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Recent advances in training vision-language models have demonstrated unprecedented robustness and transfer learning effectiveness; however, standard computer vision datasets are image-only, and therefore not well adapted to such training methods. Our paper introduces a simple methodology for adapting any fine-grained i...
http://arxiv.org/abs/2302.10281v1
We propose a hybrid neural network (NN) and PDE approach for learning generalizable PDE dynamics from motion observations. Many NN approaches learn an end-to-end model that implicitly models both the governing PDE and constitutive models (or material models). Without explicit PDE knowledge, these approaches cannot guar...
http://arxiv.org/abs/2304.14369v2
In scenarios with long-tailed distributions, the model's ability to identify tail classes is limited due to the under-representation of tail samples. Class rebalancing, information augmentation, and other techniques have been proposed to facilitate models to learn the potential distribution of tail classes. The disadva...
http://arxiv.org/abs/2310.10090v1
Stimulated Raman Adiabatic Passage (STIRAP) is a widely used method for adiabatic population transfer in a multilevel system. In this work, we study STIRAP under novel conditions and focus on the fractional, F-STIRAP, which is known to create a superposition state with the maximum coherence. In both configurations, STI...
http://arxiv.org/abs/2305.18652v1
Kuznetsov and Polishchuk provided a general algorithm to construct exceptional collections of maximal length for homogeneous varieties of type A,B,C,D. We consider the case of the spinor tenfold and we prove that the corresponding collection is full, i.e. it generates the whole derived category of coherent sheaves. As ...
http://arxiv.org/abs/2306.10986v1
Accuracy and diversity have long been considered to be two conflicting goals for recommendations. We point out, however, that as the diversity is typically measured by certain pre-selected item attributes, e.g., category as the most popularly employed one, improved diversity can be achieved without sacrificing recommen...
http://arxiv.org/abs/2301.05492v1
Tracking characters and locations throughout a story can help improve the understanding of its plot structure. Prior research has analyzed characters and locations from text independently without grounding characters to their locations in narrative time. Here, we address this gap by proposing a new spatial relationship...
http://arxiv.org/abs/2305.17561v1
Collider experiments provide an opportunity to produce particles at close distances and momenta. The measured correlation functions between particles can provide information on both the effective emission source and the interaction potential. In recent years, experiments at the LHC have shown that precision studies of ...
http://arxiv.org/abs/2305.08441v2
Swift J1749.4-2807 is the only known eclipsing accreting millisecond X-ray pulsar. In this paper, we report on 7 thermonuclear (Type-I) X-ray bursts observed by NICER during its 2021 outburst. The first 6 bursts show slow rises and long decays, indicative of mixed H/He fuel, whereas the last burst shows fast rise and d...
http://arxiv.org/abs/2306.11440v1
We extend previous efforts to quantify the entanglement generated in Hawking's evaporation process by including rotation and thermal environments (e.g. the cosmic microwave background). Both extensions are needed to describe real black holes in our universe. Leveraging techniques from Gaussian quantum information, we f...
http://arxiv.org/abs/2307.06215v2
Large-scale pre-trained models have achieved remarkable success in many applications, but how to leverage them to improve the prediction reliability of downstream models is undesirably under-explored. Moreover, modern neural networks have been found to be poorly calibrated and make overconfident predictions regardless ...
http://arxiv.org/abs/2304.10127v2
As a two-dimensional planar material with low depth profile, a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface. Thus, it offers more flexibility to control the wave front. A traditional metasurface design process mainly adopts the forwa...
http://arxiv.org/abs/2307.09126v1
ML models are increasingly being pushed to mobile devices, for low-latency inference and offline operation. However, once the models are deployed, it is hard for ML operators to track their accuracy, which can degrade unpredictably (e.g., due to data drift). We design the first end-to-end system for continuously monito...
http://arxiv.org/abs/2305.07772v2
Satellites have become more widely available due to the reduction in size and cost of their components. As a result, there has been an advent of smaller organizations having the ability to deploy satellites with a variety of data-intensive applications to run on them. One popular application is image analysis to detect...
http://arxiv.org/abs/2301.04954v2
Google has mandated developers to use Data Safety Sections (DSS) to increase transparency in data collection and sharing practices. In this paper, we present a comprehensive analysis of Google's Data Safety Section (DSS) using both quantitative and qualitative methods. We conduct the first large-scale measurement study...
http://arxiv.org/abs/2306.08111v1
We develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) hardware. Our approach leverages Hessian-aware quantization (HAWQ) of NNs, the Quantized Open Neural Network Ex...
http://arxiv.org/abs/2304.06745v1
A spin Hamiltonian, which characterizes interatomic interactions between spin moments, is highly valuable in predicting and comprehending the magnetic properties of materials. A deeper understanding of the microscopic origin of magnetic interactions can open new pathways toward realizing nanometer-scale systems for fut...
http://arxiv.org/abs/2306.07222v2
We define and fully characterize the witnesses based on second moments detecting steering in Gaussian states by means of Gaussian measurements. All such tests, which arise from linear combination of variances or second moments of canonical operators, are easily implemented in experiments. We propose also a set of linea...
http://arxiv.org/abs/2304.11239v1
This paper revisits an adaptation of the random forest algorithm for Fr\'echet regression, addressing the challenge of regression in the context of random objects in metric spaces. Recognizing the limitations of previous approaches, we introduce a new splitting rule that circumvents the computationally expensive operat...
http://arxiv.org/abs/2306.17031v1
We present a CNN-BiLSTM system for the problem of offline English handwriting recognition, with extensive evaluations on the public IAM dataset, including the effects of model size, data augmentation and the lexicon. Our best model achieves 3.59\% CER and 9.44\% WER using CNN-BiLSTM network with CTC layer. Test time au...
http://arxiv.org/abs/2307.00664v1
We propose TextManiA, a text-driven manifold augmentation method that semantically enriches visual feature spaces, regardless of class distribution. TextManiA augments visual data with intra-class semantic perturbation by exploiting easy-to-understand visually mimetic words, i.e., attributes. This work is built on an i...
http://arxiv.org/abs/2307.14611v3
Citations in scientific papers not only help us trace the intellectual lineage but also are a useful indicator of the scientific significance of the work. Citation intents prove beneficial as they specify the role of the citation in a given context. In this paper, we present CitePrompt, a framework which uses the hithe...
http://arxiv.org/abs/2304.12730v2
Quantum thermodynamics seeks to extend non-equilibrium stochastic thermodynamics to small quantum systems where non-classical features are essential to its description. Such a research area has recently provided meaningful theoretical and experimental advances by exploring the wealth and the power of quantum features a...
http://arxiv.org/abs/2303.08917v1
We propose a model to flexibly estimate joint tail properties by exploiting the convergence of an appropriately scaled point cloud onto a compact limit set. Characteristics of the shape of the limit set correspond to key tail dependence properties. We directly model the shape of the limit set using Bezier splines, whic...
http://arxiv.org/abs/2306.13257v3
We explore the opportunities of using electron scattering by screened Coulomb potential as a tool to retrieve properties of the relativistic vortex beams of electrons, such as their transverse momentum and orbital angular momentum (OAM). We focus on relativistic and ultra-relativistic regimes of the electron energies o...
http://arxiv.org/abs/2305.12419v2
The coherent transport of charge and spin is one key requirement of future devices for quantum computing and communication. Scattering at defects or impurities may seriously reduce the coherence of quantum-mechanical states, thereby affecting device functionality. While numerous methods exist to experimentally assess c...
http://arxiv.org/abs/2303.00393v1
Language models have graduated from being research prototypes to commercialized products offered as web APIs, and recent works have highlighted the multilingual capabilities of these products. The API vendors charge their users based on usage, more specifically on the number of ``tokens'' processed or generated by the ...
http://arxiv.org/abs/2305.13707v1
The critical challenge of Semi-Supervised Learning (SSL) is how to effectively leverage the limited labeled data and massive unlabeled data to improve the model's generalization performance. In this paper, we first revisit the popular pseudo-labeling methods via a unified sample weighting formulation and demonstrate th...
http://arxiv.org/abs/2301.10921v2
Graph convolutional network (GCN) has been successfully applied to capture global non-consecutive and long-distance semantic information for text classification. However, while GCN-based methods have shown promising results in offline evaluations, they commonly follow a seen-token-seen-document paradigm by constructing...
http://arxiv.org/abs/2304.04152v1
Boundaries of Walker-Wang models have been used to construct commuting projector models which realize chiral unitary modular tensor categories (UMTCs) as boundary excitations. Given a UMTC $\mathcal{A}$ representing the Witt class of an anomaly, the article [arXiv:2208.14018] gave a commuting projector model associated...
http://arxiv.org/abs/2305.14068v2
High-precision modeling of systems is one of the main areas of industrial data analysis. Models of systems, their digital twins, are used to predict their behavior under various conditions. We have developed several models of a storage system using machine learning-based generative models. The system consists of severa...
http://arxiv.org/abs/2307.02073v1
In this article, we study algebraic properties of binomial edge ideals of Levi graphs associated with certain plane curve arrangements. Using combinatorial properties of Levi graphs, we discuss the Cohen-Macaulayness of binomial edge ideals of Levi graphs associated to some curve arrangements in the complex projective ...
http://arxiv.org/abs/2310.08191v3
For decades, the application of muon tomography to spent nuclear fuel (SNF) cask imaging has been theoretically evaluated and experimentally verified by many research groups around the world, including Los Alamos National Laboratory in the United States, Canadian Nuclear Laboratory in Canada, the National Institute for...
http://arxiv.org/abs/2304.14427v1
DAG-based consensus has attracted significant interest due to its high throughput in asynchronous network settings. However, existing protocols such as DAG-rider (Keidar et al., PODC 2021) and ``Narwhal and Tusk'' (Danezis et al., Eurosys 2022) face two undesired practical issues: (1) high transaction latency and (2) h...
http://arxiv.org/abs/2307.15269v2
The coupling of microwave and optical systems presents an immense challenge due to the natural incompatibility of energies, but potential applications range from optical interconnects for quantum computers to next-generation quantum microwave sensors, detectors or coherent imagers. Several engineered platforms have eme...
http://arxiv.org/abs/2302.08380v2
Over-generalization is a thorny issue in cognitive science, where people may become overly cautious due to past experiences. Agents in multi-agent reinforcement learning (MARL) also have been found to suffer relative over-generalization (RO) as people do and stuck to sub-optimal cooperation. Recent methods have shown t...
http://arxiv.org/abs/2306.05353v1
Recently, diffusion models have achieved great success in image synthesis. However, when it comes to the layout-to-image generation where an image often has a complex scene of multiple objects, how to make strong control over both the global layout map and each detailed object remains a challenging task. In this paper,...
http://arxiv.org/abs/2303.17189v2
Based on the closed operational laws in picture fuzzy numbers and strict triangular norms, we extend the Bonferroni mean (BM) operator under the picture fuzzy environment to propose the picture fuzzy interactional Bonferroni mean (PFIBM), picture fuzzy interactional weighted Bonferroni mean (PFIWBM), and picture fuzzy ...
http://arxiv.org/abs/2301.01192v1
Recent experiments reported that the magnetic field can drive the Lifshitz transition and one-dimensional (1D) Weyl nodes in the quantum limit of three-dimensional pentatellurides, as they own low carrier densities and can achieve the extreme quantum limit at a low magnetic field. In this paper, we will investigate the...
http://arxiv.org/abs/2310.10906v1
Processes of random tessellations of the Euclidean space $\mathbb{R}^d$, $d\geq 1$, are considered which are generated by subsequent division of their cells. Such processes are characterized by the laws of the life times of the cells until their division and by the laws for the random hyperplanes that divide the cells ...
http://arxiv.org/abs/2303.16297v2
Machine learning has been applied to the problem of X-ray diffraction phase prediction with promising results. In this paper, we describe a method for using machine learning to predict crystal structure phases from X-ray diffraction data of transition metals and their oxides. We evaluate the performance of our method a...
http://arxiv.org/abs/2305.15410v1
The present study introduces the notions of statistical convergence of order $\alpha$ and strong $p-$ Ces\`{a}ro summability of order $\alpha$ in partial metric spaces. Also, we examine the inclusion relations between these concepts. In addition, we introduce the notion of $\lambda -$% statistical convergence of order ...
http://arxiv.org/abs/2304.02245v1
We study the L\'evy spin glass model, a fully connected model on $N$ vertices with heavy-tailed interactions governed by a power law distribution of order $0<\alpha<2.$ Our investigation is divided into three cases $0<\alpha<1$, $\alpha=1$, and $1<\alpha<2.$ When $1<\alpha<2,$ we identify a high temperature regime, in ...
http://arxiv.org/abs/2303.06084v4
In this paper we have addressed the implementation of the accumulation and projection of high-resolution event data stream (HD -1280 x 720 pixels) onto the image plane in FPGA devices. The results confirm the feasibility of this approach, but there are a number of challenges, limitations and trade-offs to be considered...
http://arxiv.org/abs/2307.14177v1
We prove that superclub implies $\mathfrak{s}=\aleph_1$. More generally, superclub at a successor of a weakly compact cardinal implies $\mathfrak{s}_\kappa=\kappa^+$. Based on this statement, we separate tiltan from superclub at a successor of a supercompact cardinal. We use Galvin's property in order to separate tilta...
http://arxiv.org/abs/2302.00904v2
Most research on hate speech detection has focused on English where a sizeable amount of labeled training data is available. However, to expand hate speech detection into more languages, approaches that require minimal training data are needed. In this paper, we test whether natural language inference (NLI) models whic...
http://arxiv.org/abs/2306.03722v2
Random ensembles of pure states have proven to be extremely important in various aspects of quantum physics such as benchmarking the performance of quantum circuits, testing for quantum advantage, providing novel insights for many-body thermalization and studying the black hole information paradox. Although generating ...
http://arxiv.org/abs/2305.01465v3
This paper introduces a new regularized version of the robust $\tau$-regression estimator for analyzing high-dimensional datasets subject to gross contamination in the response variables and covariates (explanatory variables). The resulting estimator, termed adaptive $\tau$-Lasso, is robust to outliers and high-leverag...
http://arxiv.org/abs/2304.09310v3
The COVID-19 pandemic has highlighted the need for innovative solutions to monitor and control the spread of infectious diseases. With the potential for future pandemics and the risk of outbreaks particularly in academic institutions, there is a pressing need for effective approaches to monitor and manage such diseases...
http://arxiv.org/abs/2307.10311v1
Energy efficiency and low latency are crucial requirements for designing wearable AI-empowered human activity recognition systems, due to the hard constraints of battery operations and closed-loop feedback. While neural network models have been extensively compressed to match the stringent edge requirements, spiking ne...
http://arxiv.org/abs/2308.00787v1
Recording animal behaviour is an important step in evaluating the well-being of animals and further understanding the natural world. Current methods for documenting animal behaviour within a zoo setting, such as scan sampling, require excessive human effort, are unfit for around-the-clock monitoring, and may produce hu...
http://arxiv.org/abs/2306.11326v1
Van der Waals (vdWs) heterostructures assembled by stacking 2D crystal layers have proven to be a new material platform for high-performance optoelectronic applications such as thin film transistors, photodetectors, and emitters. Here, we demonstrate a novel device with strain tuning capabilities using MoS2/Sb2Te3 vdWs...
http://arxiv.org/abs/2305.08327v1
Taxonomy is formulated as directed acyclic concepts graphs or trees that support many downstream tasks. Many new coming concepts need to be added to an existing taxonomy. The traditional taxonomy expansion task aims only at finding the best position for new coming concepts in the existing taxonomy. However, they have t...
http://arxiv.org/abs/2303.14480v1
This paper presents a novel Diffusion-Wavelet (DiWa) approach for Single-Image Super-Resolution (SISR). It leverages the strengths of Denoising Diffusion Probabilistic Models (DDPMs) and Discrete Wavelet Transformation (DWT). By enabling DDPMs to operate in the DWT domain, our DDPM models effectively hallucinate high-f...
http://arxiv.org/abs/2304.01994v2
Shower development dynamics for a jet traveling through the quark-gluon plasma (QGP) is a multiscale process, where the heavy flavor mass is an important scale. During the high virtuality portion of the jet evolution in the QGP, emission of gluons from a heavy flavor is modified owing to heavy quark mass. Medium-induce...
http://arxiv.org/abs/2307.09640v2
Graph Convolutional Networks (GCN) have been recently employed as core component in the construction of recommender system algorithms, interpreting user-item interactions as the edges of a bipartite graph. However, in the absence of side information, the majority of existing models adopt an approach of randomly initial...
http://arxiv.org/abs/2303.15946v1
Amateurs working on mini-films and short-form videos usually spend lots of time and effort on the multi-round complicated process of setting and adjusting scenes, plots, and cameras to deliver satisfying video shots. We present Virtual Dynamic Storyboard (VDS) to allow users storyboarding shots in virtual environments,...
http://arxiv.org/abs/2301.12688v3
We explore the impact of strong classical color fields, which occur in the earliest stages of heavy-ion collisions and are known as the Glasma, on the classical transport of hard probes, namely heavy quarks and jets. To achieve this, we simulate SU(3) color fields using classical real-time lattice gauge theory and coup...
http://arxiv.org/abs/2303.05599v3
Reinforcement learning (RL) is a branch of machine learning that has been used in a variety of applications such as robotics, game playing, and autonomous systems. In recent years, there has been growing interest in applying RL to quantitative trading, where the goal is to make profitable trades in financial markets. T...
http://arxiv.org/abs/2304.06037v1
Matrix factorization-based recommender system is in effect an angle preserving dimensionality reduction technique. Since the frequency of items follows power-law distribution, most vectors in the original dimension of user feature vectors and item feature vectors lie on the same hyperplane. However, it is very difficul...
http://arxiv.org/abs/2301.03791v1
We study the fundamental limits of matching pursuit, or the pure greedy algorithm, for approximating a target function $ f $ by a linear combination $f_n$ of $n$ elements from a dictionary. When the target function is contained in the variation space corresponding to the dictionary, many impressive works over the past ...
http://arxiv.org/abs/2307.07679v3
Learning decompositions of expensive-to-evaluate black-box functions promises to scale Bayesian optimisation (BO) to high-dimensional problems. However, the success of these techniques depends on finding proper decompositions that accurately represent the black-box. While previous works learn those decompositions based...
http://arxiv.org/abs/2301.12844v2
At the staggering pace with which the capabilities of large language models (LLMs) are increasing, creating future-proof evaluation sets to assess their understanding becomes more and more challenging. In this paper, we propose a novel paradigm for evaluating LLMs which leverages the idea that correct world understandi...
http://arxiv.org/abs/2305.11662v3
Morphological development into evolutionary patterns under structural instability is ubiquitous in living systems and often of vital importance for engineering structures. Here we propose a data-driven approach to understand and predict their spatiotemporal complexities. A machine-learning framework is proposed based o...
http://arxiv.org/abs/2308.11846v1
We present nested sequent systems for propositional G\"odel-Dummett logic and its first-order extensions with non-constant and constant domains, built atop nested calculi for intuitionistic logics. To obtain nested systems for these G\"odel-Dummett logics, we introduce a new structural rule, called the "linearity rule,...
http://arxiv.org/abs/2306.07550v2
Human beings always engage in a vast range of activities and tasks that demonstrate their ability to adapt to different scenarios. Any human activity can be represented as a temporal sequence of actions performed to achieve a certain goal. Unlike the time series datasets extracted from electronics or machines, these ac...
http://arxiv.org/abs/2307.10305v1
We introduce dataset multiplicity, a way to study how inaccuracies, uncertainty, and social bias in training datasets impact test-time predictions. The dataset multiplicity framework asks a counterfactual question of what the set of resultant models (and associated test-time predictions) would be if we could somehow ac...
http://arxiv.org/abs/2304.10655v1
One of the important problems with the existence of weak gravity conjecture ($WGC$) is the violation of the cosmic censorship. Such a cosmic phenomena is important and consistent in general relativity. It means that for a charged black hole in four dimensions and in the normal state, the $WGC$ cannot hold due to the vi...
http://arxiv.org/abs/2307.09654v1
In this paper, we study the problem of (finite horizon tabular) Markov decision processes (MDPs) with heavy-tailed rewards under the constraint of differential privacy (DP). Compared with the previous studies for private reinforcement learning that typically assume rewards are sampled from some bounded or sub-Gaussian ...
http://arxiv.org/abs/2306.01121v2
We study analytic aspects of the Dunkl-type Hankel transform, which goes back to Baker and Forrester and, in an earlier symmetrized version, to Macdonald. Moreover, we introduce a Dunkl analogue of the Bessel function and K-Bessel function generalizing those of a symmetric cone. Further, we take a look at zeta integral...
http://arxiv.org/abs/2303.15952v2
The layered ATMPn$_2$ (A = alkali earth or rare earth atom, TM = transition metal, Pn = Sb, Bi) compounds are widely studied for their rich magnetism and electronic structure topology. Here, we characterize the physical properties of LaMn$_x$Sb$_2$, an understudied member of the ATMPn$_2$ family. LaMn$_x$Sb$_2$ forms w...
http://arxiv.org/abs/2308.12397v1
Few-shot node classification, which aims to predict labels for nodes on graphs with only limited labeled nodes as references, is of great significance in real-world graph mining tasks. Particularly, in this paper, we refer to the task of classifying nodes in classes with a few labeled nodes as the few-shot node classif...
http://arxiv.org/abs/2306.15154v1
Modern society is getting accustomed to the Internet of Things (IoT) and Cyber-Physical Systems (CPS) for a variety of applications that involves security-critical user data and information transfers. In the lower end of the spectrum, these devices are resource-constrained with no attack protection. They become a soft ...
http://arxiv.org/abs/2305.03266v1
We aim to address the following question: if we start with a quantum state with a spontaneously broken higher-form symmetry, what is the fate of the system under weak local quantum measurements? We demonstrate that under certain conditions, a phase transition can be driven by weak measurements, which suppresses the spo...
http://arxiv.org/abs/2304.14433v2
Understanding the location of ultra-wideband (UWB) tag-attached objects and people in the real world is vital to enabling a smooth cyber-physical transition. However, most UWB localization systems today require multiple anchors in the environment, which can be very cumbersome to set up. In this work, we develop XRLoc, ...
http://arxiv.org/abs/2307.12512v4
In this study we investigate the directional scattering of terahertz radiation by dielectric cylinders, focusing on the enhancement of directionality using incident radiation of complex-frequency. We explore the optimization of the second Kerker condition, which corresponds to backward scattering. At first, by carefull...
http://arxiv.org/abs/2305.04509v2
Liquidity providers are essential for the function of decentralized exchanges to ensure liquidity takers can be guaranteed a counterparty for their trades. However, liquidity providers investing in liquidity pools face many risks, the most prominent of which is impermanent loss. Currently, analysis of this metric is di...
http://arxiv.org/abs/2301.06831v1
Microservices architecture is one of the new architectural styles that has improved in recent years. It has become a popular architectural style among system architects and developers. This popularity increased with the advent of new technologies and technological advancements in cloud computing. These advancements cau...
http://arxiv.org/abs/2308.05833v1
We investigate the conformational properties of a multi-branched polymer structure with a dendrimer-like topology, known as a snowflake polymer. This polymer is characterized by two parameters: $f_s$, which represents the functionality of the central star-like core, and $f$, which represents the functionality of the si...
http://arxiv.org/abs/2306.13525v1
Feature matching is an important computer vision task that involves estimating correspondences between two images of a 3D scene, and dense methods estimate all such correspondences. The aim is to learn a robust model, i.e., a model able to match under challenging real-world changes. In this work, we propose such a mode...
http://arxiv.org/abs/2305.15404v2
Relation extraction models trained on a source domain cannot be applied on a different target domain due to the mismatch between relation sets. In the current literature, there is no extensive open-source relation extraction dataset specific to the finance domain. In this paper, we release FinRED, a relation extraction...
http://arxiv.org/abs/2306.03736v1
Spiking neural networks are becoming increasingly popular for their low energy requirement in real-world tasks with accuracy comparable to the traditional ANNs. SNN training algorithms face the loss of gradient information and non-differentiability due to the Heaviside function in minimizing the model loss over model p...
http://arxiv.org/abs/2302.00910v2
Combining information both within and between sample realizations, we propose a simple estimator for the local regularity of surfaces in the functional data framework. The independently generated surfaces are measured with errors at possibly random discrete times. Non-asymptotic exponential bounds for the concentration...
http://arxiv.org/abs/2307.14163v3
Dielectric nanoresonators have been shown to circumvent the heavy optical losses associated with plasmonic devices, however they suffer from less confined resonances. By constructing a hybrid system of both dielectric and metallic materials, one can retain the low losses of dielectric resonances, whilst gaining additio...
http://arxiv.org/abs/2304.02537v2
In the framework of nonrelativistic QCD, the excited doubly heavy baryons are thoroughly studied via the channel $e^{+} e^{-}\rightarrow \langle QQ^{\prime}\rangle[n] \rightarrow \Xi_{QQ^{\prime}} +\bar{Q^{\prime}} +\bar{Q}$, which takes place at the collision energy $Z$-pole. $Q^{(\prime)}$ represents $b$ or $c$ quark...
http://arxiv.org/abs/2305.15362v2
We propose an automated lowest floor elevation (LFE) estimation algorithm based on computer vision techniques to leverage the latent information in street view images. Flood depth-damage models use a combination of LFE and flood depth for determining flood risk and extent of damage to properties. We used image segmenta...
http://arxiv.org/abs/2306.03050v1
Recent rapid development of sensor technology has allowed massive fine-grained time series (TS) data to be collected and set the foundation for the development of data-driven services and applications. During the process, data sharing is often involved to allow the third-party modelers to perform specific time series d...
http://arxiv.org/abs/2301.01838v1
Point cloud analysis (such as 3D segmentation and detection) is a challenging task, because of not only the irregular geometries of many millions of unordered points, but also the great variations caused by depth, viewpoint, occlusion, etc. Current studies put much focus on the adaption of neural networks to the comple...
http://arxiv.org/abs/2307.14605v1
Delivering meaningful uncertainty estimates is essential for a successful deployment of machine learning models in the clinical practice. A central aspect of uncertainty quantification is the ability of a model to return predictions that are well-aligned with the actual probability of the model being correct, also know...
http://arxiv.org/abs/2303.01099v1
Many applications of text generation such as summarization benefit from accurately controlling the text length. Existing approaches on length-controlled summarization either result in degraded performance or can only control the length approximately. In this work, we present a framework to generate summaries with preci...
http://arxiv.org/abs/2305.05171v1
We introduce a new benchmark, COVID-VTS, for fact-checking multi-modal information involving short-duration videos with COVID19- focused information from both the real world and machine generation. We propose, TwtrDetective, an effective model incorporating cross-media consistency checking to detect token-level malicio...
http://arxiv.org/abs/2302.07919v1
The trimaximal mixing scheme is one of the widely studied neutrino mixing schemes. However, the predicted solar neutrino mixing angle $\theta_{12}$ and the reactor neutrino mixing angle $\theta_{13}$ cannot simultaneously realize their best-fit values. To address this issue, a minimal modification to the trimaximal mix...
http://arxiv.org/abs/2306.13243v2
Adapting the User Interface (UI) of software systems to user requirements and the context of use is challenging. The main difficulty consists of suggesting the right adaptation at the right time in the right place in order to make it valuable for end-users. We believe that recent progress in Machine Learning techniques...
http://arxiv.org/abs/2308.13937v2
Moving Target Defense and Cyber Deception emerged in recent years as two key proactive cyber defense approaches, contrasting with the static nature of the traditional reactive cyber defense. The key insight behind these approaches is to impose an asymmetric disadvantage for the attacker by using deception and randomiza...
http://arxiv.org/abs/2303.00387v2
We present CALLS, a Japanese speech corpus that considers phone calls in a customer center as a new domain of empathetic spoken dialogue. The existing STUDIES corpus covers only empathetic dialogue between a teacher and student in a school. To extend the application range of empathetic dialogue speech synthesis (EDSS),...
http://arxiv.org/abs/2305.13713v1
Vector autoregressions (VARs) have an associated order $p$; conditional on observations at the preceding $p$ time points, the variable at time $t$ is conditionally independent of all the earlier history. Learning the order of the model is therefore vital for its characterisation and subsequent use in forecasting. It is...
http://arxiv.org/abs/2307.05708v1
The latest generation of radio surveys are now producing sky survey images containing many millions of radio sources. In this context it is highly desirable to understand the performance of radio image source finder (SF) software and to identify an approach that optimises source detection capabilities. We have created ...
http://arxiv.org/abs/2304.14355v1
In this study the problem of Federated Learning (FL) is explored under a new perspective by utilizing the Deep Equilibrium (DEQ) models instead of conventional deep learning networks. We claim that incorporating DEQ models into the federated learning framework naturally addresses several open problems in FL, such as th...
http://arxiv.org/abs/2305.18646v1
In this paper, we consider the viscous, incompressible, nonlinear Boussinesq system in two and three spatial dimension. We study the existence and regularity of solutions to the Boussinesq system with nonhomogeneous boundary conditions for which the normal component for the velocity is not necessary equal to zero. We e...
http://arxiv.org/abs/2306.10992v1
We present a systematic study demonstrating the impact of lattice QCD data on the extraction of generalised parton distributions (GPDs). For this purpose, we use a previously developed modelling of GPDs based on machine learning techniques fulfilling the theoretical requirements of polynomiality, a form of positivity c...
http://arxiv.org/abs/2306.01647v1