December 2023 arXiv papers — page 4

A. I. Galimov, D. R. Kazanov, A. V. Poshakinskiy, M. V. Rakhlin

A single nanotube synthesized from a transition metal dichalcogenide (TMDC) exhibits strong exciton resonances and, in addition, can support optical whispering gallery modes. This combination is promising for observing exciton-polaritons without an external cavity. However, traditional energy-momentum-resolved detection methods are unsuitable for this tiny o

Babak Ghanbari, David Hartman, Vít Jelínek, Aneta Pokorná

This work deals with undirected graphs that have the same betweenness centrality for each vertex, so-called betweenness uniform graphs (or BUGs). The class of these graphs is not trivial and its classification is still an open problem. Recently, Gago, Coroni\v{c}ov\'a-Hurajov\'a and Madaras conjectured that for every rational $\alpha\ge 3/4$ there exists a B

Bitop Maitra, Emine Bardakci, Oktay Cetinkaya, Ozgur B. Akan

The advancements in nanotechnology, material science, and electrical engineering have shrunk the sizes of electronic devices down to the micro/nanoscale. This brings the opportunity of developing the Internet of Nano Things (IoNT), an extension of the Internet of Things (IoT). With nanodevices, numerous new possibilities emerge in the biomedical, military fi

Matthew B. Day, Trevor Nakamura

We construct a 3-dimensional cell complex that is the 3-skeleton for an Eilenberg--MacLane classifying space for the symmetric group $\mathfrak{S}_n$. Our complex starts with the presentation for $\mathfrak{S}_n$ with $n-1$ adjacent transpositions with squaring, commuting, and braid relations, and adds seven classes of 3-cells that fill in certain 2-spheres

Samriddha Lahiry, Pragya Sur

Over the past decade, characterizing the exact asymptotic risk of regularized estimators in high-dimensional regression has emerged as a popular line of work. This literature considers the proportional asymptotics framework, where the number of features and samples both diverge, at a rate proportional to each other. Substantial work in this area relies on Ga

Shreelekha Revankar, Shijia Liao, Yu Shen, Junbang Liang

The accuracy of 3D Human Pose and Shape reconstruction (HPS) from an image is progressively improving. Yet, no known method is robust across all image distortion. To address issues due to variations of camera poses, we introduce SHARE, a novel fine-tuning method that utilizes adversarial data augmentation to enhance the robustness of existing HPS techniques.

Luis Alcala

This paper studies a discrete-time version of the Lucas-Uzawa endogenous growth model with physical and human capital in the presence of externalities. Existence of an optimal equilibrium is proved using tools from dynamic programming with bounded or unbounded returns. The proofs also rely on properties of isoelastic utility and homogeneous production functi

Vesko Valov

This is a survey of the recent results and unsolved problems about locally compact homogeneous metric spaces. Mostly, homogeneous finite-dimensional $ANR$-spaces are discussed.

Nguyen Manh Linh

We present the notion of non-abelian descent type, which classifies torsors up to twisting by a Galois cocycle. This relies on the previous construction of kernels and non-abelian Galois 2-cohomology due to Springer and Borovoi. The necessity of descent types arises in the context of the descent theory where no torsors are given a priori, for example, when w

R. Chan, M. F. A. da Silva, V. H. Satheeshkumar

Along the lines of the Einstein-Rosen wave equation of General Relativity (GR), we derive a gravitational wave equation with cylindrical symmetry in the Einstein-aether (EA) theory. We show that the gravitational wave in the EA is periodic in time for both the metric functions $\Psi(r,t)$ and $H(r,t)$. However, in GR, $\Psi(r,t)$ is periodic in time, but $H(

Anmol Srivastava

This paper presents a conceptual insight into the Design of the Metaverse to facilitate educational transformation in selected developing nations within the Global South regions, e.g., India. These regions are often afflicted with socio-economic challenges but rich in cultural diversity. By utilizing a socio-technical design approach, this study explores the

Shaima'a Freewan, Mostafa Hayajneh

Let $A_i$ and $B_i$ be positive definite matrices for every $i=1,\cdots,m.$ Let $Z=[Z_{ij}]$ be the block matrix, where $Z_{ij}=B_i^{^\frac{1}{_2}}\left(\displaystyle\sum_{k=1}^mA_k\right)B_j^{^\frac{1}{_2}}$ for every $ i,j=~1,\cdots,m$. It is shown that $$\left|\left|\left|\sum_{i=1}^m\left(A_i^{s}\sharp B_i^{s}\right)^r\right|\right|\right|\leq\left|\left

A. P. Bray, S. S. Chabysheva, J. R. Hiller

We compute a nonperturbative effective potential between two static fermions in light-front Yukawa theory as a Hamiltonian eigenvalue problem. Fermion pair production is suppressed, to make possible an exact analytic solution in the form of a coherent state of bosons that form clouds around the sources. The effective potential is essentially an interference

Henrik J. Munch

Feynman integrals play a central role in the modern scattering amplitudes research program. Advancing our methods for evaluating Feynman integrals will, therefore, strengthen our ability to compare theoretical predictions with data from particle accelerators such as the Large Hadron Collider. Motivated by this, the present manuscript purports to study mathem

Anders Lansner, Naresh B Ravichandran, Pawel Herman

Associative memory or content addressable memory is an important component function in computer science and information processing and is a key concept in cognitive and computational brain science. Many different neural network architectures and learning rules have been proposed to model associative memory of the brain while investigating key functions like

Sebastian-Vasile Echim, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel, Florin Pop

This work focuses on plant leaf disease classification and explores three crucial aspects: adversarial training, model explainability, and model compression. The models' robustness against adversarial attacks is enhanced through adversarial training, ensuring accurate classification even in the presence of threats. Leveraging explainability techniques, we ga

Alexander A. Davydov, Stefano Marcugini, Fernanda Pambianco

In the literature, lines of the projective space $\mathrm{PG}(3,q)$ are partitioned into classes, each of which is a union of line orbits under the stabilizer group of the twisted cubic. The least studied class is named $\mathcal{O}_6$. This class contains lines external to the twisted cubic which are not its chords or axes and do not lie in any of its oscul

Juraj Foldes, Mouhamadou Sy

We construct various statistical ensembles associated to the 3D Euler equations and prove global regularity of these equations for data living on these sets. Similar results are also proven for generalized SQG equations and some shell models. Qualitative properties of the ensembles and the constructed flows are also given.

Maxime Krier, Julia Orlik, Grigory Panasenko, Konrad Steiner

This paper presents an efficient coupling of the 3D Stokes flow interacting with an effective perforated periodic heterogeneous anisotropic 2D plate. The effective model was obtained by the asymptotic analysis in earlier works and here an effective numerical algorithm is given. By $Q_3$ or bi-cubic spacial interpolation the time-dependent problem was reduced

Yinglun Xu, Tarun Suresh, Rohan Gumaste, David Zhu

Preference-based reinforcement learning (PBRL) in the offline setting has succeeded greatly in industrial applications such as chatbots. A two-step learning framework where one applies a reinforcement learning step after a reward modeling step has been widely adopted for the problem. However, such a method faces challenges from the risk of reward hacking and

Natchanon Luangsomboon, Fahimeh Fazel, Jörg Liebeherr, Ashkan Sobhani

Traffic from distributed training of machine learning (ML) models makes up a large and growing fraction of the traffic mix in enterprise data centers. While work on distributed ML abounds, the network traffic generated by distributed ML has received little attention. Using measurements on a testbed network, we investigate the traffic characteristics generate

Souvik Banerjee, Gideon Vos

In this work, we consider the atypical non-equilibrium state found in [1708.06328] which holographically represents a behind-the-horizon excitation in a blackhole spacetime. The special feature of this state is that it looks like an equilibrium state when probed by a class of low-energy operators. First, we retrieve this property using the uniformization map

Nikola Slepickova Kasalkova, Veronika Juricova, Silvie Rimpelova, Dominik Fajstavr

The presented study highlights the efficiency of employing a KrF excimer laser to create diverse types of periodic nanostructures (LIPSS - laser induced periodic surface structures) on polyether ether ketone (PEEK) and polyethylene naphthalate (PEN) substrates. By exposing the polymer films below their ablation threshold to laser fluence ranging from 4 to 16

Adam Malinowski

Assume $G$ is a group and $\mathcal{A}$ is an algebra of subsets of $G$ closed under left translation. We study various ways to understand the Ellis group of the $G$-flow $S(\mathcal{A})$ (the Stone space of $\mathcal{A}$), with particular interest in the model-theoretic setting where $G$ is definable in a first order structure $M$ and $\mathcal{A}$ consists

Julia Ingelmann, Sachin S. Bharadwaj, Philipp Pfeffer, Katepalli R. Sreenivasan

Two quantum algorithms are presented for the numerical solution of a linear one-dimensional advection-diffusion equation with periodic boundary conditions. Their accuracy and performance with increasing qubit number are compared point-by-point with each other. Specifically, we solve the linear partial differential equation with a Quantum Linear Systems Algor

Hiroyasu Akada, Jian Wang, Vladislav Golyanik, Christian Theobalt

While head-mounted devices are becoming more compact, they provide egocentric views with significant self-occlusions of the device user. Hence, existing methods often fail to accurately estimate complex 3D poses from egocentric views. In this work, we propose a new transformer-based framework to improve egocentric stereo 3D human pose estimation, which lever

Sandro Coriasco, Stevan Pilipović, Dora Seleši

We treat some classes of linear and semilinear stochastic partial differential equations of Schr\"odinger type on $\mathbb{R}^d$, involving a non-flat Laplacian, within the framework of white noise analysis, combined with Wiener-It\^o chaos expansions and pseudodifferential operator methods. The initial data and potential term of the Schr\"odinger operator a

Henri Pesonen, Jukka Corander

Approximate Bayesian computation (ABC) methods are standard tools for inferring parameters of complex models when the likelihood function is analytically intractable. A popular approach to improving the poor acceptance rate of the basic rejection sampling ABC algorithm is to use sequential Monte Carlo (ABC SMC) to produce a sequence of proposal distributions

Richard H. Hammack, Paul C. Kainen

It is shown that Euler's theorem for graphs can be generalized for 2-complexes. Two notions that generalize cycle and Eulerian tour are introduced (``circlet'' and ``Eulerian cover''), and we show that for a strongly-connected, pure 2-complex, the following are equivalent: (i) each edge meets a positive even number of 2-cells (faces), (ii) the complex can be

Yuxiang Qiu, Karim Djemili, Denis Elezi, Aaneel Shalman

With the advancement and utility of Artificial Intelligence (AI), personalising education to a global population could be a cornerstone of new educational systems in the future. This work presents the PEEKC dataset and the TrueLearn Python library, which contains a dataset and a series of online learner state models that are essential to facilitate research

Nassif Ghoussoub, Malcolm Bowles

Kantorovich operators are non-linear extensions of Markov operators and are omnipresent in several branches of mathematical analysis. The asymptotic behaviour of their iterates plays an important role even in classical ergodic, potential and probability theories, which are normally concerned with linear Markovian operators, semi-groups, and resolvents. The K

Opadele Kehinde, Ruth Abdul, Bose Afolabi, Parminder Vir

More than 5 million children under five years die from largely preventable or treatable medical conditions every year, with an overwhelmingly large proportion of deaths occurring in underdeveloped countries with low vaccination uptake. One of the United Nations' sustainable development goals (SDG 3) aims to end preventable deaths of newborns and children und

Jiahang Li, Taoyu Chen, Yuanli Wang

This study introduces a novel approach for analyzing and modifying entity relationships in GPT models, diverging from ROME's entity-focused methods. We develop a relation tracing technique to understand the influence of language model computations on relationship judgments. Using the FewRel dataset, we identify key roles of MLP modules and attention mechanis

Xu Yang, Shuangyuan Lu, Sayak Biswas, Mohit Randeria

The Ginzburg-Landau (GL) theory is very successful in describing the pairing symmetry, a fundamental characterization of the broken symmetries in a paired superfluid or superconductor. However, GL theory does not describe fermionic excitations such as Bogoliubov quasiparticles or Andreev bound states that are directly related to topological properties of the

Elnatan Kadar, Guy Gilboa

We propose a new way to explain and to visualize neural network classification through a decomposition-based explainable AI (DXAI). Instead of providing an explanation heatmap, our method yields a decomposition of the image into class-agnostic and class-distinct parts, with respect to the data and chosen classifier. Following a fundamental signal processing

Yu Hu

Heavy-ion collisions provide a unique opportunity to explore nucleon-hyperon (N-Y) interactions through two-particle correlations. The $p-\Lambda$ and $d-\Lambda$ correlations shed light on both N-Y two-body and N-N-Y three-body interactions, which is crucial for understanding neutron star properties. We present the high precision measurement of $p-\Lambda$

John K. Webb, Chung-Chi Lee, Dinko Milakovic, Victor V. Flambaum

We report unbiased AI measurements of the fine structure constant $\alpha$ in two proximate absorption regions in the spectrum of the quasar HE0515$-$4414. The data are high resolution, high signal to noise, and laser frequency comb calibrated, obtained using the ESPRESSO spectrograph on the VLT. The high quality of the data and proximity of the regions moti

Gregory P. Smith, Tommaso P. Fraccia, Chenhui Zhu, Tommaso Bellini

The collective behavior of the shortest DNA oligomers in high concentration aqueous solutions is an unexplored frontier of DNA science and technology. Here we broaden the realm of DNA nanoscience by demonstrating that single-component aqueous solutions of the DNA 4-base oligomer GCCG can spontaneously organize into three-dimensional (3D) periodic mesoscale f

Zhiwan Xu

The chiral magnetic/vortical effect (CME/CVE) in heavy-ion collisions probe the topological sector of Quantum Chromodynamics, where P and CP symmetries are violated locally in strong interactions. However, the experimental observables for the CME/CVE are dominated by backgrounds related to elliptic flow and nonflow. We employ event shape variables to mitigat

Anna Revazova, Igor Korkin

The Windows authentication infrastructure relies on the Local Security Authority (LSA) system, with its integral component being lsass.exe. Regrettably, this framework is not impervious, presenting vulnerabilities that attract threat actors with malicious intent. By exploiting documented vulnerabilities sourced from the CVE database or leveraging sophisticat

Yifan Su, Rishi Veerapaneni, Jiaoyang Li

The Multi-Agent Path Finding (MAPF) problem involves planning collision-free paths for multiple agents in a shared environment. The majority of MAPF solvers rely on the assumption that an agent can arrive at a specific location at a specific timestep. However, real-world execution uncertainties can cause agents to deviate from this assumption, leading to col

M. AbdulRazek, G. Khoriba, M. Belal

Medical imaging is an essential tool for diagnosing and treating diseases. However, lacking medical images can lead to inaccurate diagnoses and ineffective treatments. Generative models offer a promising solution for addressing medical image shortage problems due to their ability to generate new data from existing datasets and detect anomalies in this data.

Daniel Huttenlocher, Hannah Li, Liang Lyu, Asuman Ozdaglar

Many online platforms of today, including social media sites, are two-sided markets bridging content creators and users. Most of the existing literature on platform recommendation algorithms largely focuses on user preferences and decisions, and does not simultaneously address creator incentives. We propose a model of content recommendation that explicitly f

Seppo Hassi, Henk de Snoo

A sequence of operators $T_n$ from a Hilbert space ${\mathfrak H}$ to Hilbert spaces ${\mathfrak K}_n$ which is nondecreasing in the sense of contractive domination is shown to have a limit which is still a linear operator $T$ from ${\mathfrak H}$ to a Hilbert space ${\mathfrak K}$. Moreover, the closability or closedness of $T_n$ is preserved in the limit.

Will Traves

Traves and Wehlau recently gave a straightedge construction that checks whether 10 points lie on a plane cubic curve. They also highlighted several open problems in the synthetic geometry of cubics. Hermann Grassmann investigated incidence relations among points on cubic curves in three papers appearing in Crelle's Journal from 1846 to 1856. Grassmann's meth

Alexander Zuyev, Peter Benner

Nonlinear control-affine systems described by ordinary differential equations with bounded measurable input functions are considered. The solvability of general boundary value problems for these systems is formulated in the sense of Carath\'eodory solutions. It is shown that, under the dominant linearization assumption, the considered class of boundary value

G. D. Alexeev, M. G. Alexeev, C. Alice, A. Amoroso

New results are presented on a high-statistics measurement of Collins and Sivers asymmetries of charged hadrons produced in deep inelastic scattering of muons on a transversely polarised $^6$LiD target. The data were taken in 2022 with the COMPASS spectrometer using the 160 \gevv\ muon beam at CERN, balancing the existing data on transversely polarised proto

Yongchun Li, Santanu S. Dey, Weijun Xie

The classical Canonical Correlation Analysis (CCA) identifies the correlations between two sets of multivariate variables based on their covariance, which has been widely applied in diverse fields such as computer vision, natural language processing, and speech analysis. Despite its popularity, CCA can encounter challenges in explaining correlations between

Tayfun Sönmez

Minimalist market design is an economic design framework developed from the perspective of an outsider -- one seeking to improve real institutions without a commission or official mandate. It offers a structured, "minimally invasive" method for reforming institutions from within: identify their mission as understood by stakeholders, diagnose the root causes

Samantha Linn, Sean D. Lawley, Bhargav R. Karamched, Zachary P. Kilpatrick

Decisions are often made by heterogeneous groups of individuals, each with distinct initial biases and access to information of different quality. We show that in large groups of independent agents who accumulate evidence the first to decide are those with the strongest initial biases. Their decisions align with their initial bias, regardless of the underlyi

Arjan van der Schaft

One of the key contributions of the 1972 seminal paper by Willems was the analysis of symmetry (also called reciprocity) of input-state-output systems, both from an external (input-output) and internal (state) point of view. The developed theory also included the combination of reciprocity with passivity, and the consideration of relaxation systems, which ar

John K. Webb, Chung-Chi Lee

Searches for spacetime variations of fundamental constants have entered an era of unprecedented precision. New, high quality quasar spectra require increasingly refined analytic methods. In this article, a continuation in a series to establish robust and unbiased methodologies, we explore how convergence criteria in non-linear least squares optimisation impa

Esteban Cárdenas, Benjamín Pavez, Edgardo Stockmeyer

We prove tunneling estimates for two-dimensional Dirac systems which are localized in space due to the presence of a magnetic field. The Hamiltonian driving the motion admits the decomposition $H = H_0 + W$, where $H_0 $ is a rotationally symmetric magnetic Dirac operator and $W$ is a position-dependent matrix-valued potential satisfying certain smoothness c

Hiram K. Herrera-Alcantar, Andrea Muñoz-Gutiérrez, Ting Tan, Alma X. González-Morales

Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-$\alpha$ quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In part

Miloš S. Kurilić

For a relational structure ${\mathbb X}$ we investigate the partial order $\langle {\mathbb P} ({\mathbb X}) ,\subset \rangle$, where ${\mathbb P} ({\mathbb X}):=\{ f[X]: f\in \mathop{\rm Emb}\nolimits ({\mathbb X})\}$. Here we consider uncountable ordinals. Since $\mathop{\rm sq}\nolimits {\mathbb P} (\alpha )$ is isomorphic to the direct product $\prod _{i

S. P. O'Neil, C. A. Weidner, E. A. Jonckheere, F. C. Langbein

Dynamic control via optimized, piecewise-constant pulses is a common paradigm for open-loop control to implement quantum gates. While numerous methods exist for the synthesis of such controls, there are many open questions regarding the robustness of the resulting control schemes in the presence of model uncertainty; unlike in classical control, there are ge

Cemal Tugrul Yilmaz, Mamadou Diagne, Miroslav Krstic

We present multivariable extremum seeking (ES) designs that achieve unbiased convergence to the optimum. Two designs are introduced: one with exponential unbiased convergence (unbiased extremum seeker, uES) and the other with user-assignable prescribed-time unbiased convergence (unbiased PT extremum seeker, uPT-ES). In contrast to the conventional ES, which

Noga Alon, Jozsef Balogh, Vladimir N. Potapov

Denote by Q_d the d-dimensional hypercube. Addressing a recent question we estimate the number of ways the vertex set of Q_d can be partitioned into vertex disjoint smaller cubes. Among other results, we prove that the asymptotic order of this function is not much larger than the number of perfect matchings of Q_d. We also describe several new (and old) ques

Omer Ben-Porat, Yishay Mansour, Michal Moshkovitz, Boaz Taitler

Principal-agent problems arise when one party acts on behalf of another, leading to conflicts of interest. The economic literature has extensively studied principal-agent problems, and recent work has extended this to more complex scenarios such as Markov Decision Processes (MDPs). In this paper, we further explore this line of research by investigating how

Seyed Hassan Yajadda, Farshad Safaei

Despite technological advancements, the significance of interdisciplinary subjects like complex networks has grown. Exploring communication within these networks is crucial, with traffic becoming a key concern due to the expanding population and increased need for connections. Congestion tends to originate in specific network areas but quickly proliferates t

Maxime Medevielle, Thomas Mohaupt

When applying T-duality to a generic, non-extreme Killing horizon, T-duality is spacelike on one side and timelike on the other. We show, using simple examples from four-dimensional Einstein-Maxwell theory, that the image of the horizon is a singularity which can be understood as an interface between two different T-dual theories and their solutions. Using a

Sudipta Mondal, Samir Kumar Hazra, Aditi Sen De

Achieving perfect control over the parameters defining a quantum gate is, in general, a very challenging task, and at the same time, environmental interactions can introduce disturbances to the initial states as well. Here we address the problem of how the imperfections in unitaries and noise present in the input states affect the entanglement-generating pow

C. A. Weidner, E. A. Reed, J. Monroe, B. Sheller

Robust control of quantum systems is an increasingly relevant field of study amidst the second quantum revolution, but there remains a gap between taming quantum physics and robust control in its modern analytical form that culminated in fundamental performance bounds. With certain exceptions such as quantum optical systems that can be modeled as linear stoc

Victor Ujaldon Garcia

Four markets are considered: Cryptocurrencies / South American exchange rate / Spanish Banking indices and European Indices and studied using TDA (Topological Data Analysis) tools. These tools are used to predict and showcase both strengths and weakness of the current TDA tools. In this paper a new tool $L0$ norm is defined and complemented with the already

Nguyen B. Tran, Tran N. Nguyen, Huynh M. Hien

This work deals with a maximal monotone operator $A$ of type (D) in a Banach space whose dual space is strictly convex. We establish some representations for the value $Ax$ at a given point $x$ via its values at nearby points of $x$. We show that the faces of $Ax$ are contained in the set of all weak$^*$ convergent limits of bounded nets of the operator at n

Grzegorz Filcek, Janusz Miroforidis

The Multi-Objective Mixed-Integer Programming (MOMIP) problem is one of the most challenging. To derive its Pareto optimal solutions one can use the well-known Chebyshev scalarization and Mixed-Integer Programming (MIP) solvers. However, for a large-scale instance of the MOMIP problem, its scalarization may not be solved to optimality, even by state-of-the-a

Feiyan Guo, Jiajun Zhou, Zhongyuan Ruan, Jian Zhang

The box-covering method plays a fundamental role in the fractal property recognition and renormalization analysis of complex networks. This study proposes the hub-collision avoidance and leaf-node options (HALO) algorithm. In the box sampling process, a forward sampling rule (for avoiding hub collisions) and a reverse sampling rule (for preferentially select

Aleksander Buszydlik, Karol Dobiczek, Michał Teodor Okoń, Konrad Skublicki

We consider the problem of red teaming LLMs on elementary calculations and algebraic tasks to evaluate how various prompting techniques affect the quality of outputs. We present a framework to procedurally generate numerical questions and puzzles, and compare the results with and without the application of several red teaming techniques. Our findings suggest

Md Shahinur Alam, Jason Lamberton, Jianye Wang, Carly Leannah

We developed an American Sign Language (ASL) learning platform in a Virtual Reality (VR) environment to facilitate immersive interaction and real-time feedback for ASL learners. We describe the first game to use an interactive teaching style in which users learn from a fluent signing avatar and the first implementation of ASL sign recognition using deep lear

Yao Wan, Yang He, Zhangqian Bi, Jianguo Zhang

Code intelligence leverages machine learning techniques to extract knowledge from extensive code corpora, with the aim of developing intelligent tools to improve the quality and productivity of computer programming. Currently, there is already a thriving research community focusing on code intelligence, with efforts ranging from software engineering, machine

Neeraj Varshney, Pavel Dolin, Agastya Seth, Chitta Baral

As Large Language Models (LLMs) play an increasingly pivotal role in natural language processing applications, their safety concerns become critical areas of NLP research. This paper presents Safety and Over-Defensiveness Evaluation (SODE) benchmark: a collection of diverse safe and unsafe prompts with carefully designed evaluation methods that facilitate sy

Siva Raja Sindiramutty

The evolution of cybersecurity has spurred the emergence of autonomous threat hunting as a pivotal paradigm in the realm of AI-driven threat intelligence. This review navigates through the intricate landscape of autonomous threat hunting, exploring its significance and pivotal role in fortifying cyber defense mechanisms. Delving into the amalgamation of arti

Zeyang Zhang, Hui Li, Tianyang Xu, Xiaojun Wu

In a scenario where multi-modal cameras are operating together, the problem of working with non-aligned images cannot be avoided. Yet, existing image fusion algorithms rely heavily on strictly registered input image pairs to produce more precise fusion results, as a way to improve the performance of downstream high-level vision tasks. In order to relax this

Maximilian Weber, Merle Reichardt

This paper explores the use of open generative Large Language Models (LLMs) for annotation tasks in the social sciences. The study highlights the challenges associated with proprietary models, such as limited reproducibility and privacy concerns, and advocates for the adoption of open (source) models that can be operated on independent devices. Two examples

Hongshan Liu, Tong Qin, Zhen Gao, Tianqi Mao

This article presents a comprehensive study on the emerging near-space communications (NS-COM) within the context of space-air-ground-sea integrated network (SAGSIN). Specifically, we firstly explore the recent technical developments of NS-COM, followed by the discussions about motivations behind integrating NS-COM into SAGSIN. To further demonstrate the nec

Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar

Symbolic regression (SR) aims to discover concise closed-form mathematical equations from data, a task fundamental to scientific discovery. However, the problem is highly challenging because closed-form equations lie in a complex combinatorial search space. Existing methods, ranging from heuristic search to reinforcement learning, fail to scale with the numb

Arkady Pikovsky, Franco Bagnoli

We study populations of oscillators, all-to-all coupled by means of quenched disordered phase shifts. While there is no traditional synchronization transition with a nonvanishing Kuramoto order parameter, the system demonstrates a specific order as the coupling strength increases. This order is characterized by partial phase locking, which is put into eviden

Anastasiia Kropova, Igor Korkin

The purpose of this study is to evaluate the possibility of implementing an attack on ALPC connection in the Windows operating system through the kernel without closing the connection covertly from programs and the operating system and to propose a method of protection against this type of attacks. Asynchronous Local Procedure Call technology (ALPC) is used

Reza Fayyazi, Rozhina Taghdimi, Shanchieh Jay Yang

Tactics, Techniques, and Procedures (TTPs) outline the methods attackers use to exploit vulnerabilities. The interpretation of TTPs in the MITRE ATT&CK framework can be challenging for cybersecurity practitioners due to presumed expertise and complex dependencies. Meanwhile, advancements with Large Language Models (LLMs) have led to recent surge in studies e

Jonas Hirsch, Luca Spolaor

We prove that the singular set of a $2$-valued Lipschitz graph that is stationary for the area is of codimension $1$.

Abinash Das

The intrinsic alignment (IA) of galaxies acts as a systematic effect in weak lensing measurements and tends to introduce biases. It mimics the gravitational lensing signal which makes it difficult to distinguish it from the true gravitational weak lensing effect. Hence, it is critical to account for the noise for correctly interpreting the results. This stud

Benjamin Koch, Enrique Muñoz, Alessandro Santoni

Ultracold neutrons are great experimental tools to explore the gravitational interaction in the regime of quantized states. From a theoretical perspective, starting from a Dirac equation in curved spacetime, we applied a perturbative scheme to systematically derive the non-relativistic Schr\"odinger equation that governs the evolution of the neutron's wave f

Yusuf Sale, Paul Hofman, Lisa Wimmer, Eyke Hüllermeier

Uncertainty quantification is a critical aspect of machine learning models, providing important insights into the reliability of predictions and aiding the decision-making process in real-world applications. This paper proposes a novel way to use variance-based measures to quantify uncertainty on the basis of second-order distributions in classification prob

Hari Prasad SV

One notable method for recording brainwaves to identify neurological problems is electroencephalography (hereafter EEG). A trained neuro physician can learn more about how the brain functions through the use of EEGs. However conventionally, EEGs are only used to examine neurological problems (Eg. Seizures). But abnormal links to neurological circuits can als

Vladyslav Gapyak, Corinna Rentschler, Thomas März, Andreas Weinmann

Objective: Magnetic particle imaging (MPI) is an emerging medical imaging modality which has gained increasing interest in recent years. Among the benefits of MPI are its high temporal resolution, and that the technique does not expose the specimen to any kind of ionizing radiation. It is based on the non-linear response of magnetic nanoparticles to an appli

Yunuo Xiong, Shujuan Liu, Hongwei Xiong

Recently, fictitious identical particles have provided a promising way to overcome the fermion sign problem and have been used in path integral Monte Carlo (PIMC) to accurately simulate warm dense matter with up to 1000 electrons (T. Dornheim et al., arXiv:2311.08098 (2023)). The inclusion of fictitious identical particles in path integral molecular dynamics

Chih-Kai Yang, Kuan-Po Huang, Ke-Han Lu, Chun-Yi Kuan

This work evaluated several cutting-edge large-scale foundation models based on self-supervision or weak supervision, including SeamlessM4T, SeamlessM4T v2, and Whisper-large-v3, on three code-switched corpora. We found that self-supervised models can achieve performances close to the supervised model, indicating the effectiveness of multilingual self-superv

Can Chen, Hao Liu, Zeming Liu, Xue Liu

Proactively and naturally guiding the dialog from the non-recommendation context (e.g., Chit-chat) to the recommendation scenario (e.g., Music) is crucial for the Conversational Recommender System (CRS). Prior studies mainly focus on planning the next dialog goal~(e.g., chat on a movie star) conditioned on the previous dialog. However, we find the dialog goa

Ana Uzelac

This paper introduces an educational card game designed to elucidate fundamental particle physics concepts, specifically emphasizing the classification of hadrons through the "Eightfold Path." Derived from the Quark Matter Card Games series, the game entails arranging elementary particle cards to construct baryons and mesons on designated game boards. Detail

Yilan Dong, Chunlin Yu, Ruiyang Ha, Ye Shi

Existing gait recognition benchmarks mostly include minor clothing variations in the laboratory environments, but lack persistent changes in appearance over time and space. In this paper, we propose the first in-the-wild benchmark CCGait for cloth-changing gait recognition, which incorporates diverse clothing changes, indoor and outdoor scenes, and multi-mod

Gareth A. Jones, Alexander K. Zvonkin

Motivated by their research on automorphism groups of pseudo-real Riemann surfaces, Bujalance, Cirre and Conder have conjectured that there are infinitely many primes $p$ such that $p+2$ has all its prime factors $q\equiv -1$ mod~$(4)$. We use theorems of Landau and Raikov to prove that the number of integers $n\le x$ with only such prime factors $q$ is asym

Rong-Peng Liu, Yunhe Hou, Yujia Li, Shunbo Lei

This paper adopts a two-stage sample robust optimization (SRO) model to address the wind power penetrated unit commitment optimal energy flow (UC-OEF) problem for IEGSs. The two-stage SRO model can be approximately transformed into a computationally efficient form. Specifically, we employ linear decision rules to simplify the proposed UC-OEF model. Moreover,

Ana Uzelac

This paper introduces a card game called "Quark Matter Card Games," inspired by the creativity of a high school student, Csaba T\"or\"ok, and developed in collaboration with physicist Tam\'as Cs\"org\H{o}. The game utilizes a deck of 66 cards representing elementary particles and antiparticles, offering an entertaining way to popularize science and introduce

Joseph D. Hart

Reservoir computing is a machine learning framework that has been shown to be able to replicate the chaotic attractor, including the fractal dimension and the entire Lyapunov spectrum, of the dynamical system on which it is trained. We quantitatively relate the generalized synchronization dynamics of a driven reservoir during the training stage to the perfor

Lianyu Hu, Liqing Gao, Zekang Liu, Chi-Man Pun

Pretrained large-scale vision-language models such as CLIP have demonstrated excellent generalizability over a series of downstream tasks. However, they are sensitive to the variation of input text prompts and need a selection of prompt templates to achieve satisfactory performance. Recently, various methods have been proposed to dynamically learn the prompt

James Ingoldby

This proceedings paper extends the scope of our conference talk, where we presented a comprehensive analysis of newly expanded and refined lattice data concerning the SU(3) gauge theory with Nf = 8 light Dirac fermions - a theory positioned near the conformal window boundary. The analysis presented here makes use of a dilaton effective field theory and we de

Brent Cody, Chris Lambie-Hanson, Jing Zhang

We introduce a natural two-cardinal version of Bagaria's sequence of derived topologies on ordinals. We prove that for our sequence of two-cardinal derived topologies, limit points of sets can be characterized in terms of a new iterated form of pairwise simultaneous reflection of certain kinds of stationary sets, the first few instances of which are often eq

Jae Hyuck Lee, GwanWoo Kim, Inkyung Song, Yejin Kim

In condensed matter physics, the Kagome lattice and its inherent flat bands have attracted considerable attention for their potential to host a variety of exotic physical phenomena. Despite extensive efforts to fabricate thin films of Kagome materials aimed at modulating the flat bands through electrostatic gating or strain manipulation, progress has been li

Wayne Yuan Gao, Rui Wang

This paper provides a general identification approach for a wide range of nonlinear panel data models, including binary choice, ordered response, and other types of limited dependent variable models. Our approach accommodates dynamic models with any number of lagged dependent variables as well as other types of endogenous covariates. Our identification strat

Christoph Moehr

This paper sets out a framework for the valuation of insurance liabilities that is intended to be economically realistic, elementary, reasonably practically applicable, and as a special case to provide a basis for the valuation in regulatory solvency systems such as Solvency II and the SST. The valuation framework is based on the cost of producing the liabil