April 2024 arXiv papers — page 60

Antonio Marino, Claudio Pacchierotti, Paolo Robuffo Giordano

In this paper, we propose the Liquid-Graph Time-constant (LGTC) network, a continuous graph neural network(GNN) model for control of multi-agent systems based on therecent Liquid Time Constant (LTC) network. We analyse itsstability leveraging contraction analysis and propose a closed-form model that preserves the model contraction rate and doesnot require so

Eleonora Di Valentino, Leandros Perivolaropoulos, Jackson Levi Said

The Special Issue on "Modified Gravity Approaches to the Tensions of $\Lambda$CDM"} in the Universe journal tackles significant challenges faced by the $\Lambda$CDM model, including discrepancies in the Hubble constant, growth rate of structures, and cosmological anisotropies. These issues suggest foundational cracks in the model, raising questions about the

Guillaume Rialland

We consider perturbations of the one-dimensional cubic Schr\"odinger equation, of the form $i \, \partial_t \psi + \partial_x^2 \psi + |\psi|^2 \psi + g( |\psi|^2 ) \psi = 0$. Under hypotheses on the function $g$ that can be easily verified in some cases (such as $g(s) = s^\sigma$ with $\sigma >1$), we show that the linearized problem around a small solitary

Naila Azam, Anna Lito Michala, Shuja Ansari, Nguyen Truong

Data-driven applications and services have been increasingly deployed in all aspects of life including healthcare and medical services in which a huge amount of personal data is collected, aggregated, and processed in a centralised server from various sources. As a consequence, preserving the data privacy and security of these applications is of paramount im

Mokhtar Ben Henda

The semantics of content is one of the essential constituents of models of innovative educational systems. It is gradually built based on normative efforts carried out by different actors in the fields of the technological industry, telecommunications, IT, linguistic engineering, information sciences documentation, etc. Semantics in networks and digital info

Mokhtar Ben Henda, Henri Hudrisier

Terminology and lexicography standardization is a fundamental issue that is becoming increasingly important in the era of multilingual globalization and particularly, from our standpoint, the era of terminotics and translation. The challenges of multilingual globalization and e-semantics directly impact standardization methods: Development and perspectives o

C. W. J. Beenakker

We extend the scattering theory of the Josephson effect to include a coupling of the Josephson junction to a gapless electron reservoir in the normal state. By opening up the system with a quasiparticle escape rate $1/\tau$, the supercurrent carried at zero temperature by an Andreev level at energy $\varepsilon_{\rm A}$ is reduced by a factor $(2/\pi)\arctan

Mokhtar Ben Henda

University renovation is a recurring fact generated by permanent technological innovations and new methods of organizing universities and training offers. Technological interoperability standards play a determining role, not only by providing added value in terms of saving space and time, but also by changing educational models and knowledge acquisition proc

Mokhtar Ben Henda

In the era of globalization and digital networks, the so-called ''minored'' or ''endangered'' languages are facing a twofold dilemma: either succeed in their digital modernity by accepting a ''painful'' linguistic management or slide towards a slow extinction in front of hegemonic and ''predatory'' languages which dominate the digital networks.Oral languages

Charles Bertucci, Matthias Rakotomalala

We exploit the structure of geometric graphs on Riemannian manifolds to analyze strategic dynamic graphs at the limit, when the number of nodes tends to infinity. This framework allows to preserve intrinsic geometrical information about the limiting graph structure, such as the Ollivier curvature. After introducing the setting, we derive a mean field game sy

Xuelei Lin, Jiamei Dong, Sean Hon

{In [X. L. Lin, M. K. Ng, and Y. Zhi. {\it J. Comput. Phys.}, 434 (2021), pp. 110221] and [Y. L. Zhao, J. Wu, X. M. Gu, and H. Li. {\it Comput. Math. Appl.}, 148(2023), pp. 200--210]}, two-sided preconditioning techniques are proposed for non-local evolutionary equations, which possesses (i) mesh-size independent theoretical bound of condition number of the

Akira Taniguchi, Ayako Fukawa, Hiroshi Yamakawa

Spatial cognition in hippocampal formation is posited to play a crucial role in the development of self-localization techniques for robots. In this paper, we propose a self-localization approach, DEQ-MCL, based on the discrete event queue hypothesis associated with phase precession within the hippocampal formation. Our method effectively estimates the poster

Mingyuan Lin, Jian Liu, Chi Zhang, Zibo Zhao

By leveraging the blur-noise trade-off, imaging with non-uniform exposures largely extends the image acquisition flexibility in harsh environments. However, the limitation of conventional cameras in perceiving intra-frame dynamic information prevents existing methods from being implemented in the real-world frame acquisition for real-time adaptive camera shu

Kyomin Hwang, Suyoung Kim, JunHoo Lee, Nojun Kwak

Large Models (LMs) have heightened expectations for the potential of general AI as they are akin to human intelligence. This paper shows that recent large models such as Stable Diffusion and DALL-E3 also share the vulnerability of human intelligence, namely the "white bear phenomenon". We investigate the causes of the white bear phenomenon by analyzing their

Xiaotian Xu, Kuan-Cheng Chen, Robert Wille

In this paper, we introduce HamilToniQ, an open-source, and application-oriented benchmarking toolkit for the comprehensive evaluation of Quantum Processing Units (QPUs). Designed to navigate the complexities of quantum computations, HamilToniQ incorporates a methodological framework assessing QPU types, topologies, and multi-QPU systems. The toolkit facilit

Javier De Miguel, Abaz Kryemadhi, Konstantin Zioutas

Dark matter substructures emerge naturally in a scenario in which the axion angular field acquires propagating degrees of freedom in a post-inflationary Universe. The DALI experiment is a new generation wavy dark matters interferometer currently in prototyping. Although DALI's main objective is to explore the virialized DM in our Galaxy, to a large degree in

M. M. Piva, R. Wawrzyńczak, Nitesh Kumar, L. O. Kutelak

At ambient pressure, HfTe$_{5}$ is a material at the boundary between a weak and a strong topological phase, which can be tuned by changes in its crystalline structure or by the application of high magnetic fields. It exhibits a Lifshitz transition upon cooling, and three-dimensional (3D) quantum Hall effect (QHE) plateaus can be observed at low temperatures

Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang

The advent of large language models (LLMs) has revolutionized the field of natural language processing, yet they might be attacked to produce harmful content. Despite efforts to ethically align LLMs, these are often fragile and can be circumvented by jailbreaking attacks through optimized or manual adversarial prompts. To address this, we introduce the Infor

Paolo Colusso, Damir Filipović

We propose a function-learning methodology with a control-theoretical foundation. We parametrise the approximating function as the solution to a control system on a reproducing-kernel Hilbert space, and propose several methods to find the set of controls which bring the initial function as close as possible to the target function. At first, we derive the exp

Shimpei Kobayashi

We investigate a connection between the complex landslide flow, defined on a pair of Teichm\"uller spaces, and the integrable system approach to harmonic maps into a symmetric space. We will prove that the holonomy of the complex landslide flow can be derived from the holonomy of the family of flat connections determined by a harmonic map into the hyperbolic

Amílcar Branquinho, Ana Foulquié-Moreno, Manuel Mañas

This paper serves as an introduction to banded totally positive matrices, exploring various characterizations and associated properties. A significant result within is the demonstration that the collection of such matrices forms a semigroup, notably including a subset permitting positive bidiagonal factorization. Moreover, the paper applies this concept to i

Jiachen T. Wang, Zhun Deng, Hiroaki Chiba-Okabe, Boaz Barak

Generative artificial intelligence (AI) systems are trained on large data corpora to generate new pieces of text, images, videos, and other media. There is growing concern that such systems may infringe on the copyright interests of training data contributors. To address the copyright challenges of generative AI, we propose a framework that compensates copyr

Dario Benedetti, Razvan Gurau, Davide Lettera

Quantum long-range models at zero temperature can be described by fractional Lifshitz field theories, that is, anisotropic models whose actions are short-range in time and long-range in space. In this paper we study the renormalization of fractional Lifshitz field theories with weakly relevant cubic or quartic self-interactions. Their nontrivial infrared fix

Xiaoyan Luan, Zhun Lu

We study the chiral-odd generalized parton distributions (GPDs) of the $\bar{u}$ and $\bar{d}$ quarks inside the proton at zero skewness using the overlap representation within the light cone formalism. Using the light cone wave functions (LCWFs) of the proton obtained from the baryon-meson fluctuation model in terms of the $|q\bar{q}B\rangle$ Fock states, w

Haixia Chen, Seunghyeok Kim

Given a smooth closed Riemannian manifold $(M,g)$ of dimension $N \ge 3$, we derive sharp quantitative stability estimates for nonnegative functions near the solution set of the Yamabe problem on $(M,g)$. The seminal work of Struwe (1984) \cite{S} states that if $\Gamma(u) := \|\Delta_g u - \frac{N-2}{4(N-1)} R_g u + u^{\frac{N+2}{N-2}}\|_{H^{-1}(M)} \to 0$,

Andrew Ying

Double robustness (DR) is a widely-used property of estimators that provides protection against model misspecification and slow convergence of nuisance functions. Despite its widespread application, the theoretical foundation of DR remains underexplored. While DR is a property of global invariance along both nuisance directions, it is often implied by influe

Tongyu Zhang, Moe Vali

Ever since its discovery by Roy Kerr in 1963, the geometry around rotating, electrostatically-neutral black holes, otherwise known as Kerr black holes, has significantly contributed to theoretical developments in the fields of general relativity, thermodynamics and beyond. Extremal Kerr black holes, in which the spin parameter of the rotating black hole is a

Eduárd Zsurka, Cheng Wang, Julian Legendre, Daniele Di Miceli

We develop an accurate nanoelectronic modeling approach for realistic three-dimensional topological insulator nanostructures and investigate their low-energy surface-state spectrum. Starting from the commonly considered four-band $\boldsymbol{\mathrm{k\cdot p}}$ bulk model Hamiltonian for the Bi$_2$Se$_3$ family of topological insulators, we derive new param

Amílcar Branquinho, Juan EF Díaz, Ana Foulquié-Moreno, Manuel Mañas

This paper delves into classical multiple orthogonal polynomials with an arbitrary number of weights, including Jacobi-Pi\~neiro, Laguerre of both first and second kinds, as well as multiple orthogonal Hermite polynomials. Novel explicit expressions for nearest-neighbor recurrence coefficients, as well as the step line case, are provided for all these polyno

Man Tik Ng, Hui Tung Tse, Jen-tse Huang, Jingjing Li

The role-play ability of Large Language Models (LLMs) has emerged as a popular research direction. However, existing studies focus on imitating well-known public figures or fictional characters, overlooking the potential for simulating ordinary individuals. Such an oversight limits the potential for advancements in digital human clones and non-player charact

Antonio Arroyo-Polonio, Carolina Kehrig, Jorge Iglesias Paramo, José Manuel Vílchez

This study delves into the intricate kinematic behavior of ionized gas within IZw18, a galaxy known for its remarkably low metallicity and proximity. Leveraging data from MEGARA/GTC, we meticulously analyzed the galaxy's structure and dynamics using H{\alpha} line profiles. Employing single and double Gaussian component fittings, we generated detailed maps o

Sheng Liu, Zhiqiang Yao, Xuemeng Cao, Xiaowen Cai

Recent years, people have put forward higher and higher requirements for context-adaptive navigation (CAN). CAN system realizes seamless navigation in complex environments by recognizing the ambient surroundings of vehicles, and it is crucial to develop a fast, reliable, and robust navigational context recognition (NCR) method to enable CAN systems to operat

Patrick Ribu Gorton, Andreas Strand, Karsten Brathen

With the recent advances in machine learning, creating agents that behave realistically in simulated air combat has become a growing field of interest. This survey explores the application of machine learning techniques for modeling air combat behavior, motivated by the potential to enhance simulation-based pilot training. Current simulated entities tend to

Yinzhe Xu, Huajian Huang, Yingshu Chen, Sai-Kit Yeung

Visual object tracking and segmentation in omnidirectional videos are challenging due to the wide field-of-view and large spherical distortion brought by 360{\deg} images. To alleviate these problems, we introduce a novel representation, extended bounding field-of-view (eBFoV), for target localization and use it as the foundation of a general 360 tracking fr

Étienne Fouvry, Peter Koymans

Let $F, G \in \mathbb{Z}[X, Y]$ be binary forms of degree $\geq 3$, non-zero discriminant and with automorphism group isomorphic to $D_4$. If $F(\mathbb{Z}^2) = G(\mathbb{Z}^2)$, we show that $F$ and $G$ are ${\rm GL}(2, \mathbb{Z})$--equivalent.

Ruijie Meng, Gregory J. Duck, Abhik Roychoudhury

Computer programs are not executed in isolation, but rather interact with the execution environment which drives the program behaviors. Software validation methods thus need to capture the effect of possibly complex environmental interactions. Program environments may come from files, databases, configurations, network sockets, human-user interactions, and m

Thibault Formal, Stéphane Clinchant, Hervé Déjean, Carlos Lassance

The late interaction paradigm introduced with ColBERT stands out in the neural Information Retrieval space, offering a compelling effectiveness-efficiency trade-off across many benchmarks. Efficient late interaction retrieval is based on an optimized multi-step strategy, where an approximate search first identifies a set of candidate documents to re-rank exa

Jaeho Shin, Seungsang Yun, Ayoung Kim

RGB-D cameras are crucial in robotic perception, given their ability to produce images augmented with depth data. However, their limited FOV often requires multiple cameras to cover a broader area. In multi-camera RGB-D setups, the goal is typically to reduce camera overlap, optimizing spatial coverage with as few cameras as possible. The extrinsic calibrati

Sukmin Cho, Soyeong Jeong, Jeongyeon Seo, Taeho Hwang

The robustness of recent Large Language Models (LLMs) has become increasingly crucial as their applicability expands across various domains and real-world applications. Retrieval-Augmented Generation (RAG) is a promising solution for addressing the limitations of LLMs, yet existing studies on the robustness of RAG often overlook the interconnected relationsh

A. Miroshnikov, O. Nikitenko, A. Skopenkov

In this expository paper we present some ideas of algebraic topology (more precisely, of homology theory) in a language accessible to non-specialists in the area. A $1$-cycle in a graph is a set $C$ of edges such that every vertex is contained in an even number of edges from $C$. It is easy to check that the sum (modulo $2$) of $1$-cycles is a $1$-cycle. We

Dongze Hao, Qunbo Wang, Longteng Guo, Jie Jiang

While large visual-language models (LVLM) have shown promising results on traditional visual question answering benchmarks, it is still challenging for them to answer complex VQA problems which requires diverse world knowledge. Motivated by the research of retrieval-augmented generation in the field of natural language processing, we use Dense Passage Retrie

Rong Wang, Guichen Zhou, Mingjun Gao, Yunpeng Xiao

In recent years, the neural network backdoor hidden in the parameters of the federated learning model has been proved to have great security risks. Considering the characteristics of trigger generation, data poisoning and model training in backdoor attack, this paper designs a backdoor attack method based on federated learning. Firstly, aiming at the conceal

Liwen Wang, Yuanyuan Yuan, Ao Sun, Zongjie Li

Visual deep learning (VDL) systems have shown significant success in real-world applications like image recognition, object detection, and autonomous driving. To evaluate the reliability of VDL, a mainstream approach is software testing, which requires diverse mutations over image semantics. The rapid development of multi-modal large language models (MLLMs)

Jia Wei Sii, Chee Seng Chan

Contemporary makeup transfer methods primarily focus on replicating makeup from one face to another, considerably limiting their use in creating diverse and creative character makeup essential for visual storytelling. Such methods typically fail to address the need for uniqueness and contextual relevance, specifically aligning with character and story settin

Vladimir Petrov Kostov

We study real univariate polynomials with non-zero coefficients and with all roots real, out of which exactly two positive. The sequence of coefficients of such a polynomial begins with $m$ positive coefficients followed by $n$ negative followed by $q$ positive coefficients. We consider the sequence of moduli of their roots on the positive real half-axis; al

Geoffrey R. Grimmett

This biographical and scientific memoir of Dominic Welsh includes summaries of his important contributions to probability and combinatorics. With John Hammersley, he introduced first-passage percolation, and in so doing they formulated and proved the first subadditive ergodic theorem. Welsh has numerous results in matroid theory, and wrote the first monograp

Mingxuan Gao, Min Wang, Maoyin Chen

Deep learning has shown the great power in the field of fault detection. However, for incipient faults with tiny amplitude, the detection performance of the current deep learning networks (DLNs) is not satisfactory. Even if prior information about the faults is utilized, DLNs can't successfully detect faults 3, 9 and 15 in Tennessee Eastman process (TEP). Th

Jiayin Wang, Fengran Mo, Weizhi Ma, Peijie Sun

Large language models (LLMs) are essential tools that users employ across various scenarios, so evaluating their performance and guiding users in selecting the suitable service is important. Although many benchmarks exist, they mainly focus on specific predefined model abilities, such as world knowledge, reasoning, etc. Based on these ability scores, it is h

Matthias Becher, Ludwig A. Hothorn, Frank Konietschke

A common goal in clinical trials is to conduct tests on estimated treatment effects adjusted for covariates such as age or sex. Analysis of Covariance (ANCOVA) is often used in these scenarios to test the global null hypothesis of no treatment effect using an $F$-test. However, in several samples, the $F$-test does not provide any information about individua

Ted Dobson, Joy Morris, Pablo Spiga

Let $k$ be odd, and $n$ an odd multiple of $3$. We prove that $C_k \rtimes C_8$ and $(C_n \times C_3)\rtimes C_8$ do not have the Directed Cayley Isomorphism (DCI) property. When $k$ is also prime, $C_k \rtimes C_8$ had previously been proved to have the Cayley Isomorphism (CI) property. To the best of our knowledge, the groups $C_p \rtimes C_8$ (where $p$ i

Victor G. Lopez, Matthias A. Müller

This paper presents novel solutions of the data-based synchronization problem for continuous-time multiagent systems. We consider the cases of homogeneous and heterogeneous systems. First, we obtain a data-based representation of the synchronization error dynamics for homogeneous systems and show how to extend existing data-based stabilization results to sta

Pei Fu, Gunilla Kreiss, Sara Zahedi

In this paper we present a family of high order cut finite element methods with bound preserving properties for hyperbolic conservation laws in one space dimension. The methods are based on the discontinuous Galerkin framework and use a regular background mesh, where interior boundaries are allowed to cut through the mesh arbitrarily. Our methods include gho

Aayushi Verma, Saurabh Sharma, Lokesh Dewangan

We have carried out a quantitative analysis of the $1^{\circ} \times 1^{\circ}$ region near star-forming site AFGL 5157 using 'Minimal Spanning Tree' (MST). The analysis reveals that this region consists of five major clusters. The cluster radii of the cores and active regions were found to be varying between 0.75-2.62 pc and 2.77-4.58 pc, respectively, for

Peter Emil Carstensen, Jacob Bendsen, Laura Hjort Blicher, Kim Kristensen

Cardiovascular diseases are the leading cause of death. Increased levels of plasma cholesterol are consistently associated with an increased risk of cardiovascular disease. As a result, it is imperative that studies are conducted to determine the best course of action to reduce whole-body cholesterol levels. A whole-body mathematical model for cholesterol me

Yifan Jiang, Filip Ilievski, Kaixin Ma

While vertical thinking relies on logical and commonsense reasoning, lateral thinking requires systems to defy commonsense associations and overwrite them through unconventional thinking. Lateral thinking has been shown to be challenging for current models but has received little attention. A recent benchmark, BRAINTEASER, aims to evaluate current models' la

Ajit Krishnan, Himanshu Vishwakarma, Maharudra Kharsade, Pradipta Biswas

On-orbit manual attitude control of manned spacecraft is accomplished using external visual references and some method of three axis attitude control. All past, present, and developmental spacecraft feature the capability to manually control attitude for deorbit. National Aeronautics and Space Administration (NASA) spacecraft permit an aircraft windshield ty

Xiaozhi Hu

Change in the interatomic spacing of a two-atom system under tension and compression has been modelled by the elastic deformation of atoms. The critical elastic strain of atoms before separation or cracking from tension was estimated by the Griffith theory together with a recent mechanics model, then extended to the lateral elastic expansion under uniaxial c

Zuo Lin

We prove an effective density theorem with polynomial error rate for orbits of upper triangular subgroup of $\mathrm{SL}_2(\mathbb{Q}_p)$ in $\mathrm{SL}_2(\mathbb{Q}_p) \times \mathrm{SL}_2(\mathbb{Q}_p)$ for prime number $p > 3$. The proof is based on the use of Margulis function, a restricted projection theorem on $\mathbb{Q}_p^3$, and spectral gap of the

Zixian Li, Yuming Zhong, Yi Wang

Breast cancer is the most common malignant tumor among women and the second cause of cancer-related death. Early diagnosis in clinical practice is crucial for timely treatment and prognosis. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has revealed great usability in the preoperative diagnosis and assessing therapy effects thanks to its cap

Huw Price

In previous work with Ken Wharton, it was proposed that Bell correlations are a special sort of selection artefact, explained by a combination of (i) collider bias and (ii) a boundary constraint on the collider variable. This requires no direct causal influence outside lightcones, and may hence offer a new way to reconcile Bell nonlocality and relativity. Th

Benoît Claudon, Andreas Höring

In this short note we prove two projectivity criteria for fibrations between mildly singular compact K\"ahler spaces. They are the relative versions of the celebrated criteria of Kodaira and Moishezon. As an application we obtain that the MRC fibration always has a model that is a projective morphism.

Chunyan Cao, Lingyu Zhao, Gang Li

Soil degradation threatens agricultural productivity and food supply, leading to hunger issues in some developing regions. To address this challenge, we developed a low-cost, highly efficient, and long-term stable soil improvement method. We chose polyvinyl alcohol (PVA), a commercially available polymer that is safe and non-degradable, to serve as a soil ad

Boning Zhang, Chengxi Li, Kai Fan

Large language models (LLMs) have been explored in a variety of reasoning tasks including solving of mathematical problems. Each math dataset typically includes its own specially designed evaluation script, which, while suitable for its intended use, lacks generalizability across different datasets. Consequently, updates and adaptations to these evaluation t

Saif Mahmud, Vineet Parikh, Qikang Liang, Ke Li

We present ActSonic, an intelligent, low-power active acoustic sensing system integrated into eyeglasses that can recognize 27 different everyday activities (e.g., eating, drinking, toothbrushing) from inaudible acoustic waves around the body. It requires only a pair of miniature speakers and microphones mounted on each hinge of the eyeglasses to emit ultras

Zeyu Li, Ruitong Gan, Chuanchen Luo, Yuxi Wang

Driven by powerful image diffusion models, recent research has achieved the automatic creation of 3D objects from textual or visual guidance. By performing score distillation sampling (SDS) iteratively across different views, these methods succeed in lifting 2D generative prior to the 3D space. However, such a 2D generative image prior bakes the effect of il

Siyu Chen, Wenchao Yan, Mingyang Zhu, Yaojun Li

A dual-beam platform for all-optical electron-photon scattering, or Thomson/Compton scattering, with adjustable collision-angle and parameter tuning ability has been developed, which, in principle, can be used for the verification of strong-field quantum electrodynamics effects. Combining this platform with a 200 TW Ti:Sapphire laser system, we demonstrated

Chi Huang, Xinyang Li, Yansong Qu, Changli Wu

In indoor scenes, the diverse distribution of object locations and scales makes the visual 3D perception task a big challenge. Previous works (e.g, NeRF-Det) have demonstrated that implicit representation has the capacity to benefit the visual 3D perception task in indoor scenes with high amount of overlap between input images. However, previous works cannot

Husnain Shahid, Miguel Á. Vázquez, Musbah Shaat, Pol Henarejos

In Non-Terrestrial Networks (NTN), achieving effective radio resource allocation across multi-satellite system, encompassing efficient channel and bandwidth allocation, effective beam management, power control and interference mitigation, poses significant challenges due to the varying satellite links and highly dynamic nature of user traffic. This calls for

Yukyung Lee, Soonwon Ka, Bokyung Son, Pilsung Kang

Large Language Models (LLMs) have impacted the writing process, enhancing productivity by collaborating with humans in content creation platforms. However, generating high-quality, user-aligned text to satisfy real-world content creation needs remains challenging. We propose WritingPath, a framework that uses explicit outlines to guide LLMs in generating goa

Husnain Shahid, Carla Amatetti, Riccardo Campana, Sorya Tong

The efforts on the development, standardization and improvements to communication systems towards 5G Advanced and 6G are on track to provide benefits such as an unprecedented level of connectivity and performance, enabling a diverse range of vertical services. The full integration of non-terrestrial components into 6G plays a pivotal role in realizing this p

Yutaka Ookouchi, Ryota Sato, Sohei Tsukahara

In the decay process of metastable vacua in quantum field theories, the bounce solution, a classical solution in Euclideanized theories, is helpful in calculating the decay rate. Recently, the bounce solution with a conical singularity has attracted wide attention and revealed physical importance. In this paper, we discuss the bubble of nothing solution, whi

Binsheu Shieh, Ryo Masuda, Satoshi Tsutsui, Shun Katakami

M\"ossbauer spectroscopy is a technique employed to investigate the microscopic properties of materials using transitions between energy levels in the nuclei. Conventionally, in synchrotron-radiation-based M\"ossbauer spectroscopy, the measurement window is decided by the researcher heuristically, although this decision has a significant impact on the shape

Zhiyuan Lu, Muhammad Hanif, Takumi Shimizu, Takeshi Hatanaka

This paper presents a novel control strategy for drone networks to improve the quality of 3D structures reconstructed from aerial images by drones. Unlike the existing coverage control strategies for this purpose, our proposed approach simultaneously controls both the camera orientation and drone translational motion, enabling more comprehensive perspectives

Menglu Li, Yasaman Ahmadiadli, Xiao-Ping Zhang

The availability of smart devices leads to an exponential increase in multimedia content. However, advancements in deep learning have also enabled the creation of highly sophisticated Deepfake content, including speech Deepfakes, which pose a serious threat by generating realistic voices and spreading misinformation. To combat this, numerous challenges have

Igor G. Korepanov

In this short note, we construct solutions to quantum tetrahedron equation of the kind "with variables on the edges". Each of these variables takes just two values, called sometimes "colors". We propose two different constructions. The first of them involves, in particular, two $\mathcal R$-operators each depending on one parameter, while these parameters ar

Yonghong Yao, Lateef O. Jolaoso, Yekini Shehu

Many recently proposed gradient projection algorithms with inertial extrapolation step for solving quasi-variational inequalities in Hilbert spaces are proven to be strongly convergent with no linear rate given when the cost operator is strongly monotone and Lipschitz continuous. In this paper, our aim is to design an inertial type gradient projection algori

Tong Pan, Hongjun Wang, Jiyuan Chen, Xuan Song

Global wildfire spreading dynamics and severity are analyzed using the susceptible-infected-recovered (SIR) compartment model. We use the novel FireTracks (FT) Scientific Dataset covering the wildfire time series of 2002-2023.

Xiao Xiang Zhu, Qingyu Li, Yilei Shi, Yuanyuan Wang

Understanding how buildings are distributed globally is crucial to revealing the human footprint on our home planet. This built environment affects local climate, land surface albedo, resource distribution, and many other key factors that influence well-being and human health. Despite this, quantitative and comprehensive data on the distribution and properti

Pierre Lelièvre, Chien-Chung Chen

Attribution methods are primarily designed to study input component contributions to individual model predictions. However, some research applications require a summary of attribution patterns across the entire dataset to facilitate the interpretability of the scrutinized models at a task-level rather than an instance-level. It specifically applies when the

Yared W. Bekele

Physics-Informed Neural Networks (PINNs) have emerged as a highly active research topic across multiple disciplines in science and engineering, including computational geomechanics. PINNs offer a promising approach in different applications where faster, near real-time or real-time numerical prediction is required. Examples of such areas in geomechanics incl

Shiri Chechik, Tianyi Zhang

Given a simple weighted directed graph $G = (V, E, \omega)$ on $n$ vertices as well as two designated terminals $s, t\in V$, our goal is to compute the shortest path from $s$ to $t$ avoiding any pair of presumably failed edges $f_1, f_2\in E$, which is a natural generalization of the classical replacement path problem which considers single edge failures onl

Mudit Chopra, Abhinav Barnawal, Harshil Vagadia, Tamajit Banerjee

Given the task of positioning a ball-like object to a goal region beyond direct reach, humans can often throw, slide, or rebound objects against the wall to attain the goal. However, enabling robots to reason similarly is non-trivial. Existing methods for physical reasoning are data-hungry and struggle with complexity and uncertainty inherent in the real wor

Yu-Xiang Lin, Wei-Yun Ma

The goal of product copywriting is to capture the interest of potential buyers by emphasizing the features of products through text descriptions. As e-commerce platforms offer a wide range of services, it's becoming essential to dynamically adjust the styles of these auto-generated descriptions. Typical approaches to copywriting generation often rely solely

Yubin Kim, Chanwoo Park, Hyewon Jeong, Yik Siu Chan

Foundation models are becoming valuable tools in medicine. Yet despite their promise, the best way to leverage Large Language Models (LLMs) in complex medical tasks remains an open question. We introduce a novel multi-agent framework, named Medical Decision-making Agents (MDAgents) that helps address this gap by automatically assigning a collaboration struct

Shihao Zhang, kenji kawaguchi, Angela Yao

Most works studying representation learning focus only on classification and neglect regression. Yet, the learning objectives and, therefore, the representation topologies of the two tasks are fundamentally different: classification targets class separation, leading to disconnected representations, whereas regression requires ordinality with respect to the t

Chen Xu, Tianhui Song, Weixin Feng, Xubin Li

Diffusion models have significantly advanced the state of the art in image, audio, and video generation tasks. However, their applications in practical scenarios are hindered by slow inference speed. Drawing inspiration from the approximation strategies utilized in consistency models, we propose the Sub-path Linear Approximation Model (SLAM), which accelerat

RD Russell, J He, LJ Black, A Begley

Background Multiple sclerosis (MS) is a complex immune-mediated disease with no currently known cure. There is growing evidence to support the role of diet in reducing some of the symptoms and disease progression in MS, and we previously developed and tested the feasibility of a digital nutrition education program for people with MS. Objective The aim of thi

Mourad Choulli, Hiroshi Takase

We consider the problem of determining the unknown boundary values of a solution of an elliptic equation outside a bounded open set $B$ from the knowledge of the values of this solution on a boundary of an arbitrary Lipschitz bounded domain surrounding $B$. We obtain for this inverse problem Lipschitz stability for an admissible class of unknown boundary fun

Sathya Krishnan Suresh, Shunmugapriya P

In recent times, the research on Large Language Models (LLMs) has grown exponentially, predominantly focusing on models underpinned by the transformer architecture, as established by [1], and further developed through the decoder-only variations by [2]. Contemporary efforts in this field primarily aim to enhance model capabilities by scaling up both the arch

Rebecca D. Russell, Andrea Begley, Alison Daly, Eleanor Dunlop

Objective: Diet quality is important for people with multiple sclerosis (MS), but conflicting online information causes them confusion. People with MS want evidence-based MS-specific information to help them make healthy dietary changes, and we co-designed an asynchronous, online nutrition education program (Eating Well with MS) with the MS community. Our ai

Yihang Wu, Xiao Cao, Kaixin Li, Zitan Chen

In text-to-image generation tasks, the advancements of diffusion models have facilitated the fidelity of generated results. However, these models encounter challenges when processing text prompts containing multiple entities and attributes. The uneven distribution of attention results in the issues of entity leakage and attribute misalignment. Training from

Yinqiu Liu, Hongyang Du, Dusit Niyato, Jiawen Kang

Employing massive Mobile AI-Generated Content (AIGC) Service Providers (MASPs) with powerful models, high-quality AIGC services can become accessible for resource-constrained end users. However, this advancement, referred to as mobile AIGC, also introduces a significant challenge: users should download large AIGC outputs from the MASPs, leading to substantia

Jo-An Occhipinti, William Hynes, Ante Prodan, Harris A. Eyre

Work is fundamental to societal prosperity and mental health, providing financial security, identity, purpose, and social integration. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement. Some argue that many new jobs and industries will emerge to offset the displacement, while others foresee a widespread decoupl

De-Zhang Li, Yu-Jie Cen, Xin Wang, Xiao-Bao Yang

Residual entropy of ice systems has long been a significant and intriguing issue in condensed matter physics and statistical mechanics. The exact solutions for the residual entropy of realistic three-dimensional ice systems remain unknown. In this study, we focus on two typical realistic ice systems, namely the hexagonal ice (ice Ih) and cubic ice (ice Ic).

Yunlong Ran, Yanxu Li, Qi Ye, Yuchi Huo

Neural radiance field (NeRF) has achieved impressive results in high-quality 3D scene reconstruction. However, NeRF heavily relies on precise camera poses. While recent works like BARF have introduced camera pose optimization within NeRF, their applicability is limited to simple trajectory scenes. Existing methods struggle while tackling complex trajectories

Subhojyoti Mukherjee, Anusha Lalitha, Kousha Kalantari, Aniket Deshmukh

Learning of preference models from human feedback has been central to recent advances in artificial intelligence. Motivated by the cost of obtaining high-quality human annotations, we study efficient human preference elicitation for learning preference models. The key idea in our work is to generalize optimal designs, an approach to computing optimal informa

Huhu Zhang, Xing Gao, Tingzeng Wu, Xinyang Feng

Bremner and Elgendy developed a classification of operated polynomial identities for linear operators on associative algebras, encompassing both classical and newly discovered cases. Within the framework of Rota's Program, each of these new operated associative polynomial identities was shown to be Gr\"obner-Shirshov. This naturally led to a question posed b

Leo Sementilli, Daniil M. Lukin, Hope Lee, Joshua Yang

The applications of nanomechanical resonators range from biomolecule mass sensing to hybrid quantum interfaces. Their performance is often limited by internal material damping, which can be greatly reduced by using crystalline materials. Crystalline silicon carbide is appealing due to its exquisite mechanical, electrical and optical properties, but has suffe

Zuheng Kang, Yayun He, Botao Zhao, Xiaoyang Qu

With recent advances in speech synthesis including text-to-speech (TTS) and voice conversion (VC) systems enabling the generation of ultra-realistic audio deepfakes, there is growing concern about their potential misuse. However, most deepfake (DF) detection methods rely solely on the fuzzy knowledge learned by a single model, resulting in performance bottle

Hang Xu, Kai Li, Bingyun Liu, Haobo Fu

Counterfactual regret minimization (CFR) is a family of algorithms for effectively solving imperfect-information games. It decomposes the total regret into counterfactual regrets, utilizing local regret minimization algorithms, such as Regret Matching (RM) or RM+, to minimize them. Recent research establishes a connection between Online Mirror Descent (OMD)