October 2022 arXiv papers — page 51

Noga Alon, Michael Krivelevich, Wojciech Samotij

We prove that for every non-trivial hereditary family of graphs ${\cal P}$ and for every fixed $p \in (0,1)$, the maximum possible number of edges in a subgraph of the random graph $G(n,p)$ which belongs to ${\cal P}$ is, with high probability, $$ \left(1-\frac{1}{k-1}+o(1)\right)p{n \choose 2}, $$ where $k$ is the minimum chromatic number of a graph that do

Gil Kalai, Yosef Rinott, Tomer Shoham

In October 2019, Nature published a paper describing an experiment that took place at Google. The paper claims to demonstrate quantum (computational) supremacy on a 53-qubit quantum computer. Since September 2019 we have been involved in a long-term project to study various statistical aspects of the Google experiment. We have been trying to gather the relev

Wanyi Zhuang, Qi Chu, Zhentao Tan, Qiankun Liu

Intra-frame inconsistency has been proved to be effective for the generalization of face forgery detection. However, learning to focus on these inconsistency requires extra pixel-level forged location annotations. Acquiring such annotations is non-trivial. Some existing methods generate large-scale synthesized data with location annotations, which is only co

Gheorghe Ivan

The main purpose of this paper is to present a general method for the controllability of the stability of a system of fractional-order differential equations around its equilibrium states. This method is applied to analyze and control the fractional stability of the fractional 2-dimensional fractional Toda lattice with one linear control.

Daniel Azses, David F. Mross, Eran Sela

Symmetry-resolved entanglement is a useful tool for characterizing symmetry-protected topological states. In two dimensions, their entanglement spectra are described by conformal field theories but the symmetry resolution is largely unexplored. However, addressing this problem numerically requires system sizes beyond the reach of exact diagonalization. Here,

D. I. Borisov

We consider a boundary value problem for a general second order linear equation in a perforated domain. The perforation is made by small cavities, a minimal distance between the cavities is also small. We impose minimal natural geometric conditions on the shapes of the cavities and no conditions on their distribution in the domain. On the boundaries of the c

Xin Wu, Hao Zhao, Shunkai Li, Yingdian Cao

Visual re-localization aims to recover camera poses in a known environment, which is vital for applications like robotics or augmented reality. Feed-forward absolute camera pose regression methods directly output poses by a network, but suffer from low accuracy. Meanwhile, scene coordinate based methods are accurate, but need iterative RANSAC post-processing

Alexander Kovalev, Ilia Mikheev, Alexei Ossadtchi

The access to activity of subcortical structures offers unique opportunity for building intention dependent brain-computer interfaces, renders abundant options for exploring a broad range of cognitive phenomena in the realm of affective neuroscience including complex decision making processes and the eternal free-will dilemma and facilitates diagnostics of a

Arpit Bhardwaj, Phanish Suryanarayana

We study the electronic response of Janus transition metal dihalide (TMH) nanotubes to mechanical deformations using Kohn-Sham density functional theory. Specifically, considering twelve armchair and zigzag Janus TMH nanotubes that are expected to be stable from the phonon analysis of flat monolayer counterparts, we first compute their equilibrium diameters

Rozenn Dahyot

We propose to directly compute classification estimates by learning features encoded with their class scores using PCA. Our resulting model has a encoder-decoder structure suitable for supervised learning, it is computationally efficient and performs well for classification on several datasets.

Hasan Al-Zoubi, Ala'a Al-Kateeb

In this paper, we introduce a generalization of Balancing and Balancing-Lucas numbers. We describe some of their properties also we give the related matrix representation and divisibility properties.

Vincent Chambouleyron, Olivier Fauvarque, Cédric Plantet, Jean-François Sauvage

To reach the full potential of the new generation of ground based telescopes, an extremely fine adjustment of the phase is required. Wavefront control and correction before detection has therefore become one of the cornerstones of instruments to achieve targeted performance, especially for high-contrast imaging. A crucial feature of accurate wavefront contro

Jiamin Hou, Azadeh Moradinezhad Dizgah, ChangHoon Hahn, Elena Massara

Extracting the non-Gaussian information encoded in the higher-order clustering statistics of the large-scale structure is key to fully realizing the potential of upcoming galaxy surveys. We investigate the information content of the redshift-space {\it weighted skew spectra} of biased tracers as efficient estimators for 3-point clustering statistics. The ske

Shi-Mei Ma, Hao Qi, Jean Yeh, Yeong-Nan Yeh

Motivated by the work of Visontai and Dey-Sivasubramanian on the gamma-positivity of some polynomials, we find the commutative property of a pair of Eulerian operators. As an application, we show the bi-gamma-positivity of the descent polynomials on permutations of the multiset $\{1^{a_1},2^{a_2},\ldots,n^{a_n}\}$, where $0\leqslant a_i\leqslant 2$. Therefor

Curial Gallart

The purpose of this paper is to present a general method for forcing on $\omega_2$ and $\omega_3$ with finite conditions, while preserving all cardinals and some fragments of $\mathrm{GCH}$. This method is based on the technique of forcing with finite symmetric systems of elementary submodels, and improves earlier versions of this forcing by including models

Chunhui Wang, Chang Zeng, Jun Chen, Xing He

Entertainment-oriented singing voice synthesis (SVS) requires a vocoder to generate high-fidelity (e.g. 48kHz) audio. However, most text-to-speech (TTS) vocoders cannot reconstruct the waveform well in this scenario. In this paper, we propose HiFi-WaveGAN to synthesize the 48kHz high-quality singing voices in real-time. Specifically, it consists of an Extend

Kha Pham, Hung Le, Man Ngo, Truyen Tran

The capacity to achieve out-of-distribution (OOD) generalization is a hallmark of human intelligence and yet remains out of reach for machines. This remarkable capability has been attributed to our abilities to make conceptual abstraction and analogy, and to a mechanism known as indirection, which binds two representations and uses one representation to refe

J. Łoś, A. Drozd-Rzoska, S. J. Rzoska

The report presents pressure-related broadband dielectric spectroscopy (BDS) studies in liquid crystalline octyloxycyanbiphenyl and its nanocolloid with BaTiO3 nanoparticles, focused on the low-frequency ionic domain and the impact of pretransitional fluctuations. Hence basic exogenic (pressure) and endogenic (nanoparticles) impacts on dielectric properties

G. Revati, Syed Shadab, K. Sonam, S. R. Wagh

The dynamic mode decomposition (DMD) technique extracts the dominant modes characterizing the innate dynamical behavior of the system within the measurement data. For appropriate identification of dominant modes from the measurement data, the DMD algorithm necessitates ensuring the quality of the input measurement data sequences. On that account, for validat

Lin Zhou, Jun Diao, Lin Bai

We revisit $M$-ary classification of Gutman (TIT 1989), where one is tasked to determine whether a testing sequence is generated with the same distribution as one of the $M$ training sequences or not. Our main result is a two-phase test, its theoretical analysis and its optimality guarantee. Specifically, our two-phase test is a special case of a sequential

Jiangfeng Zhou, Zebang Ouyang, Junhui Liao, Zhuo Liang

ALETHEIA is a newly established dark matter direct detection project that aims at hunting for low-mass WIMPs. TPB is widely implemented in liquid helium and argon experiments to shift VUV photons to visible light. We first report that we have successfully coated $\sim 3 ~\mu$m TPB on the inner walls of a 10-cm cylindrical PTFE detector; we split the coating

Shenyang Tan, Wenjun Liu

In this paper, we study the higher-order regularity of solutions to the large scale moist atmosphere system through the way of $p$-strong solutions. On the basis of the well-posedness results of strong solutions, we first improve the regularity of solutions in the vertical direction, and then improve the regularity in the horizontal direction. Thus we obtain

Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao

Amodal perception requires inferring the full shape of an object that is partially occluded. This task is particularly challenging on two levels: (1) it requires more information than what is contained in the instant retina or imaging sensor, (2) it is difficult to obtain enough well-annotated amodal labels for supervision. To this end, this paper develops a

Ze-Hao Huang, Peng He, Li-Jun Lang, Shi-Liang Zhu

We propose a general quantum circuit based on the swap test for measuring the quantity $\langle \psi_1 | A | \psi_2 \rangle$ of an arbitrary operator $A$ with respect to two quantum states $|\psi_{1,2}\rangle$. This quantity is frequently encountered in many fields of physics, and we dub it the generalized expectation as a two-state generalization of the con

Qing Wu, Xin Li, Hongjiang Wei, Jingyi Yu

Neural Radiance Field (NeRF) has widely received attention in Sparse-View Computed Tomography (SVCT) reconstruction tasks as a self-supervised deep learning framework. NeRF-based SVCT methods represent the desired CT image as a continuous function of spatial coordinates and train a Multi-Layer Perceptron (MLP) to learn the function by minimizing loss on the

Takeshi Araki, Kento Asai, Hidetoshi Otono, Takashi Shimomura

FASER is one of the promising experiments which search for long-lived particles beyond the Standard Model. In this paper, we consider charged lepton flavor violation (CLFV) via a light and weakly interacting boson and discuss the detectability by FASER. We focus on four types of CLFV interactions, i.e., the scalar-, pseudoscalar-, vector-, and dipole-type in

Brian Tyrrell

A field $K$ in a ring language $\mathcal{L}$ is finitely undecidable if $\mbox{Cons}(\Sigma)$ is undecidable for every nonempty finite $\Sigma \subseteq \mbox{Th}(K; \mathcal{L})$. We extend a construction of Ziegler and (among other results) use a first-order classification of Anscombe and Jahnke to prove every NIP henselian nontrivially valued field is fin

Huiling Zhong, Fanrong Xu, Qiaoyi Wen, Yu Gu

In this work, we carry out a global fitting for the two-body weak decays of antitriplet charmed baryons in both SU(3) respected and broken scenarios incorporating all the available data up to date. In the SU(3) irreducible representation approach (IRA), more amplitudes for irreducible representation terms are taken into account and the ranges for their coeff

Elijah Rippeth, Matt Post

Additive interventions are a recently-proposed mechanism for controlling target-side attributes in neural machine translation. In contrast to tag-based approaches which manipulate the raw source sequence, interventions work by directly modulating the encoder representation of all tokens in the sequence. We examine the role of additive interventions in a larg

Jia-Bao Liu, Ya-Qian Zheng, Xin-Bei Peng

The Sombor indices, a new category of degree-based topological molecular descriptors, have been widely investigated due to their excellent chemical applicability. This paper aims to establish Sombor indices distributions in random polygonal chain networks and to achieve expressions of the expected values and variances. The expected values and variances of th

Jarah Evslin, Hui Liu

We scatter a meson off of a scalar kink in quantum field theory, at leading order in perturbation theory. We calculate the full quantum state, at leading order, at all times and also check that the reflection and transmission coefficients agree with those which would be obtained in relativistic quantum mechanics.

Mei Wu, Ruochen Shi, Ruishi Qi, Yuehui Li

Phonons are the primary heat carriers in non-metallic solids. In compositionally heterogeneous materials, the thermal properties are believed to be mainly governed by the disrupted phonon transport due to mass disorder and strain fluctuations, while the effects of compositional fluctuation induced local phonon states are usually ignored. Here, by scanning tr

Guo-Jun Qi, Mubarak Shah

In this paper, we review adversarial pretraining of self-supervised deep networks including both convolutional neural networks and vision transformers. Unlike the adversarial training with access to labeled examples, adversarial pretraining is complicated as it only has access to unlabeled examples. To incorporate adversaries into pretraining models on eithe

Zi Wang, Haoming Fang, Chen Qian, Boxuan Shi

Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from prolonged scan time. To alleviate this limitation, advanced fast MRI technology attracts extensive research interests. Recent deep learning has shown its great potential in improving image quality and reconstruction speed. Faithful coil sensitivity estimation is vital for MRI

J. Fransson

The current understanding of chirality suggests the existence of a connection between structure and angular momentum, including spin. This is particularly emphasised in the chiral induced spin selectivity effect, where chiral structures act as spin filters. However, the recent discovery of chiral phonons have demonstrated that phonons too may carry angular m

A. V. Razumov

The central object of the quantum algebraic approach to the study of quantum integrable models is the universal $R$-matrix, which is an element of a completed tensor product of two copies of quantum algebra. Various integrability objects are constructed by choosing representations for the factors of this tensor product. There are two approaches to constructi

Bin Ji, Shasha Li, Hao Xu, Jie Yu

Span-based joint extraction simultaneously conducts named entity recognition (NER) and relation extraction (RE) in text span form. However, since previous span-based models rely on span-level classifications, they cannot benefit from token-level label information, which has been proven advantageous for the task. In this paper, we propose a Sequence Tagging a

Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball

Building generally capable agents is a grand challenge for deep reinforcement learning (RL). To approach this challenge practically, we outline two key desiderata: 1) to facilitate generalization, exploration should be task agnostic; 2) to facilitate scalability, exploration policies should collect large quantities of data without costly centralized retraini

Hao Meng, Xiuqiang Wu, Yajie Ren, Jiansheng Wu

Based on the Bogoliubov-de Gennes equations, we investigate the transport of the Josephson current in a S/$f_L$-F$_1$-$f_C$-F$_2$-$f_R$/S junction, where S and F$_{1,2}$ are superconductors and ferromagnets, and $f_{L, C, R}$ are the left, central, and right spin-active interfaces. These interfaces have noncollinear magnetizations, and the azimuthal angles o

Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo

Magnetic flux emergence from the solar interior to the atmosphere is believed to be a key process of formation of solar active regions and driving solar eruptions. Due to the limited capability of observation, the flux emergence process is commonly studied using numerical simulations. In this paper, we developed a numerical model to simulate the emergence of

Junzhe Cao, Sha Liu, Chengwen Zhong, Congshan Zhuo

In this study, the multiple solutions of Nonlinear Coupled Constitutive Relation (NCCR) model are firstly observed and a way for identifying the physical solution is proposed. The NCCR model proposed by Myong is constructed from the generalized hydrodynamic equations of Eu, and aims to describe rarefied flows. The NCCR model is a complicated nonlinear system

Hefu Ye, Haijia Wu, Kai Zhao, Yongduan Song

It is nontrivial to achieve exponential stability even for time-invariant nonlinear systems with matched uncertainties and persistent excitation (PE) condition. In this paper, without the need for PE condition, we address the problem of global exponential stabilization of strict-feedback systems with mismatched uncertainties and unknown yet time-varying cont

Hongbin Ye, Ningyu Zhang, Hui Chen, Huajun Chen

Generative Knowledge Graph Construction (KGC) refers to those methods that leverage the sequence-to-sequence framework for building knowledge graphs, which is flexible and can be adapted to widespread tasks. In this study, we summarize the recent compelling progress in generative knowledge graph construction. We present the advantages and weaknesses of each

Stefan Aimet, Hadrien Chevalier, M. S. Kim

Over the past century, a large community within theoretical physics has been seeking a unified framework for quantum gravity. Yet, to date, there is still no experimental evidence of any non-classical features of gravity. While traditional experimental proposals would usually require immensely challenging Planck scale experiments, recent table-top protocols

Hefu Ye, Yongduan Song, Frank L. Lewis

Prescribed-time (PT) control, originated from \textit{Song et al.}, has gained increasing attention among control community. The salient feature of PT control lies in its ability to achieve system stability within a finite settling time user-assignable in advance irrespective of initial conditions. It is such a unique feature that has enticed many follow-up

Xinhui Li, Yukun Wang, Yunguang Han, Shi-Ning Zhu

Self-testing, which refers to device independent characterization of the state and the measurement, enables the security of quantum information processing task certified independently of the operation performed inside the devices. Quantum states lie in the core of self-testing as key resources. However, for the different entangled states, usually different m

Lia F. Sartori, Christophe Lovis, Jean-Baptiste Delisle, Monika Lendl

Context. Planets around stars in the solar neighbourhood will be prime targets for characterisation with upcoming large space- and ground-based facilities. Since large-scale exoplanet searches will not be feasible with such telescopes, it is crucial to use currently available data and instruments to find possible target planets before next generation facilit

Xianqi Tong, Gao Xianlong, Su-peng Kou

We investigate the transition from PT-symmetry to PT-symmetry breaking and vice versa in the non-Hermitian Landau-Zener (LZ) models. The energy is generally complex, so the relaxation rate of the system is set by the absolute value of the gap. To illustrate the dynamics of phase transitions, the relative population is introduced to calculate the defect densi

Charles M. Telesco, Frank Varosi, Christopher Wright, Bruce T. Draine

We present the first mid-IR detection of the linear polarization toward the star CygOB2-12, a luminous blue hypergiant that, with Av of ~10 mag of foreground extinction, is a benchmark in the study of the properties of dust in the diffuse interstellar medium. The 8-13 micrometer spectropolarimetry, obtained with the CanariCam multi-mode camera at the Gran Te

Sonia Lopez Alarcon, Cory Merkel, Martin Hoffnagle, Sabrina Ly

Binary Neural Networks are a promising technique for implementing efficient deep models with reduced storage and computational requirements. The training of these is however, still a compute-intensive problem that grows drastically with the layer size and data input. At the core of this calculation is the linear regression problem. The Harrow-Hassidim-Lloyd

Hefu Ye, Yongduan Song

It is an interesting open problem to achieve adaptive prescribed-time control for strict-feedback systems with unknown and fast or even abrupt time-varying parameters. In this paper we present a solution with the aid of several design and analysis innovations. First, by using a spatiotemporal transformation, we convert the original system operational over fi

Ömer Sümer, Fabio Hellmann, Alexander Hustinx, Tzung-Chien Hsieh

Computer vision-based methods have valuable use cases in precision medicine, and recognizing facial phenotypes of genetic disorders is one of them. Many genetic disorders are known to affect faces' visual appearance and geometry. Automated classification and similarity retrieval aid physicians in decision-making to diagnose possible genetic conditions as ear

Yassine Larbaoui

This paper presents new six solutions for sixth degree polynomial equation in general forms basing on new theorems, where the possibility to calculate the six roots of any sixth degree equation nearly simultaneously. The proposed roots for sixth degree polynomials in this paper are structured basing on new proposed solutions for quartic polynomial equations,

Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby

Learning functions with high-dimensional outputs is critical in many applications, such as physical simulation and engineering design. However, collecting training examples for these applications is often costly, e.g. by running numerical solvers. The recent work (Li et al., 2022) proposes the first multi-fidelity active learning approach for high-dimensiona

Youssef Moawad, Wim Vanderbauwhede, René Steijl

For efficient hardware-accelerated simulations of quantum circuits, we can define hardware-specific quantum-circuit transformations. We use a functional programming approach to create a quantum-circuit analysis and transformation method implemented in Haskell. This tool forms a key part of our larger quantum-computing simulation toolchain. As an example of h

Yao Wei, Haoxiang Wang, Mingze Sun, Jiawang Liu

Facial action unit (AU) recognition is essential to facial expression analysis. Since there are highly positive or negative correlations between AUs, some existing AU recognition works have focused on modeling AU relations. However, previous relationship-based approaches typically embed predefined rules into their models and ignore the impact of various AU r

Der-Chen Chang, Shu-Cheng Chang, Yingbo Han, Chien Lin

In this paper, we show that the uniform L^4-bound of the transverse Ricci curvature along the Sasaki-Ricci flow on a compact quasi-regular transverse Fano Sasakian (2n+1)-manifold M. When M is dimension up to seven and the space of leaves of the characteristic foliation is well-formed, we first show that any solution of the Sasaki-Ricci flow converges in the

Shibani Hamsa, Ismail Shahin, Youssef Iraqi, Ernesto Damiani

Speech signals are subjected to more acoustic interference and emotional factors than other signals. Noisy emotion-riddled speech data is a challenge for real-time speech processing applications. It is essential to find an effective way to segregate the dominant signal from other external influences. An ideal system should have the capacity to accurately rec

Nikita Kramarev, Andrey Yudin

We consider the gas dynamics in an accreting binary system of degenerate stars within the framework of the Newtonian approximation. In such a system, the accretion stream can impact the surface of a white dwarf (WD) or neutron star (NS) as a result of the very compact orbit. This causes a loss of angular momentumfrom the orbit and spin-up of the accretor. We

Raphael Steiner

In 2006, Noga Alon raised the following open problem: Does there exist an absolute constant $c>0$ such that every $2n$-vertex digraph with minimum out-degree at least $s$ contains an $n$-vertex subdigraph with minimum out-degree at least $\frac{s}{2}-c$ ? In this note, we answer this natural question in the negative, by showing that for arbitrarily large val

Marc Barthelemy

Despite the recently exhibited importance of higher-order interactions for various processes, few flexible (null) models are available. In particular, most studies on hypergraphs focus on a small set of theoretical models. Here, we introduce a class of models for random hypergraphs which displays a similar level of flexibility of complex network models and w

Ningning Jia, Yongting Shi, Zhiheng Lv, Junting Qin

In past decades, the ever-expanding library of 2D carbon allotropes has yielded a broad range of exotic properties for the future carbon-based electronics. However, the known allotropes are all intrinsic nonmagnetic due to the paired valence electrons configuration. Based on the reported 2D carbon structure database and first-principles calculations, herein

Kun Li, Jia Wu, Bo Du, Sergey V. Petoukhov

GNN-based methods have achieved excellent results as a mainstream task in drug response prediction tasks in recent years. Traditional GNN methods use only the atoms in a drug molecule as nodes to obtain the representation of the molecular graph through node information passing, whereas the method using the transformer can only extract information about the n

Nadir Durrani, Hassan Sajjad, Fahim Dalvi, Firoj Alam

We study the evolution of latent space in fine-tuned NLP models. Different from the commonly used probing-framework, we opt for an unsupervised method to analyze representations. More specifically, we discover latent concepts in the representational space using hierarchical clustering. We then use an alignment function to gauge the similarity between the lat

Dorra Bourgiuba, Said Zarati

Let $n \geq 1$ be an integer, let $V=(\mathbb{Z}/2\mathbb{Z})^{n}$ and let $X$ be a $V$-CW-complex. If $X$ is a finite $CW$-complexe, the equivariant modulo $2$ cohomology of the $V$-CW-complexe $X$, denoted by $H_{V}^{*}(X, \mathbb{F}_{2})$, is a finite type module over the modulo $2$ cohomology of the group $V$, denoted by $H^{*}(V, \mathbb{F}_{2})$. Let $

Sungjin Park, Seungwoo Ryu, Edward Choi

Recent success of pre-trained language models (PLMs) has stimulated interest in their ability to understand and work with numbers. Yet, the numerical reasoning over measurements has not been formally studied despite their importance. In this study, we show that PLMs lack the capability required for reasoning over measurements. Furthermore, we find that a lan

Chengyin Li, Zheng Dong, Nathan Fisher, Dongxiao Zhu

Electric Vehicle (EV) charging recommendation that both accommodates user preference and adapts to the ever-changing external environment arises as a cost-effective strategy to alleviate the range anxiety of private EV drivers. Previous studies focus on centralized strategies to achieve optimized resource allocation, particularly useful for privacy-indiffere

Pengchao Hu, Man Lu, Lei Wang, Guoyue Jiang

Multi-level intermediate representations (MLIR) show great promise for reducing the cost of building domain-specific compilers by providing a reusable and extensible compiler infrastructure. This work presents TPU-MLIR, an end-to-end compiler based on MLIR that deploys pre-trained neural network (NN) models to a custom ASIC called a Tensor Processing Unit (T

Jingheng Ye, Yinghui Li, Shirong Ma, Rui Xie

Chinese Grammatical Error Correction (CGEC) aims to automatically detect and correct grammatical errors contained in Chinese text. In the long term, researchers regard CGEC as a task with a certain degree of uncertainty, that is, an ungrammatical sentence may often have multiple references. However, we argue that even though this is a very reasonable hypothe

Stella Civelli, Enrico Forestieri, Marco Secondini

We propose two novel techniques to implement sequence selection (SS) for fiber nonlinearity mitigation, demonstrating a nonlinear shaping gain of 0.24 bits/s/Hz, just 0.1 bits/s/Hz below the SS capacity lower bound.

Shanfan Zhang, Zhan Bu

Temporal networks are an important type of network whose topological structure changes over time. Compared with methods on static networks, temporal network embedding (TNE) methods are facing three challenges: 1) it cannot describe the temporal dependence across network snapshots; 2) the node embedding in the latent space fails to indicate changes in the net

Mengyu Rao, Ruyi Bao, Liangshun Dong

Facial expression is one of the most external indications of a person's feelings and emotions. In daily conversation, according to the psychologist, only 7% and 38% of information is communicated through words and sounds respective, while up to 55% is through facial expression. It plays an important role in coordinating interpersonal relationships. Ekman and

Ruben Wolhandler, Arie Cattan, Ori Ernst, Ido Dagan

The task of multi-document summarization (MDS) aims at models that, given multiple documents as input, are able to generate a summary that combines disperse information, originally spread across these documents. Accordingly, it is expected that both reference summaries in MDS datasets, as well as system summaries, would indeed be based on such dispersed info

Minju Kim, Chaehyeong Kim, Yongho Song, Seung-won Hwang

To build open-domain chatbots that are able to use diverse communicative skills, we propose a novel framework BotsTalk, where multiple agents grounded to the specific target skills participate in a conversation to automatically annotate multi-skill dialogues. We further present Blended Skill BotsTalk (BSBT), a large-scale multi-skill dialogue dataset compris

Gueter Josmy Faure, Min-Hung Chen, Shang-Hong Lai

Actions are about how we interact with the environment, including other people, objects, and ourselves. In this paper, we propose a novel multi-modal Holistic Interaction Transformer Network (HIT) that leverages the largely ignored, but critical hand and pose information essential to most human actions. The proposed "HIT" network is a comprehensive bi-modal

Xiao Meng, Fan Liu, Shihang Lu, Sundeep Prabhakar Chepuri

In this paper, we propose a novel joint active and passive beamforming approach for integrated sensing and communication (ISAC) transmission with assistance of reconfigurable intelligent surfaces (RISs) to simultaneously detect a target and communicate with a communication user. We first show that the sensing and communication (S&C) performance can be jointl

Yufeng Wang, Cong Xu, Min Yang, Jin Zhang

Although Physics-Informed Neural Networks (PINNs) have been successfully applied in a wide variety of science and engineering fields, they can fail to accurately predict the underlying solution in slightly challenging convection-diffusion-reaction problems. In this paper, we investigate the reason of this failure from a domain distribution perspective, and i

A. Crespo-Hernández, E. A. Mena-Barboza, M. Sabido

In this paper we propose a generalization to the Schwarzschild metric and define noncommutative SUSY black holes. We introduce the noncommutative deformation to the minisuperspace variables and derive the noncommutative supersymmetric (SUSY) Wheeler-DeWitt (WDW) equation for the Schwarzschild black hole. We calculate the metric and find that the singularitie

Yunfan Liu, Qi Li, Qiyao Deng, Zhenan Sun

Facial Attribute Manipulation (FAM) aims to aesthetically modify a given face image to render desired attributes, which has received significant attention due to its broad practical applications ranging from digital entertainment to biometric forensics. In the last decade, with the remarkable success of Generative Adversarial Networks (GANs) in synthesizing

Sergey Zakharov, Rares Ambrus, Vitor Guizilini, Wadim Kehl

Synthetic data is a scalable alternative to manual supervision, but it requires overcoming the sim-to-real domain gap. This discrepancy between virtual and real worlds is addressed by two seemingly opposed approaches: improving the realism of simulation or foregoing realism entirely via domain randomization. In this paper, we show that the recent progress in

Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie

Rotation is frequently listed as a candidate for data augmentation in contrastive learning but seldom provides satisfactory improvements. We argue that this is because the rotated image is always treated as either positive or negative. The semantics of an image can be rotation-invariant or rotation-variant, so whether the rotated image is treated as positive

D. V. Artamonov

In the paper we consider a realization of a finite dimensional irreducible representation of the Lie algebra $\mathfrak{gl}_n$ in the space of functions on the group $GL_n$. It is proved that functions corresponding to Gelfand-Tsetlin diagrams are linear combinations of some new functions of hypergeometric type which are closely related to $A$-hypergeometric

Chenxu Liu, Karl Gebhardt, Wolfram Kollatschny, Robin Ciardullo

We report an Active Galactic Nucleus (AGN) with extremely high equivalent width (EW), EW(LyA+NV,rest)>921 AA in the rest-frame, at z~2.24 in the Hobby-Eberly Telescope Dark Energy Experiment Survey (HETDEX) as a representative case of the high EW AGN population. The continuum level is a non-detection in the HETDEX spectrum, thus the measured EW is a lower li

Silin Gao, Jena D. Hwang, Saya Kanno, Hiromi Wakaki

Understanding rich narratives, such as dialogues and stories, often requires natural language processing systems to access relevant knowledge from commonsense knowledge graphs. However, these systems typically retrieve facts from KGs using simple heuristics that disregard the complex challenges of identifying situationally-relevant commonsense knowledge (e.g

Changhao Chen, Zhengyan Miao

We study the arithmetic structure of the exceptional set of projections. For any bounded subset $E\subset \mathbb{R}^d$, let $$ \Omega=\{\xi\in \mathbb{R}: \dim_B(E+\xi E)=\dim_B E\}. $$ We prove that either $\Omega=\{0\}$ or $\Omega$ is a subfield of $\mathbb{R}$. We show that in general the statement does not hold for Hausdorff dimension and lower box dime

Ulises Pérez Cendejas, Gerardo Pérez Suárez

We investigate a class of topological monoids with a suitable family of characters which we call Feller topological monoids. We extend the classical notion of subordinators to subordinators on Feller topological monoids. Under suitable assumptions, we prove a L\'evy-Khintchine type representation for such subordinators. In addition, a L\'evy-It\^o like decom

Paul Manuel, Sandi Klavzar, R. Prabha, Andrew Arokiaraj

A geodesic cover, also known as an isometric path cover, of a graph is a set of geodesics which cover the vertex set of the graph. An edge geodesic cover of a graph is a set of geodesics which cover the edge set of the graph. The geodesic (edge) cover number of a graph is the cardinality of a minimum (edge) geodesic cover. The (edge) geodesic cover problem o

Chang Gao, Bowen Li, Wenxuan Zhang, Wai Lam

Text-to-SQL parsing tackles the problem of mapping natural language questions to executable SQL queries. In practice, text-to-SQL parsers often encounter various challenging scenarios, requiring them to be generalizable and robust. While most existing work addresses a particular generalization or robustness challenge, we aim to study it in a more comprehensi

Elron Bandel, Yoav Goldberg, Yanai Elazar

While fine-tuned language models perform well on many tasks, they were also shown to rely on superficial surface features such as lexical overlap. Excessive utilization of such heuristics can lead to failure on challenging inputs. We analyze the use of lexical overlap heuristics in natural language inference, paraphrase detection, and reading comprehension (

M. C. L. Madden, A. C. A. Boogert, J. E. Chiar, C. Knez

The properties of dust change during the transition from diffuse to dense clouds as a result of ice formation and dust coagulation, but much is still unclear about this transformation. We present 2-20 micron spectra of 49 field stars behind the Perseus and Serpens Molecular Clouds and establish relationships between the near-infrared continuum extinction (AK

Liang Xiao, Zhiqi Huang, Yi Zheng, Xin Wang

The tomographic Alcock-Paczynski (AP) method is a promising method that uses the redshift evolution of the anisotropic clustering in redshift space to calibrate cosmology. It extends the applicable range of AP method to substantially nonlinear scales, yielding very tight cosmological constraints. For future stage-IV slitless spectroscopic surveys, the non-ne

Xincheng Shu, Zhongyuan Ruan

The mobility patterns of individuals in China during the early outbreak of the COVID-19 pandemic exhibit reversible changes -- in many regions, the mobility first decreased significantly and later restored. Based on this observation, here we study the classical SIR model on a particular type of time-varying network where the links undergo a freeze-recovery p

Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast

Physics-informed neural networks (PINNs) are emerging as popular mesh-free solvers for partial differential equations (PDEs). Recent extensions decompose the domain, apply different PINNs to solve the problem in each subdomain, and stitch the subdomains at the interface. Thereby, they can further alleviate the problem complexity, reduce the computational cos

Ritvik Ramkumar, Alessio Sammartano

Let I be the ideal of minors of a 2 by n matrix of linear forms with the expected codimension. In this paper we prove that the Rees algebra of I and its special fiber ring are Cohen-Macaulay and Koszul; in particular, they are quadratic algebras. The main novelty in our approach is the analysis of a stratification of the Hilbert scheme of determinantal ideal

Sergey A. Khaibrakhmanov, Alexander E. Dudorov, Anton I. Vasyunin, Mikhail Yu. Kiskin

The vertical structure of the accretion disks of young stars with fossil large-scale magnetic field is studied. The equations of magnetostatic equilibrium of the disk are solved taking into account the stellar gravity, gas and magnetic pressure, turbulent heating, and heating by stellar radiation. The modelled physical structure of the disk is used to simula

Majid Rahro Zargar

Let $M$ be an $R$-module over a Noetherian ring $R$ and $\mathfrak{a}$ be an ideal of $R$ with $c={\rm cd}(\mathfrak{a},M)$. First, we prove that $M$ is finite $\mathfrak{a}$-relative Cohen-Macaulay if and only if ${\rm H}_i(\Lambda_{\mathfrak{a}}({\rm H}_{\mathfrak{a}}^c(M)))=0$ for all $i\neq c$ and ${\rm H}_c(\Lambda_{\mathfrak{a}}({\rm H}_{\mathfrak{a}}^

Rodica Dinu, Francesco Navarra

We study the K\H{o}nig type property for non-simple polyominoes. We prove that, for closed path polyominoes, the polyomino ideals are of K\H{o}nig type, extending the results of Herzog and Hibi for simple thin polyominoes. As an application of this result, we give a combinatorial interpretation for the canonical module of the coordinate ring of a sub-class o

Daohua Yu, Ruihao Gu

Let f and g be two Anosov diffeomorphisms on T3 with three-subbundles partially hyperbolic splittings where the weak stable subbundles are considered as center subbundles. Assume that f is conjugate to g and the conjugacy preserves the strong stable foliation, then their center Lyapunov exponents of corresponding periodic points coincide. This is the convers

Mengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang

Supply chain management (SCM) has been recognized as an important discipline with applications to many industries, where the two-echelon stochastic inventory model, involving one downstream retailer and one upstream supplier, plays a fundamental role for developing firms' SCM strategies. In this work, we aim at designing online learning algorithms for this p

Qinghua Mao, Jiatong Li, Kui Meng

Compared with English, Chinese suffers from more grammatical ambiguities, like fuzzy word boundaries and polysemous words. In this case, contextual information is not sufficient to support Chinese named entity recognition (NER), especially for rare and emerging named entities. Semantic augmentation using external knowledge is a potential way to alleviate thi