October 2022 arXiv papers — page 54

Patrick Hennebelle, Ugo Lebreuilly, Tine Colman, Davide Elia

In spite of decades of theoretical efforts, the physical origin of the stellar initial mass function (IMF) is still debated. We aim at understanding the influence of various physical processes such as radiative stellar feedback, magnetic field and non-ideal magneto-hydrodynamics on the IMF. We present a series of numerical simulations of collapsing 1000 M$_\

Alec Owens, Sophie Dooley, Luke McLaughlin, Brandon Tan

New molecular line lists for calcium monohydride ($^{40}$Ca$^{1}$H) and magnesium monohydride ($^{24}$Mg$^{1}$H) and its minor isotopologues ($^{25}$Mg$^{1}$H and $^{26}$Mg$^{1}$H) are presented. The rotation-vibration-electronic (rovibronic) line lists, named \texttt{XAB}, consider transitions involving the \X, \A, and \BBp\ electronic states in the 0--30\,

Saibal Ganguli, Mainak Poddar

We define a notion of Heegaard Floer homology for three dimensional orbifolds with arbitrary cyclic singularities, generalizing the recent work of Biji Wong where the singular locus is assumed to be connected.

Sergiy Borodachov

We show that among antipodal $2d$-point configurations on the sphere $S^{d-1}$ in $\mathbb R^d$, the set of vertices of a regular cross-polytope inscribed in $S^{d-1}$ uniquely solves the best-covering problem (this is new for $d\geq 5$) and the maximal polarization problem for potentials given by a function of the distance squared with a positive and convex

Andriy E. Yaroshchuk, Stanislaw Koter, Volodymyr I. Kovalchuk, Emiliy K. Zholkovskiy

The paper deals with relationships between the individual transmembrane fluxes of binary electrolyte solution components and the experimentally measurable quantities describing rates of transfer processes, namely, the electric current, the transmembrane volume flow and the rates of concentration changes in the solutions adjacent to the membrane. Also, we col

Yaolong Yu, Haifeng Xu, Haipeng Chen

Many real-world strategic games involve interactions between multiple players. We study a hierarchical multi-player game structure, where players with asymmetric roles can be separated into leaders and followers, a setting often referred to as Stackelberg game or leader-follower game. In particular, we focus on a Stackelberg game scenario where there are mul

Yasuaki Hiraoka, Shu Kanazawa, Jun Miyanaga, Kenkichi Tsunoda

The objective of this article is to investigate the asymptotic behavior of the persistence diagrams of a random cubical filtration as the window size tends to infinity. Here, a random cubical filtration is an increasing family of random cubical sets, which are the union of randomly generated higher-dimensional unit cubes with integer coordinates in a Euclide

Yichuan Deng, Xiaoyu Li, Zhao Song, Omri Weinstein

A recent work by [Larsen, SODA 2023] introduced a faster combinatorial alternative to Bansal's SDP algorithm for finding a coloring $x \in \{-1, 1\}^n$ that approximately minimizes the discrepancy $\mathrm{disc}(A, x) := | A x |_{\infty}$ of a real-valued $m \times n$ matrix $A$. Larsen's algorithm runs in $\widetilde{O}(mn^2)$ time compared to Bansal's $\wi

Rajdeep Mukherjee, Abhinav Bohra, Akash Banerjee, Soumya Sharma

Despite tremendous progress in automatic summarization, state-of-the-art methods are predominantly trained to excel in summarizing short newswire articles, or documents with strong layout biases such as scientific articles or government reports. Efficient techniques to summarize financial documents, including facts and figures, have largely been unexplored,

Jin-Long Zhu, Wen-Xin Zhu, Xiao-Tao Shi, Chen-Tao Zhang

The mid-infrared (MIR) band entangled photon source is vital for the next generation of quantum communication, quantum imaging, and quantum sensing. However, the current entangled states are mainly prepared in visible or near-infrared bands. It is still lack of high-quality entangled photon sources in the MIR band. In this work, we optimize the poling sequen

Silvia Fernández-Merchant, Rimma Hämäläinen

In 1982, Ungar proved that the connecting lines of a set of $n$ noncollinear points in the plane determine at least $2\lfloor n/2 \rfloor$ directions (slopes). Sets achieving this minimum for $n$ odd (even) are called \emph{direction-(near)-critical} and their full classification is still open. To date, there are four known infinite families and over 100 spo

V Ncume, T. L van Zyl, A Paskaramoorthy

Several studies have shown that deep learning models can provide more accurate volatility forecasts than the traditional methods used within this domain. This paper presents a composite model that merges a deep learning approach with sentiment analysis for predicting market volatility. To classify public sentiment, we use a Convolutional Neural Network, whic

Chen Tang, Chenghua Lin, Henglin Huang, Frank Guerin

One of the key challenges of automatic story generation is how to generate a long narrative that can maintain fluency, relevance, and coherence. Despite recent progress, current story generation systems still face the challenge of how to effectively capture contextual and event features, which has a profound impact on a model's generation performance. To add

Zikai Wei, Bo Dai, Dahua Lin

Modeling and characterizing multiple factors is perhaps the most important step in achieving excess returns over market benchmarks. Both academia and industry are striving to find new factors that have good explanatory power for future stock returns and good stability of their predictive power. In practice, factor investing is still largely based on linear m

Xueliang Zhao, Lemao Liu, Tingchen Fu, Shuming Shi

With the availability of massive general-domain dialogue data, pre-trained dialogue generation appears to be super appealing to transfer knowledge from the general domain to downstream applications. In most existing work, such transferable ability is mainly obtained by fitting a large model with hundreds of millions of parameters on massive data in an exhaus

Xueliang Zhao, Yuxuan Wang, Chongyang Tao, Chenshuo Wang

We study video-grounded dialogue generation, where a response is generated based on the dialogue context and the associated video. The primary challenges of this task lie in (1) the difficulty of integrating video data into pre-trained language models (PLMs) which presents obstacles to exploiting the power of large-scale pre-training; and (2) the necessity o

Xueliang Zhao, Tingchen Fu, Chongyang Tao, Rui Yan

Knowledge-grounded conversation (KGC) shows excellent potential to deliver an engaging and informative response. However, existing approaches emphasize selecting one golden knowledge given a particular dialogue context, overlooking the one-to-many phenomenon in dialogue. As a result, the existing paradigm limits the diversity of knowledge selection and gener

Esben Jannik Bjerrum, Christian Margreitter, Thomas Blaschke, Raquel López-Ríos de Castro

Using generative deep learning models and reinforcement learning together can effectively generate new molecules with desired properties. By employing a multi-objective scoring function, thousands of high-scoring molecules can be generated, making this approach useful for drug discovery and material science. However, the application of these methods can be h

Zachary Fulker, Patrick Forber, Rory Smead, Christoph Riedl

We study the coevolution of network structure and signaling behavior. We model agents who can preferentially associate with others in a dynamic network while they also learn to play a simple sender-receiver game. We have four major findings. First, signaling interactions in dynamic networks are sufficient to cause the endogenous formation of distinct signali

Ewa Zawiślak-Sprysak, Paweł Zawiślak

In this paper, we analyse results of the $15^{\textrm{th}}$ International Henryk Wieniawski Violin Competition by comparing the properties of its results network to the properties of \emph{generic networks of votings}.

Tongshuai Zhu, Huaiqiang Wang, Haijun Zhang

Floquet engineering is an important way to manipulate the electronic states of condensed matter physics. Recently, the discovery of the magnetic topological insulator MnBi$_2$Te$_4$ and its family provided a valuable platform to study magnetic topological phenomena, such as, the quantum anomalous Hall effect, the axion insulator state and the topological mag

Abhinandan Pal, Francesco Ranzato, Caterina Urban, Marco Zanella

We propose a symbolic representation for support vector machines (SVMs) by means of abstract interpretation, a well-known and successful technique for designing and implementing static program analyses. We leverage this abstraction in two ways: (1) to enhance the interpretability of SVMs by deriving a novel feature importance measure, called abstract feature

Chenyu Bai

We study in this article three birational invariants of projective hyper-K\"ahler manifolds: the degree of irrationality, the fibering gonality and the fibering genus. We first improve the lower bound in a recent result of Voisin saying that the fibering genus of a Mumford--Tate very general projective hyper-K\"ahler manifold is bounded from below by a const

Vinicius F. Dal Poggetto, Nicola M. Pugno, José Roberto de F. Arruda

The design of structures that can yield efficient sound insulation performance is a recurring topic in the acoustic engineering field. Special attention is given to panels, which can be designed using several approaches to achieve considerable sound attenuation. Previously, we have presented the concept of thickness-varying periodic plates with optimized pro

Yuchen Shi, Congying Han, Tiande Guo

Spanning tree problems with specialized constraints can be difficult to solve in real-world scenarios, often requiring intricate algorithmic design and exponential time. Recently, there has been growing interest in end-to-end deep neural networks for solving routing problems. However, such methods typically produce sequences of vertices, which makes it diffi

Zanbin Xing, Lei Chang

A symmetry-preserving regularization procedure for dealing with the contact interaction model is proposed in this work. This regularization procedure follows a series of consistency conditions which are necessary to maintain gauge symmetry. Under this regularization, proofs for the preservation of the Ward-Takahashi identities are given and the loop integral

Christian Lehn, Giovanni Mongardi, Gianluca Pacienza

In this note, we extend to the singular case some results on the birational geometry of irreducible holomorphic symplectic manifolds.

Theodoros Assiotis

We consider one-dimensional diffusions, with polynomial drift and diffusion coefficients, so that in particular the motion can be space-inhomogeneous, interacting via one-sided reflections. The prototypical example is the well-known model of Brownian motions with one-sided collisions, also known as Brownian TASEP, which is equivalent to Brownian last passage

Yitian Qian, Shaohua Pan

This work extends the iterative framework proposed by Attouch et al. (in Math. Program. 137: 91-129, 2013) for minimizing a nonconvex and nonsmooth function $\Phi$ so that the generated sequence possesses a Q-superlinear convergence rate. This framework consists of a monotone decrease condition, a relative error condition and a continuity condition, and the

Andrei A. Rusu, Sebastian Flennerhag, Dushyant Rao, Razvan Pascanu

We evaluate the use of original game curricula supported by the Atari 2600 console as a heterogeneous transfer benchmark for deep reinforcement learning agents. Game designers created curricula using combinations of several discrete modifications to the basic versions of games such as Space Invaders, Breakout and Freeway, making them progressively more chall

Xuhua Li, Weize Sun, Lei Huang, Shaowu Chen

Filter pruning is a common method to achieve model compression and acceleration in deep neural networks (DNNs).Some research regarded filter pruning as a combinatorial optimization problem and thus used evolutionary algorithms (EA) to prune filters of DNNs. However, it is difficult to find a satisfactory compromise solution in a reasonable time due to the co

Mengbing Liu, Xin Li, Boyu Ning, Chongwen Huang

Reconfigurable Intelligent Surface (RIS) is considered as an energy-efficient solution for future wireless communication networks due to its fast and low-cost configuration. In this letter, we consider the estimation of cascaded channels in a double-RIS aided massive multiple-input multiple-output system, which is a critical challenge due to the large number

Shivaditya Shivganesh, Nitin Narayanan N, Pranav Murali, Ajaykumar M

This study is about inducing classifiers using data that is imbalanced, with a minority class being under-represented in relation to the majority classes. The first section of this research focuses on the main characteristics of data that generate this problem. Following a study of previous, relevant research, a variety of artificial, imbalanced data sets in

Xuefeng Bai, Seng Yang, Leyang Cui, Linfeng Song

Abstract Meaning Representation (AMR) parsing aims to predict an AMR graph from textual input. Recently, there has been notable growth in AMR parsing performance. However, most existing work focuses on improving the performance in the specific domain, ignoring the potential domain dependence of AMR parsing systems. To address this, we extensively evaluate fi

Long Chen, Yulei Niu, Brian Chen, Xudong Lin

Given a long untrimmed video and natural language queries, video grounding (VG) aims to temporally localize the semantically-aligned video segments. Almost all existing VG work holds two simple but unrealistic assumptions: 1) All query sentences can be grounded in the corresponding video. 2) All query sentences for the same video are always at the same seman

Liu Qiu, Rishabh Sahu, William Hease, Georg Arnold

Recent quantum technologies have established precise quantum control of various microscopic systems using electromagnetic waves. Interfaces based on cryogenic cavity electro-optic systems are particularly promising, due to the direct interaction between microwave and optical fields in the quantum regime. Quantum optical control of superconducting microwave c

Alexander M. T. L. Yiu, Torsten Kleinow, George Streftaris

In recent years, improvements in all-cause mortality rates and life expectancies for males and females in England and Wales have slowed down. In this paper, cause-specific mortality data for England and Wales from 2001 to 2018 are used to investigate the cause-specific contributions to the slowdown in improvements. Cause-specific death counts in England and

Sullivan Francis MacDonald, Scott Rodney

In this work we study global boundedness and exponential integrability of weak solutions to degenerate $p$-Poisson equations using an iterative method of De Giorgi type. Given a symmetric, non-negative definite matrix valued function $Q$ defined on a bounded domain $\Omega\Subset\mathbb{R}^n$, a weight function $v\in L^1_\textrm{loc}(\Omega,dx)$, and a suita

Yansong Wang, Yundong Sun, Yansheng Fu, Dongjie Zhu

Spectral detection technology, as a non-invasive method for rapid detection of substances, combined with deep learning algorithms, has been widely used in food detection. However, in real scenarios, acquiring and labeling spectral data is an extremely labor-intensive task, which makes it impossible to provide enough high-quality data for training efficient s

Andrei A. Rusu, Dan A. Calian, Sven Gowal, Raia Hadsell

We introduce the Lossy Implicit Network Activation Coding (LINAC) defence, an input transformation which successfully hinders several common adversarial attacks on CIFAR-$10$ classifiers for perturbations up to $\epsilon = 8/255$ in $L_\infty$ norm and $\epsilon = 0.5$ in $L_2$ norm. Implicit neural representations are used to approximately encode pixel colo

Hong Wu, Jun-Hong An

Having the potential for performing quantum computation, topological superconductors have been generalized to the second-order case. The hybridization of different orders of topological superconductors is attractive because it facilitates the simultaneous utilization of their respective advantages. However, previous studies found that they cannot coexist in

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley

The research area of algorithms with predictions has seen recent success showing how to incorporate machine learning into algorithm design to improve performance when the predictions are correct, while retaining worst-case guarantees when they are not. Most previous work has assumed that the algorithm has access to a single predictor. However, in practice, t

Abhishek Agarwal, Shanshan Xu, Matthias Grabmair

Summarizing legal decisions requires the expertise of law practitioners, which is both time- and cost-intensive. This paper presents techniques for extractive summarization of legal decisions in a low-resource setting using limited expert annotated data. We test a set of models that locate relevant content using a sequential model and tackle redundancy by le

Takachika Isomae, Akito Sakai, Mingxuan Fu, Takanori Taniguchi

Multipolar Kondo systems offer unprecedented opportunities for designing astonishing quantum phases and functionalities beyond spin-only descriptions. A model material platform of this kind is the cubic heavy-fermion system Pr$Tr_{2}$Al$_{20}$ ($Tr=$ Ti, V), which hosts a nonmagnetic crystal-electric-field (CEF) ground state and substantial Kondo entanglemen

Jiale Han, Shuai Zhao, Bo Cheng, Shengkun Ma

Using prompts to explore the knowledge contained within pre-trained language models for downstream tasks has now become an active topic. Current prompt tuning methods mostly convert the downstream tasks to masked language modeling problems by adding cloze-style phrases and mapping all labels to verbalizations with fixed length, which has proven effective for

Haojie Ren

For a Lipschitz $\mathbb{Z}-$periodic function $\phi:\mathbb{R}\to \mathbb{R}^2$ satisfied that $\mathbb{R}^2\setminus\{\phi(x):x\in\mathbb{R}\}$ is not connected, an integer $b\ge 2$ and $\lambda\in (c/{b^{\frac12}},1)$, we prove the following for the generalized Weierstrass-type function $W(x)=\sum\limits_{n=0}^{\infty}{{\lambda}^n\phi(b^nx)}$: the box dim

Wei Cao, Daqing Wan

Let $\mathbb{F}_q$ denote the finite field of $q$ elements with characteristic $p$. Let $\mathbb{Z}_q$ denote the unramified extension of the $p$-adic integers $\mathbb{Z}_p$ with residue field $\mathbb{F}_q$. In this paper, we investigate the $q$-divisibility for the number of solutions of a polynomial system in $n$ variables over the finite Witt ring $\mat

Bin Wang, Jiangzhou Ju, Yang Fan, Xinyu Dai

As one of the challenging NLP tasks, designing math word problem (MWP) solvers has attracted increasing research attention for the past few years. In previous work, models designed by taking into account the properties of the binary tree structure of mathematical expressions at the output side have achieved better performance. However, the expressions corres

Livia Terlizzi

ALICE (A Large Ion Collider Experiment) at the CERN Large Hadron Collider (LHC) is designed to study proton-proton and heavy-ion collisions at ultra-relativistic energies. The main goal of the experiment is to assess the properties of quark gluon plasma, a state of matter where quarks and gluons are de-confined, reached in extreme conditions of temperature a

Cheng Lu, Wenming Zheng, Hailun Lian, Yuan Zong

Spectrogram is commonly used as the input feature of deep neural networks to learn the high(er)-level time-frequency pattern of speech signal for speech emotion recognition (SER). \textcolor{black}{Generally, different emotions correspond to specific energy activations both within frequency bands and time frames on spectrogram, which indicates the frequency

David Gros, Yu Li, Zhou Yu

Dialog systems are often designed or trained to output human-like responses. However, some responses may be impossible for a machine to truthfully say (e.g. "that movie made me cry"). Highly anthropomorphic responses might make users uncomfortable or implicitly deceive them into thinking they are interacting with a human. We collect human ratings on the feas

Siddhartha Solanki, Manohar Lal, Vineet Kumar Agotiya

In the present work we have studied the Differential Scattering Cross-section for ground states of charmonium and bottomonium in the frame work of the medium modified form of quark-antiquark potential and Born-approximation using the non-relativistic quantum chromo-dynamics approach. To reach this end, quasi-particle (QP) Debye mass depending upon baryonic c

Faraz A. Inam, Rajesh V. Nair

Generation of an ultra-bright, deterministic, solid-state single photon source with high photon collection rate is an imperative requirement for quantum technologies. In this direction, various nanophotonic systems coupled with single quantum emitters are being implemented, but results in low decay rate enhancement and MHz photon collection rate. Here, we un

Dongkyu Lee, Zhiliang Tian, Yingxiu Zhao, Ka Chun Cheung

In knowledge distillation, a student model is trained with supervisions from both knowledge from a teacher and observations drawn from a training data distribution. Knowledge of a teacher is considered a subject that holds inter-class relations which send a meaningful supervision to a student; hence, much effort has been put to find such knowledge to be dist

Dongkyu Lee, Ka Chun Cheung, Nevin L. Zhang

Overconfidence has been shown to impair generalization and calibration of a neural network. Previous studies remedy this issue by adding a regularization term to a loss function, preventing a model from making a peaked distribution. Label smoothing smoothes target labels with a pre-defined prior label distribution; as a result, a model is learned to maximize

Nitesh Singh, Rajesh V Nair

The resonant modes associated with engineered photonic structures of different spatial-dimension are essential to obtain bright on-demand single photon sources for quantum technologies. Negatively-charged nitrogen-vacancy (NV-) center in diamond is proposed as an excellent single photon source at room temperature. The possible optical readout of spin states

Sergey A. Khaibrakhmanov, Alexander E. Dudorov, Natalya S. Kargaltseva, Andrey G. Zhilkin

We investigate collapse of magnetic protostellar clouds of mass $10$ and $1 M_{\odot}$. The collapse is simulated numerically using the two-dimensional magnetohydrodynamic (MHD) code `Enlil'. The simulations show that protostellar clouds acquire a hierarchical structure by the end of the isothermal stage of collapse. Under the action of the electromagnetic f

Franco Flandoli, Ruojun Huang

A new noise, based on vortex structures in 2D (point vortices) and 3D (vortex filaments), is introduced. It is defined as the scaling limit of a jump process which explores vortex structures and it can be defined in any domain, also with boundary. The link with Fractional Gaussian Fields and Kraichnan noise is discussed. The vortex noise is finally shown to

Christian Hirsch, Taegyu Kang, Takashi Owada

This paper develops the large deviations theory for the point process associated with the Euclidean volume of $k$-nearest neighbor balls centered around the points of a homogeneous Poisson or a binomial point processes in the unit cube. Two different types of large deviation behaviors of such point processes are investigated. Our first result is the Donsker-

Yidi Wang, Shuangnan Zhang, Minyu Ge, Wei Zheng

The recent flight experiments with Neutron Star Interior Composition Explorer (\textit{NICER}) and \textit{Insight}-Hard X-ray Modulation Telescope (\textit{Insight}-HXMT) have demonstrated the feasibility of X-ray pulsar-based navigation (XNAV) in the space. However, the current pulse phase estimation and navigation methods employed in the above flight expe

Shahriyar Jafarzade

The $\rho_2$ meson is the missing isovector member of the meson nonet with the quantum numbers $J^{PC}=2^{--}$. It belongs to the class of $\rho$-mesons such as the vector meson $\rho(770)$, the excited vector $\rho(1700)$ and the tensor $\rho_3(1690)$. Yet, despite the rich experimental and theoretical studies for other $\rho$-meson states, no resonance tha

J. A. Gracey

We construct the five loop anomalous dimensions of the basic fields in Quantum Chromodynamics in a linear covariant gauge in the modified Regularization Invariant (RI') scheme. Using these core results we also compute the four loop Green's function where the quark mass operator and vector current are separately inserted in a quark 2-point function. These are

Konstantin Ardakov, Peter Schneider

The center $Z(\mathcal{A})$ of an abelian category $\mathcal{A}$ is the endomorphism ring of the identity functor on that category. A localizing subcategory of a Grothendieck category $\mathcal{C}$ is said to be stable if it is stable under essential extensions. The set $\mathbf{L}^{st}(\mathcal{C})$ of stable localizing subcategories of $\mathcal{C}$ is par

Vignesh Prasad, Dorothea Koert, Ruth Stock-Homburg, Jan Peters

Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human's actions and intentions is critical for efficient and effective collaborative Human-Robot Interactions (HRI). Learning from Demonstration (LfD) methods from Human-Human Interactions (HHI) have shown promising results, especially when coupled with r

Junliang Chen, Xiaodong Zhao, Minmin Liu, Linlin Shen

Recent mainstream weakly-supervised semantic segmentation (WSSS) approaches mainly relies on image-level classification learning, which has limited representation capacity. In this paper, we propose a novel semantic learning based framework, named SLAMs (Semantic Learning based Activation Map), for WSSS.

Matthew J. Lake

We show that the equations of motion governing the dynamics of strings in a compact internal space can be written as dispersion relations, with a local speed that depends on the velocity and curvature of the string in the large dimensions. From a $(3+1)$-dimensional perspective these can be viewed as dispersion relations for waves propagating in the string i

Zhiying Xu, Jiafan Xu, Hongding Peng, Wei Wang

Deep learning models rely on highly optimized tensor libraries for efficient inference on heterogeneous hardware. Current deep compilers typically predetermine layouts of tensors and then optimize loops of operators. However, such unidirectional and one-off workflow strictly separates graph-level optimization and operator-level optimization into different sy

Tarun Maity, Mounika Gosika, Tod A. Pascal, Prabal K. Maiti

Increasing the energy density in electric double layer capacitors (EDLCs), also known as supercapacitors, remains an active area of research. Specifically, there is a need to design and discover electrode and electrolyte materials with enhanced electrochemical storage capacity. Here, using fully atomistic molecular dynamics (MD) simulations, we investigate t

K. Suchomska, D. Graczyk, C. Gałan, O. Ziółkowska

Our goal is to determine, with high accuracy, the physical and orbital parameters of two double-lined eclipsing binary systems, where the components are two giant stars. We also aim to study the evolutionary status of the binaries, to derive the distances towards them by using a surface brightness-colour relation, and to compare these measurements with the m

Anirban Bose

An equation of pair correlation function has been derived from the first two members of BBGKY hierarchy in a weakly coupled inhomogeneous self gravitating system in quasi thermal equilibrium. This work may be useful to study the thermodynamic properties of the central region of a star cluster which is older than a few or more central relaxation time.

Olivier Absil, Christian Delacroix, Gilles Orban de Xivry, Prashant Pathak

The high-speed variability of the local water vapor content in the Earth atmosphere is a significant contributor to ground-based wavefront quality throughout the infrared domain. Unlike dry air, water vapor is highly chromatic, especially in the mid-infrared. This means that adaptive optics correction in the visible or near-infrared domain does not necessari

Tomislav Došlić, Mate Puljiz, Stjepan Šebek, Josip Žubrinić

We consider a one-dimensional variant of a recently introduced settlement planning problem in which houses can be built on finite portions of the rectangular integer lattice subject to certain requirements on the amount of insolation they receive. In our model, each house occupies a unit square on a $1 \times n$ strip, with the restriction that at least one

Bashar Alhafni, Nizar Habash, Houda Bouamor, Ossama Obeid

In this paper, we present the results and findings of the Shared Task on Gender Rewriting, which was organized as part of the Seventh Arabic Natural Language Processing Workshop. The task of gender rewriting refers to generating alternatives of a given sentence to match different target user gender contexts (e.g., female speaker with a male listener, a male

Jinyi Hu, Xiaoyuan Yi, Wenhao Li, Maosong Sun

Variational Auto-Encoder (VAE) has been widely adopted in text generation. Among many variants, recurrent VAE learns token-wise latent variables with each conditioned on the preceding ones, which captures sequential variability better in the era of RNN. However, it is unclear how to incorporate such recurrent dynamics into the recently dominant Transformer d

Ibéria Medeiros, Geert Deconinck

Collection of manuscripts accepted for presentation at the Student Forum and Fast Abstracts tracks of the 18th European Dependable Computing Conference (EDCC 2022).

Xianfa Hu, Yonglei Fang, Bin Wang

In this paper, two new families of fourth-order explicit exponential Runge--Kutta (ERK) methods with four stages are studied for solving first-order differential systems $y'(t)+My(t)=f(y(t))$. By comparing the Taylor series of the exact solution, the order conditions of these ERK methods are derived, which are exactly identical to the order conditions of exp

Gereon Koßmann, Lennart Binkowski, Lauritz van Luijk, Timo Ziegler

Despite its popularity, several empirical and theoretical studies suggest that the quantum approximate optimization algorithm (QAOA) has persistent issues in providing a substantial practical advantage. Numerical results for few qubits and shallow circuits are, at best, ambiguous, and the well-studied barren plateau phenomenon draws a rather sobering picture

Anna A. Taranenko

The paper is devoted to multidimensional $(0,1)$-matrices extremal with respect to containing a polydiagonal (a fractional generalization of a diagonal). Every extremal matrix is a threshold matrix, i.e., an entry belongs to its support whenever a weighted sum of incident hyperplanes exceeds a given threshold. Firstly, we prove that nonequivalent threshold m

Manimala Mitra, Sanjoy Mandal, Rojalin Padhan, Agnivo Sarkar

The gauge singlet right-handed neutrinos (RHNs) are essential fields in several neutrino mass models that explain the observed eV scale neutrino mass. We assume RHN field to be present in the vicinity of the electroweak scale and all the other possible beyond the standard model (BSM) fields arise at high energy scale $\ge\Lambda$. In this scenario, the BSM p

Yupeng Zhang, Hongzhi Zhang, Sirui Wang, Wei Wu

A wide range of NLP tasks benefit from the fine-tuning of pretrained language models (PLMs). However, a number of redundant parameters which contribute less to the downstream task are observed in a directly fine-tuned model. We consider the gap between pretraining and downstream tasks hinders the training of these redundant parameters, and results in a subop

Feifan Li, Lun Du, Qiang Fu, Shi Han

User engagement prediction plays a critical role for designing interaction strategies to grow user engagement and increase revenue in online social platforms. Through the in-depth analysis of the real-world data from the world's largest professional social platforms, i.e., LinkedIn, we find that users expose diverse engagement patterns, and a major reason fo

Xianjun Yang, Ya Zhuo, Julia Zuo, Xinlu Zhang

Scientific action graphs extraction from materials synthesis procedures is important for reproducible research, machine automation, and material prediction. But the lack of annotated data has hindered progress in this field. We demonstrate an effort to annotate Polycrystalline Materials Synthesis Procedures (PcMSP) from 305 open access scientific articles fo

Nedjma Ousidhoum, Zhangdie Yuan, Andreas Vlachos

Fact-checking requires retrieving evidence related to a claim under investigation. The task can be formulated as question generation based on a claim, followed by question answering. However, recent question generation approaches assume that the answer is known and typically contained in a passage given as input, whereas such passages are what is being sough

Musa Mammadov, Piotr Szuca

In this paper the turnpike property is established for a non-convex optimal control problem in discrete time. The functional is defined by the notion of the ideal convergence and can be considered as an analogue of the terminal functional defined over infinite time horizon. The turnpike property states that every optimal solution converges to some unique opt

Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang

Message Passing Neural Networks (MPNNs) are a widely used class of Graph Neural Networks (GNNs). The limited representational power of MPNNs inspires the study of provably powerful GNN architectures. However, knowing one model is more powerful than another gives little insight about what functions they can or cannot express. It is still unclear whether these

Yuichi Hiroi, Yuta Itoh, Jun Rekimoto

While the presentation of photo-realistic appearance plays a major role in immersion in an augmented virtuality environment, displaying the photo-realistic appearance of real objects remains a challenging problem. Recent developments in photogrammetry have facilitated the incorporation of real objects into virtual space. However, photo-realistic photogrammet

Fanghua Ye, Xi Wang, Jie Huang, Shenghui Li

Existing dialogue datasets contain lots of noise in their state annotations. Such noise can hurt model training and ultimately lead to poor generalization performance. A general framework named ASSIST has recently been proposed to train robust dialogue state tracking (DST) models. It introduces an auxiliary model to generate pseudo labels for the noisy train

Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang

Adversarial Examples Detection (AED) is a crucial defense technique against adversarial attacks and has drawn increasing attention from the Natural Language Processing (NLP) community. Despite the surge of new AED methods, our studies show that existing methods heavily rely on a shortcut to achieve good performance. In other words, current search-based adver

He Li, Yun Bo Li, Wang Sheng Hu, Sheng Jie Huang

We propose to achieve joint detections of frequency and direction of arrival in wideband using single sensor based on an active metasurface with programmable transmission states of pass and stop. By integrating two PIN diodes with the opposite directions into the proposed single-layer and ultrathin meta-atom, the transmission performance with 10 dB differenc

Alexander Tolmachev, Dmitry Protasov, Vsevolod Voronov

Quantitative estimates related to the classical Borsuk problem of splitting set in Euclidean space into subsets of smaller diameter are considered. For a given $k$ there is a minimal diameter of subsets at which there exists a covering with $k$ subsets of any planar set of unit diameter. In order to find an upper estimate of the minimal diameter we propose a

Alessandro Bondi, Sergio Pulido, Simone Scotti

We study an extension of the Heston stochastic volatility model that incorporates rough volatility and jump clustering phenomena. In our model, named the rough Hawkes Heston stochastic volatility model, the spot variance is a rough Hawkes-type process proportional to the intensity process of the jump component appearing in the dynamics of the spot variance i

Marcus Hutter

Given well-shuffled data, can we determine whether the data items are statistically (in)dependent? Formally, we consider the problem of testing whether a set of exchangeable random variables are independent. We will show that this is possible and develop tests that can confidently reject the null hypothesis that data is independent and identically distribute

Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He

Traditional machine learning follows a close-set assumption that the training and test set share the same label space. While in many practical scenarios, it is inevitable that some test samples belong to unknown classes (open-set). To fix this issue, Open-Set Recognition (OSR), whose goal is to make correct predictions on both close-set samples and open-set

David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder, Shruti Rijhwani

African languages are spoken by over a billion people, but are underrepresented in NLP research and development. The challenges impeding progress include the limited availability of annotated datasets, as well as a lack of understanding of the settings where current methods are effective. In this paper, we make progress towards solutions for these challenges

Wei Huang, Haiyang Zhang, Nir Shlezinger, Yonina C. Eldar

Dynamic metasurface antennas (DMAs) provide a new paradigm to realize large-scale antenna arrays for future wireless systems. In this paper, we study the downlink millimeter wave (mmWave) DMA systems with limited number of radio frequency (RF) chains. By using a specific DMA structure, an equivalent mmWave channel model is first explicitly characterized. Bas

Yuichi Hiroi, Kiyosato Someya, Yuta Itoh

We propose a spatial calibration method for wide Field-of-View (FoV) Near-Eye Displays (NEDs) with complex image distortions. Image distortions in NEDs can destroy the reality of the virtual object and cause sickness. To achieve distortion-free images in NEDs, it is necessary to establish a pixel-by-pixel correspondence between the viewpoint and the displaye

Mariana-Iuliana Georgescu, Radu Tudor Ionescu, Andreea-Iuliana Miron

Medical image segmentation is an actively studied task in medical imaging, where the precision of the annotations is of utter importance towards accurate diagnosis and treatment. In recent years, the task has been approached with various deep learning systems, among the most popular models being U-Net. In this work, we propose a novel strategy to generate en

Michael A. Lin, Emilio Reyes, Jeannette Bohg, Mark R. Cutkosky

Perceiving the environment through touch is important for robots to reach in cluttered environments, but devising a way to sense without disturbing objects is challenging. This work presents the design and modelling of whisker-inspired sensors that attach to the surface of a robot manipulator to sense its surrounding through light contacts. We obtain a senso

Joaquim Ortiz-Haro, Jung-Su Ha, Danny Driess, Erez Karpas

A factored Nonlinear Program (Factored-NLP) explicitly models the dependencies between a set of continuous variables and nonlinear constraints, providing an expressive formulation for relevant robotics problems such as manipulation planning or simultaneous localization and mapping. When the problem is over-constrained or infeasible, a fundamental issue is to

Dylan Molho, Jiayuan Ding, Zhaoheng Li, Hongzhi Wen

Single-cell technologies are revolutionizing the entire field of biology. The large volumes of data generated by single-cell technologies are high-dimensional, sparse, heterogeneous, and have complicated dependency structures, making analyses using conventional machine learning approaches challenging and impractical. In tackling these challenges, deep learni