November 2022 arXiv papers — page 64

L. Rodríguez-García, R. Gómez-Herrero, N. Dresing, D. Lario

Context/Aims: We present a list of 61 solar energetic electron (SEE) events measured by the MESSENGER mission and the radial dependences of the electron peak intensity and the peak-intensity energy spectrum. The analysis comprises the period from 2010 to 2015, when MESSENGER heliocentric distance varied between 0.31 and 0.47 au. We also show the radial depen

Mohamed Abdalmoaty, Alexander Medvedev

An algorithm for continuous time-delay estimation from sampled output data and known input of finite energy is presented. The continuous time-delay modeling allows for the estimation of subsample delays. The proposed estimation algorithm consists of two steps. First, the continuous Laguerre spectrum of the output signal is estimated from discrete-time (sampl

S. Meljanac, S. Mignemi

Long time ago, C.N. Yang proposed a model of noncommutative spacetime that generalized the Snyder model to a curved background. In this paper we review his proposal and the generalizations that have been suggested during the years. In particular, we discuss the most general algebras that contain as subalgebras both de Sitter and Snyder algebras, preserving L

Tolga Ergen, Behnam Neyshabur, Harsh Mehta

Understanding the fundamental mechanism behind the success of transformer networks is still an open problem in the deep learning literature. Although their remarkable performance has been mostly attributed to the self-attention mechanism, the literature still lacks a solid analysis of these networks and interpretation of the functions learned by them. To thi

John M. Ball, Giacomo Canevari, Bianca Stroffolini

We attempt to describe surface defects in smectic A thin films by formulating a free discontinuity problem - that is, a variational problem in which the order parameter is allowed to have jump discontinuities on some (unknown) set. The free energy functional contains an interfacial energy which penalizes dislocations of the smectic layers at the jump. We dis

Denis Kocetkov, Raymond Li, Loubna Ben Allal, Jia Li

Large Language Models (LLMs) play an ever-increasing role in the field of Artificial Intelligence (AI)--not only for natural language processing but also for code understanding and generation. To stimulate open and responsible research on LLMs for code, we introduce The Stack, a 3.1 TB dataset consisting of permissively licensed source code in 30 programming

Rafael Cabral, David Bolin, Håvard Rue

Latent Gaussian models (LGMs) are perhaps the most commonly used class of models in statistical applications. Nevertheless, in areas ranging from longitudinal studies in biostatistics to geostatistics, it is easy to find datasets that contain inherently non-Gaussian features, such as sudden jumps or spikes, that adversely affect the inferences and prediction

Shivani Kumar, Ishani Mondal, Md Shad Akhtar, Tanmoy Chakraborty

Conversations emerge as the primary media for exchanging ideas and conceptions. From the listener's perspective, identifying various affective qualities, such as sarcasm, humour, and emotions, is paramount for comprehending the true connotation of the emitted utterance. However, one of the major hurdles faced in learning these affect dimensions is the presen

Fabian Laakmann

The magnetohydrodynamics (MHD) equations are generally known to be difficult to solve numerically, due to their highly nonlinear structure and the strong coupling between the electromagnetic and hydrodynamic variables, especially for high Reynolds and coupling numbers. In the first part of this work, we present a scalable augmented Lagrangian preconditioner

Supriya Pan, Weiqiang Yang, Eleonora Di Valentino, David F. Mota

In most cosmological models, the equation of state of the dark matter is assumed to be zero, which means that the dark matter is pressure-less or cold. While this hypothesis is based on the abundance of cold dark matter in the universe, however, there is no compelling reason to assume that the equation of state of dark matter is exactly zero. A more general

C. P. Burgess, R. Holman, Greg Kaplanek, Jerome Martin

We compute the rate with which super-Hubble cosmological fluctuations are decohered during inflation, by their gravitational interactions with unobserved shorter-wavelength scalar and tensor modes. We do so using Open Effective Field Theory methods, that remain under control at the late times of observational interest, contrary to perturbative calculations.

Shan Huang

The proposed LUXE experiment (Laser und XFEL Experiment) at DESY Hamburg, using the electron beam from the European XFEL, aims to probe QED in the non-perturbative regime created in collisions between high-intensity laser pulses and high-energy electron or photon beams. This setup also provides a unique opportunity to probe physics beyond the standard model.

Daouda Kabre, André Consiebo

In this paper we study the structure of a class of algebras satisfying a polynomial identity of degree 6. We show, assuming the existence of a non-zero idempotent, that if an algebra satisfies such an identity, it admits a Peirce decomposition related to this idempotent. We studied the algebraic structure and highlighted the connections of the algebras of th

Dylan Radovic, Lucas Kruitwagen, Christian Schroeder de Witt, Ben Caldecott

The energy transition potentially poses an existential risk for major international oil companies (IOCs) if they fail to adapt to low-carbon business models. Projections of energy futures, however, are met with diverging assumptions on its scale and pace, causing disagreement among IOC decision-makers and their stakeholders over what the business model of an

Aditya Ghosh

We look at approximations $ \zeta_X $ of the $\zeta$-function introduced in Gonek's paper (arXiv:0704.3448). We look at how close the approximate zeroes are to the actual zeroes when (i) X is fixed (Section 1)(ii) X varies like $ t/2\pi $ (Section 3.1). We establish a heuristic for estimating these differences, involving values of $ F_X^\star(t) $ and its ne

Elizaveta Zhemchuzhina, Nikolai Filippov, Ivan P. Yamshchikov

This paper studies the limits of language models' statistical learning in the context of Zipf's law. First, we demonstrate that Zipf-law token distribution emerges irrespective of the chosen tokenization. Second, we show that Zipf distribution is characterized by two distinct groups of tokens that differ both in terms of their frequency and their semantics.

Aadesh Desai, Saagar Parikh, Seema Kumari, Shanmuganathan Raman

Point cloud segmentation and classification are some of the primary tasks in 3D computer vision with applications ranging from augmented reality to robotics. However, processing point clouds using deep learning-based algorithms is quite challenging due to the irregular point formats. Voxelization or 3D grid-based representation are different ways of applying

Jag Mohan Singh, Raghavendra Ramachandra

Face manipulation attacks have drawn the attention of biometric researchers because of their vulnerability to Face Recognition Systems (FRS). This paper proposes a novel scheme to generate Composite Face Image Attacks (CFIA) based on facial attributes using Generative Adversarial Networks (GANs). Given the face images corresponding to two unique data subject

Miguel Calvo-Fullana, Jonathan P. How

In this paper, we study the problem of distributed estimation with an emphasis on communication-efficiency. The proposed algorithm is based on a windowed maximum a posteriori (MAP) estimation problem, wherein each agent in the network locally computes a Kalman-like filter estimate that approximates the centralized MAP solution. Information sharing among agen

Andrea Brini

This survey covers recent developments on the geometry and physics of Looijenga pairs, namely pairs $(X,D)$ with $X$ a complex algebraic surface and $D$ a singular anticanonical divisor in it. I will describe a surprising web of correspondences linking together several a priori distant classes of enumerative invariants associated to $(X,D)$, including the lo

Thomas Massoni

Building upon the work of Mitsumatsu and Hozoori, we establish a complete homotopy correspondence between three-dimensional Anosov flows and certain pairs of contact forms that we call Anosov Liouville pairs. We show a similar correspondence between projectively Anosov flows and bi-contact structures, extending the work of Mitsumatsu and Eliashberg-Thurston.

Sajad Darabi, Shayan Fazeli, Jiwei Liu, Alexandre Milesi

Previous works have demonstrated the importance of considering different modalities on molecules, each of which provide a varied granularity of information for downstream property prediction tasks. Our method combines variants of the recent TransformerM architecture with Transformer, GNN, and ResNet backbone architectures. Models are trained on the 2D data,

Carolina Fransson

This paper is concerned with the growth rate of SIR (Susceptible-Infectious-Recovered) epidemics with general infectious period distribution on random intersection graphs. This type of graph is characterized by the presence of cliques (fully connected subgraphs). We study epidemics on random intersection graphs with a mixed Poisson degree distribution and sh

Yu-Zhe Shi, Manjie Xu, John E. Hopcroft, Kun He

We consider concept generalization at a large scale in the diverse and natural visual spectrum. Established computational modes (i.e., rule-based or similarity-based) are primarily studied isolated and focus on confined and abstract problem spaces. In this work, we study these two modes when the problem space scales up, and the $complexity$ of concepts becom

Tomislav Antić, Andrew Keane, Tomislav Capuder

Challenges in the planning and operation of distribution networks caused by the integration of distributed energy resources (DERs) create the need for the development of tools that can be easily used by system operators, industry, and the research society but are also easily upgraded with new functionalities. The full implementation of one such open source t

Thomas Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim

Deployed language models decay over time due to shifting inputs, changing user needs, or emergent world-knowledge gaps. When such problems are identified, we want to make targeted edits while avoiding expensive retraining. However, current model editors, which modify such behaviors of pre-trained models, degrade model performance quickly across multiple, seq

Chris Lu, Timon Willi, Alistair Letcher, Jakob Foerster

Adversarial attacks in reinforcement learning (RL) often assume highly-privileged access to the victim's parameters, environment, or data. Instead, this paper proposes a novel adversarial setting called a Cheap Talk MDP in which an Adversary can merely append deterministic messages to the Victim's observation, resulting in a minimal range of influence. The A

A. I. Breev, A. V. Shapovalov

We study the known coherent states of a quantum harmonic oscillator from the standpoint of the original developed noncommutative integration method for linear partial differential equations. The application of the method is based on the symmetry properties of the Schr\"odinger equation and on the orbit geometry of the coadjoint representation of Lie groups.

Jeremia Geiger, Karolis Martinkus, Oliver Richter, Roger Wattenhofer

Rigid origami has shown potential in large diversity of practical applications. However, current rigid origami crease pattern design mostly relies on known tessellations. This strongly limits the diversity and novelty of patterns that can be created. In this work, we build upon the recently developed principle of three units method to formulate rigid origami

Ningyuan Chen, Ming Hu, Wenhao Li

Commercial AI solutions provide analysts and managers with data-driven business intelligence for a wide range of decisions, such as demand forecasting and pricing. However, human analysts may have their own insights and experiences about the decision-making that is at odds with the algorithmic recommendation. In view of such a conflict, we provide a general

Mahmoud Selim, Amr Alanwar, M. Watheq El-Kharashi, Hazem M. Abbas

Reinforcement learning (RL) algorithms can achieve state-of-the-art performance in decision-making and continuous control tasks. However, applying RL algorithms on safety-critical systems still needs to be well justified due to the exploration nature of many RL algorithms, especially when the model of the robot and the environment are unknown. To address thi

Marilena Crupi, Antonino Ficarra

Let $S=K[x_1,\dots,x_n]$ be a polynomial ring in $n$ variables with coefficients over a field $K$. A $t$-spread lexsegment ideal $I$ of $S$ is a monomial ideal generated by a $t$-spread lexsegment set. We determine all $t$-spread lexsegment ideals with linear resolution by means of Betti splittings. As applications we provide formulas for the Betti numbers o

Ramy A. Zeineldin, Mohamed E. Karar, Franziska Mathis-Ullrich, Oliver Burgert

Reliable and accurate registration of patient-specific brain magnetic resonance imaging (MRI) scans containing pathologies is challenging due to tissue appearance changes. This paper describes our contribution to the Registration of the longitudinal brain MRI task of the Brain Tumor Sequence Registration Challenge 2022 (BraTS-Reg 2022). We developed an enhan

Mohammad Javad Salariseddigh, Vahid Jamali, Uzi Pereg, Holger Boche

Several applications of molecular communications (MC) feature an alarm-prompt behavior for which the prevalent Shannon capacity may not be the appropriate performance metric. The identification capacity as an alternative measure for such systems has been motivated and established in the literature. In this paper, we study deterministic identification (DI) fo

Ofir Gorodetsky

We study the counts of smooth permutations and smooth polynomials over finite fields. For both counts we prove an estimate with an error term that matches the error term found in the integer setting by de Bruijn more than 70 years ago. The main term is the usual Dickman $\rho$ function, but with its argument shifted. We determine the order of magnitude of $\

Bożena Czerny, Michal Zajaček, Mohammad-Hassan Naddaf, Marzena Sniegowska

Since many years we know that dust in the form of the dusty-molecular torus is responsible for the obscuration in active galactic nuclei (AGN) at large viewing angles and thus for the classification of AGN. Recently, we gained some observational and theoretical insight into geometry of the region and the role of the dust in the dynamics of the outflow and fa

Frederic Zagury

The concrete evidence adduced to support the widely held idea that unidentified infrared bands (UIBs) are enhanced in carbon-rich planetary nebulae (PNe) is a remarkable UIB 7.7 {\mu}m versus C/O ratio correlation plot for six PNe, obtained from air-born observations and published in 1986 by M. Cohen and coworkers. However, the space-born data presented by C

Francisco M. Fernández

We show that the effective secular equation proposed several years ago is suitable for estimating the location of the exceptional points of eigenvalue equations. As an illustrative example we choose the well known Mathieu

Zuzana Haniková

Vop\v{e}nka's Alternative Set Theory can be viewed both as an evolution and as a revolution: it is based on his previous experience with nonstandard universes, inspired by Skolem's construction of a nonstandard model of arithmetic, and its inception has been explicitly mentioned as an attempt to axiomatize Robinson's Nonstandard Analysis. Vop\v{e}nka preferr

Konstantin Osetrin, Ilya Kirnos, Altair Filippov

For the quadratic theory of gravity with a scalar field, exact solutions are found for gravitational-wave models in Shapovalov~I~type spacetimes, which do not arise in models of the general theory of relativity. The theory of gravity under consideration can effectively describe the early stages of the dynamics of the universe. Type I Shapovalov spaces are th

Daquan Zhou, Weimin Wang, Hanshu Yan, Weiwei Lv

We present an efficient text-to-video generation framework based on latent diffusion models, termed MagicVideo. MagicVideo can generate smooth video clips that are concordant with the given text descriptions. Due to a novel and efficient 3D U-Net design and modeling video distributions in a low-dimensional space, MagicVideo can synthesize video clips with 25

Vaibhav Kalvakota

In order to show that there exists a relation between the validity of the Weyl entropy and the cosmic censorship hypothesis, we discuss the relation between naked singularities and the gravitational entropy estimator using the Weyl invariant. We look at the examples of Vaidya and Tolman-Bondi spacetimes in asymptotically flat and de Sitter spacetime and look

Zihan Cui, Longxin Pan, Jingchao Fang, Shichao Qi

Quantum Griffiths singularity is characterized by the divergence of the dynamical critical exponent with the activated scaling law and has been widely observed in various two-dimensional superconductors. Recently, the direct activated scaling analysis with the irrelevant correction has been proposed and successfully used to analyze the experimental data of c

Jianhui Zhu

Recent measurements of prompt charm-baryon production at midrapidity in pp and p--Pb collisions show baryon-to-meson yield ratios significantly higher than those in $\rm e^+e^-$ collisions, suggesting that the charm fragmentation is not universal across different collision systems. Thus, more precise and broader measurements of prompt charm-baryon production

Minsoo Kim, Sihwa Lee, Sukjin Hong, Du-Seong Chang

Knowledge distillation (KD) has been a ubiquitous method for model compression to strengthen the capability of a lightweight model with the transferred knowledge from the teacher. In particular, KD has been employed in quantization-aware training (QAT) of Transformer encoders like BERT to improve the accuracy of the student model with the reduced-precision w

Zongyan Yao, Xilin Liu

This paper proposes a deep learning (DL) model for automatic sleep stage classification based on single-channel EEG data. The DL model features a convolutional neural network (CNN) and transformers. The model was designed to run on energy and memory-constrained devices for real-time operation with local processing. The Fpz-Cz EEG signals from a publicly avai

Franz A. Heinsen

We propose a routing algorithm that takes a sequence of vectors and computes a new sequence with specified length and vector size. Each output vector maximizes "bang per bit," the difference between a net benefit to use and net cost to ignore data, by better predicting the input vectors. We describe output vectors as geometric objects, as latent variables th

Iurii Katser, Dmitriy Raspopov, Vyacheslav Kozitsin, Maxim Mezhov

Power transformers are an important component of a nuclear power plant (NPP). Currently, the NPP operates a lot of power transformers with extended service life, which exceeds the designated 25 years. Due to the extension of the service life, the task of monitoring the technical condition of power transformers becomes urgent. An important method for monitori

Qinglong Cao, Yuntian Chen, Xiwen Yao, Junwei Han

Few-shot semantic segmentation task aims at performing segmentation in query images with a few annotated support samples. Currently, few-shot segmentation methods mainly focus on leveraging foreground information without fully utilizing the rich background information, which could result in wrong activation of foreground-like background regions with the inad

Matteo Bordignon, Ethan Simpson Lee

Using an explicit version of Selberg's upper sieve, we obtain explicit upper bounds for the number of $n\leq x$ such that a non-empty set of irreducible polynomials $F_i(n)$ with integer coefficients are simultaneously prime; this set can contain as many polynomials as desired. To demonstrate, we present computations for some irreducible polynomials and obta

Hannes Lagemann, Dennis Willsch, Madita Willsch, Fengping Jin

Constructing a quantum computer requires immensely precise control over a quantum system. A lack of precision is often quantified by gate-error metrics, such as the average infidelity or the diamond distance. However, usually such gate-error metrics are only considered for individual gates, and not the errors that accumulate over consecutive gates. Furthermo

Chuanming Tang, Xiao Wang, Ju Huang, Bo Jiang

Combining the Color and Event cameras (also called Dynamic Vision Sensors, DVS) for robust object tracking is a newly emerging research topic in recent years. Existing color-event tracking framework usually contains multiple scattered modules which may lead to low efficiency and high computational complexity, including feature extraction, fusion, matching, i

Robert E. Tarjan, Uri Zwick

A \emph{resizable array} is an array that can \emph{grow} and \emph{shrink} by the addition or removal of items from its end, or both its ends, while still supporting constant-time \emph{access} to each item stored in the array given its \emph{index}. Since the size of an array, i.e., the number of items in it, varies over time, space-efficient maintenance o

Masaaki Tokieda, Cyril Elouard, Alain Sarlette, Pierre Rouchon

When a composite Lindblad system consists of weakly coupled sub-systems with fast and slow timescales, the description of slow dynamics can be simplified by discarding fast degrees of freedom. This model reduction technique is called adiabatic elimination. While second-order perturbative expansion with respect to the timescale separation has revealed that th

Paul Caucal

The typical transverse momentum $Q_s(t)$ (or "saturation" momentum) acquired by a hard particle propagating through a $\mathcal{N}=4$ SYM plasma increases over time like $t^\gamma$, with an anomalous exponent $\gamma>1/2$ characteristic of super-diffusion. This anomalous exponent is a function of the 't Hooft coupling $\lambda=g^2N_c$. Recently, a method has

Jia Shi

In this paper, we show that if a solution to the Muskat problem in the case of different densities and the same viscosity is sufficiently smooth, then it must be analytic except at the points where a turnover of the fluids happens.

Bruno Magacho, Hugo Saraiva Tavares, Luca Moriconi, Juliana Loureiro

We develop an improved lattice-Boltzmann numerical scheme to solve magnetohydrodynamic (MHD) equations in the regime of low magnetic Reynolds numbers, grounded on a manifestly Galilean covariant modeling of the Navier-Stokes equations. The simulation of the magnetic induction equation within the lattice-Boltzmann approach to MHD has been usually devised alon

Jiawei Du, Yidi Jiang, Vincent Y. F. Tan, Joey Tianyi Zhou

Model-based deep learning has achieved astounding successes due in part to the availability of large-scale real-world data. However, processing such massive amounts of data comes at a considerable cost in terms of computations, storage, training and the search for good neural architectures. Dataset distillation has thus recently come to the fore. This paradi

Nawaf Bou-Rabee, Milo Marsden

A randomized time integrator is suggested for unadjusted Hamiltonian Monte Carlo (uHMC) which involves a very minor modification to the usual Verlet time integrator, and hence, is easy to implement. For target distributions of the form $\mu(dx) \propto e^{-U(x)} dx$ where $U: \mathbb{R}^d \to \mathbb{R}_{\ge 0}$ is $K$-strongly convex but only $L$-gradient L

M. Moalic, M. Krawczyk, M. Zelent

Magnonic crystals are structures with periodically varied magnetic properties that are used to control collective spin-wave excitations. With micromagnetic simulations, we study spin-wave spectra in a 2D antidot lattice based on a multilayered thin film with perpendicular magnetic anisotropy (PMA). We show that the modification of the PMA near the antidot ed

Giang Hoang, Tuan Nguyen Dinh, Tung Cao Hoang, Son Le Duy

The lack of large-scale datasets has been impeding the advance of deep learning approaches to the problem of F-formation detection. Moreover, most research works on this problem rely on input sensor signals of object location and orientation rather than image signals. To address this, we develop a new, large-scale dataset of simulated images for F-formation

Martin Bullinger, Warut Suksompong

We introduce a class of strategic games in which agents are assigned to nodes of a topology graph and the utility of an agent depends on both the agent's inherent utilities for other agents as well as her distance from these agents on the topology graph. This model of topological distance games (TDGs) offers an appealing combination of important aspects of s

Rodrigo Mira, Buye Xu, Jacob Donley, Anurag Kumar

Audio-visual speech enhancement aims to extract clean speech from a noisy environment by leveraging not only the audio itself but also the target speaker's lip movements. This approach has been shown to yield improvements over audio-only speech enhancement, particularly for the removal of interfering speech. Despite recent advances in speech synthesis, most

Andrey A. Kuznetsov, Sofia S. Kantorovich

Nowadays, magnetoresponsive soft materials, based not simply on magnetic nanoparticles, but rather on multiple components with distinct sizes and magnetic properties, both in liquid and polymeric carriers, are becoming more and more wide-spread due to their unique and versatile macroscopic response to an applied magnetic field. The variability of the latter

Yangning Li, Jiaoyan Chen, Yinghui Li, Tianyu Yu

Contextual synonym knowledge is crucial for those similarity-oriented tasks whose core challenge lies in capturing semantic similarity between entities in their contexts, such as entity linking and entity matching. However, most Pre-trained Language Models (PLMs) lack synonym knowledge due to inherent limitations of their pre-training objectives such as mask

Davide Alessandro Coccomini, Giorgos Kordopatis Zilos, Giuseppe Amato, Roberto Caldelli

In this paper, we introduce MINTIME, a video deepfake detection approach that captures spatial and temporal anomalies and handles instances of multiple people in the same video and variations in face sizes. Previous approaches disregard such information either by using simple a-posteriori aggregation schemes, i.e., average or max operation, or using only one

Zeyu Shangguan, Bocheng Hu, Guohua Dai, Yuyu Liu

Deep learning-based object detection has demonstrated a significant presence in the practical applications of artificial intelligence. However, objects such as fire and smoke, pose challenges to object detection because of their non-solid and various shapes, and consequently difficult to truly meet requirements in practical fire prevention and control. In th

Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang

Unsupervised depth completion aims to recover dense depth from the sparse one without using the ground-truth annotation. Although depth measurement obtained from LiDAR is usually sparse, it contains valid and real distance information, i.e., scale-consistent absolute depth values. Meanwhile, scale-agnostic counterparts seek to estimate relative depth and hav

Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo

Deep learning models have shown great promise in various healthcare applications. However, most models are developed and validated on small-scale datasets, as collecting high-quality (gold-standard) labels for health applications is often costly and time-consuming. As a result, these models may suffer from overfitting and not generalize well to unseen data.

Santiago Achig-Andrango

Given a lattice polytope $Q\subset \mathbb{R}^n$, we can consider the cone $\sigma=C(Q)=\{\lambda(q,1)\in \mathbb{R}^{n+1}|\lambda \in \mathbb{R}_{\geq0}, q\in Q\} \subset \mathbb{R}^{n+1}$, and the affine toric variety $Y_{\sigma}$ associated to $\sigma$. Altmann showed that the versal deformation space of $Y_\sigma$ can be described by the Minkowski decomp

Zhongyu Fang, Aoyun He, Qihui Yu, Baopeng Gao

Multimodal emotion analysis performed better in emotion recognition depending on more comprehensive emotional clues and multimodal emotion dataset. In this paper, we developed a large multimodal emotion dataset, named "HED" dataset, to facilitate the emotion recognition task, and accordingly propose a multimodal emotion recognition method. To promote recogni

Dohyun Kim, Hansol Park, Woojoo Shim

We introduce a higher simplicial generalization of the linear consensus model which shares several common features. The well-known linear consensus model is a gradient flow with a sum of squares of distances between each pair of points. Our newly suggested model is also represented as a gradient flow equipped with total $n$-dimensional volume functional cons

Jie Ruan, Yue Wu, Xiaojun Wan, Yuesheng Zhu

Sarcasm generation has been investigated in previous studies by considering it as a text-to-text generation problem, i.e., generating a sarcastic sentence for an input sentence. In this paper, we study a new problem of cross-modal sarcasm generation (CMSG), i.e., generating a sarcastic description for a given image. CMSG is challenging as models need to sati

Taiqiang Wu, Xingyu Bai, Weigang Guo, Weijie Liu

Zero-shot entity retrieval, aiming to link mentions to candidate entities under the zero-shot setting, is vital for many tasks in Natural Language Processing. Most existing methods represent mentions/entities via the sentence embeddings of corresponding context from the Pre-trained Language Model. However, we argue that such coarse-grained sentence embedding

Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao

In recent years, Graph Neural Networks (GNNs) have been popular in graph representation learning which assumes the homophily property, i.e., the connected nodes have the same label or have similar features. However, they may fail to generalize into the heterophilous graphs which in the low/medium level of homophily. Existing methods tend to address this prob

Hanchen Wang, Rundong Yuan, Yongjian Zhou, Yuelin Zhang

We report on coherent propagation of antiferromagnetic (AFM) spin waves over a long distance ($\sim$10 $\mu$m) at room temperature in a canted AFM $\alpha$-Fe$_2$O$_3$ with the Dzyaloshinskii-Moriya interaction (DMI). Unprecedented high group velocities (up to 22.5 km/s) are characterized by microwave transmission using all-electrical spin wave spectroscopy.

Ekaterina O. Pozdeeva, Sergey Yu. Vernov

We propose a one-parametric extension of the Starobinsky $R+R^2$ model by adding the $(R+m^2\beta^2)^{3/2}$ term. The parameter $m$ is the inflaton mass, which is determined in the same way as in the Starobinsky model, and $\beta$ is a dimensionless constant. Using the Einstein frame and the scalar field potential, we get the inflationary parameters of the m

Etienne Russeil, Emille E. O. Ishida, Roman Le Montagner, Julien Peloton

We present the Active Galactic Nuclei (AGN) classifier as currently implemented within the Fink broker. Features were built upon summary statistics of available photometric points, as well as color estimation enabled by symbolic regression. The learning stage includes an active learning loop, used to build an optimized training sample from labels reported in

Zengzhi Wang, Rui Xia, Jianfei Yu

Aspect-Based Sentiment Analysis (ABSA) aims to provide fine-grained aspect-level sentiment information. There are many ABSA tasks, and the current dominant paradigm is to train task-specific models for each task. However, application scenarios of ABSA tasks are often diverse. This solution usually requires a large amount of labeled data from each task to per

Fangzhou Jin, Enlin Yang

Given a motivic spectrum $K$ over a smooth proper scheme which is dualizable over an open subscheme, we define its quadratic Artin conductor under some assumptions, and prove a formula relating the quadratic Euler characteristic of $K$, the rank of $K$ and the quadratic Artin conductor. As a consequence, we obtain a quadratic refinement of the classical Grot

Qunliang Xing, Mai Xu, Xin Deng, Yichen Guo

Image defocus is inherent in the physics of image formation caused by the optical aberration of lenses, providing plentiful information on image quality. Unfortunately, existing quality enhancement approaches for compressed images neglect the inherent characteristic of defocus, resulting in inferior performance. This paper finds that in compressed images, si

Arpita Sharma, Ankush Mukherjee, Alexander Warren, Shuo Jin

Metal electrodeposition in batteries is fundamentally unstable and affected by different instabilities depending on operating conditions and chemical composition. Particularly at high charging rates, a hydrodynamic instability called electroconvection sets in that aggravates the situation by creating non-uniform ion flux and preferential deposition at the el

Reza Abdolmaleki, Ali Akbar Yazdan Pour

Let $S=\mathbb{K}[x_1,\ldots, x_n]$ be the polynomial ring over a field $\mathbb{K}$ and $\mathfrak{m}= (x_1, \ldots, x_n)$ be the irredundant maximal ideal of $S$. For an ideal $I \subset S$, let $\mathrm{sat}(I)$ be the minimum number $k$ for which $I \colon \mathfrak{m}^k = I \colon \mathfrak{m}^{k+1}$. In this paper, we compute the saturation number of i

Jinyu Miao, Haosong Yue, Zhong Liu, Xingming Wu

Local feature provides compact and invariant image representation for various visual tasks. Current deep learning-based local feature algorithms always utilize convolution neural network (CNN) architecture with limited receptive field. Besides, even with high-performance GPU devices, the computational efficiency of local features cannot be satisfactory. In t

Iacopo Carusotto

In this Chapter, we give a brief review of the state of the art of theoretical and experimental studies of quantum fluids of light. Such systems consist of ensembles of photons that acquire a finite mass from spatial confinement or diffraction and finite binary interactions from the optical nonlinearity of the optical medium. The peculiar properties of these

Basilis Mamalis, Marios Perlitis

The simplex algorithm has been successfully used for many years in solving linear programming (LP) problems. Due to the intensive computations required (especially for the solution of large LP problems), parallel approaches have also extensively been studied. The computational power provided by the modern GPUs as well as the rapid development of multicore CP

Ji-Hwan Jung, Suh-Ryung Kim, Hyesun Yoon

For an integer $k \ge 2$, let $A$ be a Boolean block matrix with blocks $A_{ij}$ for $1 \le i,j \le k$ such that $A_{ii}$ is a zero matrix and $A_{ij}+A_{ji}^T$ is a matrix with all elements $1$ but not both corresponding elements of $A_{ij}$ and $A_{ji}^T$ equal to $1$ for $i \neq j$. Jung~{\em et al.} [Competition periods of multipartite tournaments. {\it

Ivan Bartulović

In this paper, we first endow the set of ribbon string links (up to isotopy) with a structure of a cyclic and of a cocyclic set. Next, we relate these (co)cyclic sets with those associated with the coend of a ribbon category. The relationship is given by the universal quantum invariants \`a la Reshetikhin-Turaev.

Xiaoxi Wei, A. Aldo Faisal

Deep learning has been successful in BCI decoding. However, it is very data-hungry and requires pooling data from multiple sources. EEG data from various sources decrease the decoding performance due to negative transfer. Recently, transfer learning for EEG decoding has been suggested as a remedy and become subject to recent BCI competitions (e.g. BEETL), bu

Hongchao Li, Xie-Hang Yu, Masaya Nakagawa, Masahito Ueda

Yang and Lee investigated phase transitions in terms of zeros of partition functions, namely, Yang-Lee zeros [Phys. Rev. 87, 404 (1952); Phys. Rev. 87, 410 (1952)]. We show that the essential singularity in the superconducting gap is directly related to the number of roots of the partition function of a BCS superconductor. Those zeros are found to be distrib

Shaobo Zhang, Wenwu Tian, Mengfei Zhang, Hui Zhu

The youngest Galactic supernova remnant G1.9+0.3 shows a discrete feature between its radio and X-ray morphologies. The observed radio morphology features a single maximum in the north, while the X-ray observation shows two opposite 'ears' on the east and west sides. Using 3D magneto hydrodynamical simulations, we investigate the formation of the discrete fe

Ömer Sen, Florian Schmidtke, Federico Carere, Francesca Santori

While the increasing penetration of information and communication technology into distribution grid brings numerous benefits, it also opens up a new threat landscape, particularly through cyberattacks. To provide a basis for countermeasures against such threats, this paper addresses the investigation of the impact and manifestations of cyberattacks on smart

Peng Qi, Yuyan Bu, Juan Cao, Wei Ji

Short video platforms have become an important channel for news sharing, but also a new breeding ground for fake news. To mitigate this problem, research of fake news video detection has recently received a lot of attention. Existing works face two roadblocks: the scarcity of comprehensive and largescale datasets and insufficient utilization of multimodal in

Sanya Sinha, Nilay Gupta

Skin cancer is a fatal manifestation of cancer. Unrepaired deoxyribo-nucleic acid (DNA) in skin cells, causes genetic defects in the skin and leads to skin cancer. To deal with lethal mortality rates coupled with skyrocketing costs of medical treatment, early diagnosis is mandatory. To tackle these challenges, researchers have developed a variety of rapid de

Ömer Sen, Chijioke Eze, Andreas Ulbig, Antonello Monti

While digitization of distribution grids through information and communications technology brings numerous benefits, it also increases the grid's vulnerability to serious cyber attacks. Unlike conventional systems, attacks on many industrial control systems such as power grids often occur in multiple stages, with the attacker taking several steps at once to

Fucai Li, Shuxing Zhang

In this paper, we investigate the combined non-equilibrium diffusion and low Mach number limits of the compressible Navier-Stokes-Fourier-P1 (NSF-P1) model with general initial data, which arises in the radiation hydrodynamics. Compared to the classical compressible Navier-Stokes-Fourier system, the NSF-P1 model has an asymmetric singular structure caused by

Xiaohui Bei, Nick Gravin, Pinyan Lu, Zhihao Gavin Tang

Motivated by practical concerns in the online advertising industry, we study a bidder subset selection problem in single-item auctions. In this problem, a large pool of candidate bidders have independent values sampled from known prior distributions. The seller needs to pick a subset of bidders and run a given auction format on the selected subset to maximiz

Jiading Liu, Lei Shi

Previous analysis of regularized functional linear regression in a reproducing kernel Hilbert space (RKHS) typically requires the target function to be contained in this kernel space. This paper studies the convergence performance of divide-and-conquer estimators in the scenario that the target function does not necessarily reside in the underlying RKHS. As

Junho Cho, Kyuewang Lee, Jin Young Choi

Fonts can convey profound meanings of words in various forms of glyphs. Without typography knowledge, manually selecting an appropriate font or designing a new font is a tedious and painful task. To allow users to explore vast font styles and create new font styles, font retrieval and font style transfer methods have been proposed. These tasks increase the n

Karan Uppal, Jaeah Kim, Shashank Singh

Eye-tracking has potential to provide rich behavioral data about human cognition in ecologically valid environments. However, analyzing this rich data is often challenging. Most automated analyses are specific to simplistic artificial visual stimuli with well-separated, static regions of interest, while most analyses in the context of complex visual stimuli,