is necessary to look for solid-state electrolytes (SSEs) with high ionic conductivity and no reaction with the electrode, on the other hand, to design the all-electrochem-acti

Michele Benzi, Michele Rinelli, Igor Simunec

In this paper we propose and analyze an algorithm for identifying spectral gaps of a real symmetric matrix $A$ by simultaneously approximating the traces of spectral projectors associated with multiple different spectral slices. Our method utilizes Hutchinson's stochastic trace estimator together with the Lanczos algorithm to approximate quadratic forms invo

Primoz Moravec

The paper explores the effect of powerful class of Sylow $p$-subgroups of a given finite group on control of transfer or fusion. We also find an explicit bound for the $p$-length of a $p$-solvable group in terms of the poweful class of a Sylow $p$-subgroup.

Vladimir Medvedev

Static manifolds with boundary were recently introduced to mathematics. This kind of manifold appears naturally in the prescribed scalar curvature problem on manifolds with boundary when the mean curvature of the boundary is also prescribed. They are also interesting from the point of view of general relativity. For example, the (time-slice of the) photon sp

Marco Ripà

In the decimal numeral system, we prove that the well-known Graham's number, $G := \! ^{n}3$ (i.e., $3^{3^{\cdot^{\cdot^{\cdot^{3}}}}}$ ($n$ times)), and any base $3$ tetration whose hyperexponent is larger than $n$ share the same $\operatorname{slog}_3(G) - 1$ rightmost digits (where $\operatorname{slog}$ indicates the integer super-logarithm). This is an e

Hao-Tang Tsui, Chien-Yao Wang, Hong-Yuan Mark Liao

Identifying and localizing objects within images is a fundamental challenge, and numerous efforts have been made to enhance model accuracy by experimenting with diverse architectures and refining training strategies. Nevertheless, a prevalent limitation in existing models is overemphasizing the current input while ignoring the information from the entire dat

Muhdin Abdo Wodedo, Tesfay Gebremariam Tesfahannes, Tewodros Yirgashewa Darge, Berihu Teklu

We propose a scheme of an optomechanical system that optimizes entanglement in nanomechanical resonators through quantum state transfer of intracavity squeezing and squeezed reservoir field sources assisted by radiation pressure. The system is driven by red-detuned laser fields, which enable simultaneous cooling of the mechanical resonators and facilitate th

Keshav Krishna, Ayush Verma

The increasing use of Non-Volatile Memory (NVM) in computer architecture has brought about new challenges, one of which is the write endurance problem. Frequent writes to a particular cache cell in NVM can lead to degradation of the memory cell and reduce its lifespan. To solve this problem, we propose a sample-based blocking technique for the Last Level Cac