May 2022 arXiv papers — page 39

Jonathan Smucker, Mitchell Bredice, Robin Côté, John A. Montgomery

A semi-classical model describing the charge transfer collisions of $C_{60}$ fullerene with different slow ions has been developed to explain available experimental data. This data reveals multiple Breit-Wigner like peaks in the cross sections, with subsequent peaks of reactive cross sections decreasing in magnitude. Calculations of the charge transfer proba

Yu Lu Liu, Rachel Bawden, Thomas Scialom, Benoît Sagot

In text summarization and simplification, system outputs must be evaluated along multiple dimensions such as relevance, factual consistency, fluency, and grammaticality, and a wide range of possible outputs could be of high quality. These properties make the development of an adaptable, reference-less evaluation metric both necessary and challenging. We intr

Thomas Scialom, Tuhin Chakrabarty, Smaranda Muresan

Recent work on large language models relies on the intuition that most natural language processing tasks can be described via natural language instructions. Language models trained on these instructions show strong zero-shot performance on several standard datasets. However, these models even though impressive still perform poorly on a wide range of tasks ou

Tadahiro Taniguchi, Yuto Yoshida, Akira Taniguchi, Yoshinobu Hagiwara

Constructive studies on symbol emergence systems seek to investigate computational models that can better explain human language evolution, the creation of symbol systems, and the construction of internal representations. This study provides a new model for emergent communication, which is based on a probabilistic generative model (PGM) instead of a discrimi

Lu Cheng, Suyu Ge, Huan Liu

Natural Language Processing (NLP) models have been found discriminative against groups of different social identities such as gender and race. With the negative consequences of these undesired biases, researchers have responded with unprecedented effort and proposed promising approaches for bias mitigation. In spite of considerable practical importance, curr

Yau-Shian Wang, Yingshan Chang

Due to the subtleness, implicity, and different possible interpretations perceived by different people, detecting undesirable content from text is a nuanced difficulty. It is a long-known risk that language models (LMs), once trained on corpus containing undesirable content, have the power to manifest biases and toxicity. However, recent studies imply that,

Guido De Philippis, Alessandro Pigati

We prove that every non-degenerate minimal submanifold of codimension two can be obtained as the energy concentration set of a family of critical maps for the (rescaled) Ginzburg-Landau functional. The proof is purely variational, and follows the strategy laid out by Jerrard and Sternberg, extending a recent result for geodesics by Colinet-Jerrard-Sternberg.

Enrique Larios-Vargas, Omar Elazhary, Soroush Yousefi, Derek Lowlind

Implementing software security practices is a critical concern in modern software development. Industry practitioners, security tool providers, and researchers have provided standard security guidelines and sophisticated security development tools to ensure a secure software development pipeline. But despite these efforts, there continues to be an increase i

Prime Karera, Laurent Drissen, Hugo Martel, Jorge Iglesias-Páramo

Spectral data cubes of the interacting pair of galaxies NGC 2535 and NGC 2536 (the Arp 82 system) targeting bright emission lines in the visible band, obtained with the imaging Fourier transform spectrometer (iFTS) SITELLE attached to the Canada-France-Hawaii Telescope (CFHT), are presented. Analysis of H$\upalpha$ velocity maps reveals a bar in $\rm NGC\,25

Aidan San, Yuan Zhuang, Jan Bakus, Colin Lockard

Recently, neural models have been leveraged to significantly improve the performance of information extraction from semi-structured websites. However, a barrier for continued progress is the small number of datasets large enough to train these models. In this work, we introduce the PLAtE (Pages of Lists Attribute Extraction) benchmark dataset as a challengin

Bo Zhang, Alexey Snezhko, Andrey Sokolov

Self-organization phenomena in ensembles of self-propelled particles open pathways to the synthesis of new dynamic states not accessible by traditional equilibrium processes. The challenge is to develop a set of principles that facilitate the control and manipulation of emergent active states. Here, we report that dielectric rolling colloids energized by a p

Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang

Recipe recommendation systems play an essential role in helping people decide what to eat. Existing recipe recommendation systems typically focused on content-based or collaborative filtering approaches, ignoring the higher-order collaborative signal such as relational structure information among users, recipes and food items. In this paper, we formalize the

Bo Zhang, Alexey Snezhko

Large density fluctuations observed in active systems and hyperuniformity are two seemingly incompatible phenomena. However, the formation of hyperuniform states has been recently predicted in non-equilibrium fluids formed by chiral particles performing circular motion with the same handedness. Here we report evidence of hyperuniformity realized in a chiral

Alexandra Fedorova, Keith Smith, Keith Bostic, Alexander Gorrod

Intel OptaneTM DC Persistent Memory resides on the memory bus and approaches DRAM in access latency. One avenue for its adoption is to employ it in place of persistent storage; another is to use it as a cheaper and denser extension of DRAM. In pursuit of the latter goal, we present the design of a volatile Optane NVRAM cache as a component in a storage engin

D. M. Ambrose, M. C. Lopes Filho, H. J. Nussenzveig Lopes

Lei and Lin have recently given a proof of a global mild solution of the three-dimensional Navier-Stokes equations in function spaces based on the Wiener algebra. An alternative proof of existence of these solutions was then developed by Bae, and this new proof allowed for an estimate of the radius of analyticity of the solutions at positive times. We adapt

Chan Young Park, Julia Mendelsohn, Anjalie Field, Yulia Tsvetkov

NLP research on public opinion manipulation campaigns has primarily focused on detecting overt strategies such as fake news and disinformation. However, information manipulation in the ongoing Russia-Ukraine war exemplifies how governments and media also employ more nuanced strategies. We release a new dataset, VoynaSlov, containing 38M+ posts from Russian m

Siddharth Reddy, Sergey Levine, Anca D. Dragan

How can we train an assistive human-machine interface (e.g., an electromyography-based limb prosthesis) to translate a user's raw command signals into the actions of a robot or computer when there is no prior mapping, we cannot ask the user for supervision in the form of action labels or reward feedback, and we do not have prior knowledge of the tasks the us

James Eills, Román Picazo-Frutos, Oksana Bondar, Eleonora Cavallari

State-of-the-art magnetic resonance imaging uses hyperpolarized molecules to track metabolism in vivo, but large superconducting magnets are required, and the strong magnetic fields largely preclude measurement in the presence of conductive materials and magnify problems of magnetic susceptibility inhomogeneity. Operating at zero and low field circumvents th

Pierre Wolinski, Julyan Arbel

The study of feature propagation at initialization in neural networks lies at the root of numerous initialization designs. An assumption very commonly made in the field states that the pre-activations are Gaussian. Although this convenient Gaussian hypothesis can be justified when the number of neurons per layer tends to infinity, it is challenged by both th

Luke Snow, Shashwat Jain, Vikram Krishnamurthy

In mathematical psychology, decision makers are modeled using the Lindbladian equations from quantum mechanics to capture important human-centric features such as order effects and violation of the sure thing principle. We consider human-machine interaction involving a quantum decision maker (human) and a controller (machine). Given a sequence of human decis

Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie

Determinantal Point Processes (DPPs) are a widely used probabilistic model for negatively correlated sets. DPPs have been successfully employed in Machine Learning applications to select a diverse, yet representative subset of data. In these applications, a set of parameters that maximize the likelihood of the data is typically desirable. The algorithms used

Kyle MacMillan, Tarun Mangla, James Saxon, Nicole P. Marwell

Consumers, regulators, and ISPs all use client-based "speed tests" to measure network performance, both in single-user settings and in aggregate. Two prevalent speed tests, Ookla's Speedtest and Measurement Lab's Network Diagnostic Test (NDT), are often used for similar purposes, despite having significant differences in both the test design and implementati

Andrew J. Larkoski

The large-$N_c$ or topologically planar limit of gauge theories can be considered as a classical limit because all gauge bosons are distinguishable particles and therefore cannot exhibit interference. Quantum effects due to the flow of color therefore arise starting at subleading in $1/N_c$. We introduce kinematic observables explicitly sensitive to effects

Machel Reid, Graham Neubig

Most existing sequence generation models produce outputs in one pass, usually left-to-right. However, this is in contrast with a more natural approach that humans use in generating content; iterative refinement and editing. Recent work has introduced edit-based models for various tasks (such as neural machine translation and text style transfer), but these g

Cesar Damian, Oscar Loaiza-Brito

By implementing an error function on a Machine Learning algorithm we look for minimal conditions to construct stable Anti de Sitter and de Sitter vacua from dimensional type IIB String theory compactifcation on K\"ahler manifolds with torsion. This allows to have contributions to the scalar potential from the five-form flux and from D-branes wrapping torsion

Andrew Engel, Zhichao Wang, Anand D. Sarwate, Sutanay Choudhury

We introduce torchNTK, a python library to calculate the empirical neural tangent kernel (NTK) of neural network models in the PyTorch framework. We provide an efficient method to calculate the NTK of multilayer perceptrons. We compare the explicit differentiation implementation against autodifferentiation implementations, which have the benefit of extending

Michael Hahsler

Algorithms that create recommendations based on observed data have significant commercial value for online retailers and many other industries. Recommender systems have a significant research community, and studying such systems is part of most modern data science curricula. While there is an abundance of software that implements recommendation algorithms, t

Fernando Rivas, J. Austin Harris, W. Raphael Hix, O. E. Bronson Messer

Thermonuclear supernovae are the result of the violent unbinding of a white dwarf, but the precise nature of the explosion mechanism(s) is a matter of active debate. To this end, several specific scenarios have been proposed to explain the observable traits of SNe Ia. A promising pathway is the double-detonation scenario, where a white dwarf accretes a shell

Stella T. Schindler, Iain W. Stewart, Yong Zhao

Transverse-momentum-dependent parton distributions (TMDs) can be calculated from first principles by computing a related set of Euclidean lattice observables and connecting them via a factorization formula. This work focuses on the leading-power factorization formula connecting the lattice quasi-TMD and continuum Collins TMD for gluons. We calculate the one-

Frank Perri, Shah J Miah, Steve Zanon, Keis Ohtsuka

The aged care sector in Australia faces significant challenges. While many of these issues have been clearly identified, their urgency has been further highlighted during the COVID-19 pandemic. Technology such as in-home monitoring is one way to address some of these challenges. However, the efficacy of technology must be considered together with its impleme

Heng-Yi Wu, Jingqing Zhang, Julia Ive, Tong Li

Structured (tabular) data in the preclinical and clinical domains contains valuable information about individuals and an efficient table-to-text summarization system can drastically reduce manual efforts to condense this data into reports. However, in practice, the problem is heavily impeded by the data paucity, data sparsity and inability of the state-of-th

Rob Claes, Karl Meerbergen, Simon Telen

Solving polynomial eigenvalue problems with eigenvector nonlinearities (PEPv) is an interesting computational challenge, outside the reach of the well-developed methods for nonlinear eigenvalue problems. We present a natural generalization of these methods which leads to a contour integration approach for computing all eigenvalues of a PEPv in a compact regi

Dmitry Kleinbock, Jiajie Zheng

In the study of some dynamical systems the limsup set of a sequence of measurable sets is often of interest. The shrinking targets and recurrence are two of the most commonly studied problems that concern limsup sets. However, the zero-one laws for the shrinking targets and recurrence are usually treated separately and proved differently. In this paper, we i

Meyer Scetbon, Marco Cuturi

The matching principles behind optimal transport (OT) play an increasingly important role in machine learning, a trend which can be observed when OT is used to disambiguate datasets in applications (e.g. single-cell genomics) or used to improve more complex methods (e.g. balanced attention in transformers or self-supervised learning). To scale to more challe

Esteban Marulanda, Alejandro Restrepo, Johans Restrepo

In classical physics there is a well-known theorem in which it is established that the energy per degree of freedom is the same. However, in quantum mechanics due to the non-commutativity of some pairs of observables and the possibility of having non-Markovian dynamics, the energy is not equally distributed. We propose a correspondence between what we know a

Sebastian Krügel, Matthias Uhl

Is the ethics of autonomous vehicles (AVs) restricted to weighing lives in unavoidable accidents? We argue that AVs distribute risks between road users in regular traffic situations, either explicitly or implicitly. This distribution of risks raises ethically relevant questions that cannot be evaded by simple heuristics such as "hitting the brakes." Using an

Dingding Dong, Nitya Mani, Yufei Zhao

We show that for a fixed $q$, the number of $q$-ary $t$-error correcting codes of length $n$ is at most $2^{(1 + o(1)) H_q(n,t)}$ for all $t \leq (1 - q^{-1})n - C_q\sqrt{n \log n}$ (for sufficiently large constant $C_q$), where $H_q(n, t) = q^n / V_q(n,t)$ is the Hamming bound and $V_q(n,t)$ is the cardinality of the radius $t$ Hamming ball. This proves a c

Joeri van Leeuwen, Eric Kooistra, Leon Oostrum, Liam Connor

Fast Radio Bursts must be powered by uniquely energetic emission mechanisms. This requirement has eliminated a number of possible source types, but several remain. Identifying the physical nature of Fast Radio Burst (FRB) emitters arguably requires good localisation of more detections, and broadband studies enabled by real-time alerting. We here present the

James Matuk, Amy H. Herring, David B. Dunson

Functional factor analysis is an important dimension reduction method for functional and longitudinal data. Factor loadings give insight into patterns of variability of the observations, while latent factors provide a low-dimensional representation of the data that is useful for inferential tasks. Constraining the functional factor loadings to be mutually or

Ruiyi Zhou, Dillon C. Yost, Yosuke Kanai

We demonstrate nonadiabatic Thouless pumping of electrons in trans-polyacetylene in the framework of Floquet engineering using first-principles theory. We identify the regimes in which the quantized pump is operative with respect to the driving electric field for a time-dependent Hamiltonian. By employing the time-dependent maximally localized Wannier functi

Omar Alomari, Mohammad Abudayah, Manal Ghanem

The $\alpha$-Hermitian adjacency matrix $H_\alpha$ of a mixed graph $X$ has been recently introduced. It is a generalization of the adjacency matrix of unoriented graphs. In this paper, we consider a special case of the complex number $\alpha$. This enables us to define an incidence matrix of mixed graphs. Consequently, we define a generalization of line gra

Wenhao Wang, Yifan Sun, Yi Yang

Image copy detection (ICD) aims to determine whether a query image is an edited copy of any image from a reference set. Currently, there are very limited public benchmarks for ICD, while all overlook a critical challenge in real-world applications, i.e., the distraction from hard negative queries. Specifically, some queries are not edited copies but are inhe

G. M. Viswanathan, M. A. G. Portillo, E. P. Raposo, M. G. E. da Luz

Exact solution of the Ising model on the simple cubic lattice is one of the long-standing open problems in rigorous statistical mechanics. Indeed, it is generally believed that settling it would constitute a methodological breakthrough, fomenting great prospects for further application, similarly to what happened when Lars Onsager solved the two dimensional

Rafael de la Llave, Maria Saprykina

\def\G{\mathcal G} \def\M{\mathcal M} \def\cE{\mathcal E} We prove an analog of Liv\v{s}ic theorem for real-analytic families of cocycles over an integrable system with values in a Banach algebra $\G$ or a Lie group. Namely, we consider an integrable dynamical system $f:\M \equiv\torus^d \times [-1,1]^d\to \M$, $f(\theta, I)=(\theta + I, I)$, and a real-anal

Claudio Fontana, Alessandro Gnoatto, Guillaume Szulda

We introduce and study the class of CBI-time-changed L\'evy processes (CBITCL), obtained by time-changing a L\'evy process with respect to an integrated continuous-state branching process with immigration (CBI). We characterize CBITCL processes as solutions to a certain stochastic integral equation and relate them to affine stochastic volatility processes. W

Zhiyu Dong, Andrey V. Chubukov, Leonid Levitov

The quest for unconventional superconductivity governed by Coulomb repulsion between electrons rather than phonon attraction received new momentum with the advent of moir\'e graphene. Initially, delineating the phonon and Coulomb-repulsion-based pairing mechanisms has proven to be a challenging task, however the situation has changed after recent discovery o

Nitish K. Panigrahy, Prajit Dhara, Don Towsley, Saikat Guha

Recent technological advancements in satellite based quantum communication has made it a promising technology for realizing global scale quantum networks. Due to better loss distance scaling compared to ground based fiber communication, satellite quantum communication can distribute high quality quantum entanglements among ground stations that are geographic

Guillermo Gambini, Pedro C. de Holanda, Saulo Carneiro

Popular extensions of the standard model of particle physics feature new fields and symmetries which could, for example, dynamically generate neutrino masses from $B-L$ spontaneous symmetry breaking. If a new light scalar that decays into dark radiation appears in the spectrum of the theory, it could significantly modify the cosmological observables. In this

Shahaf E. Finder, Yair Zohav, Maor Ashkenazi, Eran Treister

Convolutional Neural Networks (CNNs) are known for requiring extensive computational resources, and quantization is among the best and most common methods for compressing them. While aggressive quantization (i.e., less than 4-bits) performs well for classification, it may cause severe performance degradation in image-to-image tasks such as semantic segmentat

Sanjida Akter Sharna, Sheikh Ashraf Ali

Preservation of information and computer security is broadly dependent on the secured authentication system which is underpinned by password. Text based password is a commonly used and available system for authentication. But it bears many limitations like shoulder surfing, dictionary attack, Phishing, guessing the password etc. In order to overwhelm these v

Yong-Geun Oh

In the present article, we provide analytic foundation of the following nonlinear elliptic system, called the \emph{Hamiltonian-perturbed contact instanton equation}, $$ (du - X_H \otimes \gamma)^{\pi(0,1)} = 0, \quad d(e^{g_{H, u}}u^*(\lambda + H \otimes \gamma)\circ j) = 0 $$ associated to a contact triad $(M,\lambda,J)$ and contact Hamiltonian $H$ and its

Sudheesh Singanamalla, Apurv Mehra, Nishanth Chandran, Himanshi Lohchab

The use of blockchain in regulatory ecosystems is a promising approach to address challenges of compliance among mutually untrusted entities. In this work, we consider applications of blockchain technologies in telecom regulations. In particular, we address growing concerns around Unsolicited Commercial Communication (UCC aka. spam) sent through text message

Fortino Garcia, Daniel Appelö, Olof Runborg

In this paper we extend analysis of the WaveHoltz iteration -- a time-domain iterative method for the solution of the Helmholtz equation. We expand the previous analysis of energy conserving problems and prove convergence of the WaveHoltz iteration for problems with impedance boundary conditions in a single spatial dimension. We then consider interior Dirich

Primoz Skraba, D. Yogeshwaran

We investigate asymptotics for the minimal spanning acycles of the (Alpha)-Delaunay complex on a stationary Poisson process on $\mathbb{R}^d, d \geq 2$. Minimal spanning acycles are topological (or higher-dimensional) generalization of minimal spanning trees. We establish a central limit theorem for total weight of the minimal spanning acycle on a Poisson-De

Venktesh V, Md. Shad Akhtar, Mukesh Mohania, Vikram Goyal

Online learning platforms conduct exams to evaluate the learners in a monotonous way, where the questions in the database may be classified into Bloom's Taxonomy as varying levels in complexity from basic knowledge to advanced evaluation. The questions asked in these exams to all learners are very much static. It becomes important to ask new questions with d

Bo Fan, Antonio M. García-García

We study the interplay of vortices and disorder in a two-dimensional disordered superconductor at zero temperature described by the Bogoliubov-de Gennes (BdG) self-consistent formalism for lattices of sizes up to $100\times100$ where the magnetic flux is introduced by the Peierls's substitution. The substantial larger size than in previous approaches ($\leq

Ankit Kumar, Sandeep Kumar Kataria

Cosmological simulations predict more classical bulges than their observational counterpart in the local Universe. Here, we quantify evolution of the bulges since $z=0.1$ using photometric parameters of nearly 39,000 unbarred disc galaxies from SDSS DR7 which are well represented by two components. We adopted a combination of the S\'ersic index and Kormendy

Jani A. Virtanen

In this note known formulas for the product of Toeplitz operators are revisited in the context of their applications to the study of Fredholmness, boundedness of Toeplitz products, and the Berezin-Toeplitz quantization. A few open problems are also mentioned.

Daniel Appelö, Fortino Garcia, Allen Alvarez Loya, Olof Runborg

We consider the application of the WaveHoltz iteration to time-harmonic elastic wave equations with energy conserving boundary conditions. The original WaveHoltz iteration for acoustic Helmholtz problems is a fixed-point iteration that filters the solution of the wave equation with time-harmonic forcing and boundary data. As in the original WaveHoltz method,

Rocco Palmitessa, Morten Grum, Allan Peter Engsig-Karup, Roland Löwe

We propose and demonstrate a new approach for fast and accurate surrogate modelling of urban drainage system hydraulics based on physics-guided machine learning. The surrogates are trained against a limited set of simulation results from a hydrodynamic (HiFi) model. Our approach reduces simulation times by one to two orders of magnitude compared to a HiFi mo

Jiang-Tao Li, Q. Daniel Wang, Theresa Wiegert, Joel N. Bregman

AGN bubbles could play an important role in accelerating high-energy CRs and galactic feedback. Only in nearby galaxies could we have high enough angular resolution in multi-wavelengths to study the sub-kpc environment of the AGN, where the bubbles are produced and strongly interact with the surrounding ISM. In this paper, we present the latest Chandra obser

Marc Tanti, Shaun Abdilla, Adrian Muscat, Claudia Borg

Current image description generation models do not transfer well to the task of describing human faces. To encourage the development of more human-focused descriptions, we developed a new data set of facial descriptions based on the CelebA image data set. We describe the properties of this data set, and present results from a face description generator train

Fernando W. Rossine, Gabriel Vercelli, Corina E. Tarnita, Thomas Gregor

Predators and their foraging strategies often determine ecosystem structure and function. Yet, the role of protozoan predators in microbial soil ecosystems remains elusive despite the importance of these ecosystems to global biogeochemical cycles. In particular, amoebae -- the most abundant soil protozoan predators of bacteria -- remineralize soil nutrients

Till Koebe, Alejandra Arias-Salazar

Household survey programs around the world publish fine-granular georeferenced microdata to support research on the interdependence of human livelihoods and their surrounding environment. To safeguard the respondents' privacy, micro-level survey data is usually (pseudo)-anonymized through deletion or perturbation procedures such as obfuscating the true locat

Vasu Goel, Dhruv Sahnan, Venktesh V, Gaurav Sharma

Online education platforms are powered by various NLP pipelines, which utilize models like BERT to aid in content curation. Since the inception of the pre-trained language models like BERT, there have also been many efforts toward adapting these pre-trained models to specific domains. However, there has not been a model specifically adapted for the education

Shahab Mahdian, Michael A. Nitsche, Vahid Nejati

The perspective-taking in social cognition is an ability that makes third-person judgments about the intentions, beliefs and thoughts of others. We aimed to investigate gender differences in the neural structure differences in (non) emotional perspective-taking ability.Thirty healthy adults (15 females and 15 males) received anodal and sham transcranial dire

Diab W. Abueidda, Seid Koric, Erman Guleryuz, Nahil A. Sobh

Physics-informed neural networks have gained growing interest. Specifically, they are used to solve partial differential equations governing several physical phenomena. However, physics-informed neural network models suffer from several issues and can fail to provide accurate solutions in many scenarios. We discuss a few of these challenges and the technique

Anders M. Buvarp, Robert M. Taylor, Kumar Vijay Mishra, Lamine M. Mili

Recent research in ultra-reliable and low latency communications (URLLC) for future wireless systems has spurred interest in short block-length codes. In this context, we analyze arbitrary harmonic bandwidth (BW) expansions for a class of high-dimension constant curvature curve codes for analog error correction of independent continuous-alphabet uniform sour

Haiteng Zhao, Chang Ma, Xinshuai Dong, Anh Tuan Luu

Deep learning models have achieved great success in many fields, yet they are vulnerable to adversarial examples. This paper follows a causal perspective to look into the adversarial vulnerability and proposes Causal Intervention by Semantic Smoothing (CISS), a novel framework towards robustness against natural language attacks. Instead of merely fitting obs

Ryno Laubscher, Johan Van Der Merwe, Jacques Liebenberg, Philip Herbst

Accurate estimates of left ventricle elastances based on non-invasive measurements are required for clinical decision-making during treatment of valvular diseases. The present study proposes a parameter discovery approach based on a lumped parameter model of the cardiovascular system in conjunction with optimization and non-invasive, clinical input measureme

Matthew Mould, Davide Gerosa, Floor S. Broekgaarden, Nathan Steinle

Population inference of gravitational-wave catalogues is a useful tool to translate observations of black-hole mergers into constraints on compact-binary formation. Different formation channels predict identifiable signatures in the astrophysical distributions of source parameters, such as masses and spins. One example within the scenario of isolated binary

Ahmed Nassar, Ebru Sezer

In this study, we aimed to improve the performance results of Arabic sentiment analysis. This can be achieved by investigating the most successful machine learning method and the most useful feature vector to classify sentiments in both term and document levels into two (positive or negative) categories. Moreover, specification of one polarity degree for the

Sharadhi Alape Suryanarayana, David Sarne, Sarit Kraus

In many social-choice mechanisms the resulting choice is not the most preferred one for some of the participants, thus the need for methods to justify the choice made in a way that improves the acceptance and satisfaction of said participants. One natural method for providing such explanations is to ask people to provide them, e.g., through crowdsourcing, an

Limor Gultchin, Vincent Cohen-Addad, Sophie Giffard-Roisin, Varun Kanade

Among the various aspects of algorithmic fairness studied in recent years, the tension between satisfying both \textit{sufficiency} and \textit{separation} -- e.g. the ratios of positive or negative predictive values, and false positive or false negative rates across groups -- has received much attention. Following a debate sparked by COMPAS, a criminal just

Uta Bilow, Kenneth Cecire

International Masterclasses (IMC) enable high school students and teachers to work with particle physicists to analyze authentic data from contemporary experiments and experience being "physicists for a day". The IMC program has a worldwide reach, including several universities and research institutes in Egypt, Algeria, Morocco, Sao Tom'e and Principe, and S

Yuchen Liu, Joaquín Moraga, Hendrik Süß

In this article we study conjectures regarding normalized volume and boundedness of singularities. We focus on singularities with a torus action of complexity 1, threefold singularities, and hypersurface singularities. Given a real value v>0, we prove that the class of K-semistable threefold singularities with normalized volume at least v forms a bounded fam

Matthew B. Hastings

The sum-of-squares (SoS) hierarchy is a powerful technique based on semi-definite programming that can be used for both classical and quantum optimization problems. This hierarchy goes under several names; in particular, in quantum chemistry it is called the reduced density matrix (RDM) method. We consider the ability of this hierarchy to reproduce weak coup

Ferenc Illés

We introduce the notion of linearly representable games. Broadly speaking, these are TU games that can be described by as many parameters as the number of players, like weighted voting games, airport games, or bankruptcy games. We show that the Shapley value calculation is pseudo-polynomial for linearly representable games. This is a generalization of many c

Silviu Paun, Juntao Yu, Nafise Sadat Moosavi, Massimo Poesio

Anaphoric reference is an aspect of language interpretation covering a variety of types of interpretation beyond the simple case of identity reference to entities introduced via nominal expressions covered by the traditional coreference task in its most recent incarnation in ONTONOTES and similar datasets. One of these cases that go beyond simple coreference

Md Mahmudul Hasan, Tasnim Ibn Faiz, Alicia Sasser Modestino, Gary J. Young

Opioid Use Disorder (OUD) has reached an epidemic level in the US. Diversion of unused prescription opioids to secondary users and black market significantly contributes to the abuse and misuse of these highly addictive drugs, leading to the increased risk of OUD and accidental opioid overdose within communities. Hence, it is critical to design effective str

Roberto Zucchini

This is the second of a series of two papers devoted to the partition function realization of Wilson surfaces in strict higher gauge theory. A higher 2--dimensional counterpart of the topological coadjoint orbit quantum mechanical model computing Wilson lines is presented based on the derived geometric framework, which has shown its usefulness in 4--dimensio

Roberto Zucchini

This is the first of a series of two papers devoted to the partition function realization of Wilson surfaces in strict higher gauge theory. A higher version of the Kirillov-Kostant-Souriau theory of coadjoint orbits is presented based on the derived geometric framework, which has shown its usefulness in 4--dimensional higher Chern--Simons theory. An original

Nex C. X. Stuhlmüller, Thomas M. Fischer, Daniel de las Heras

We simulate the transport of colloidal particles driven by a static and homogeneous drift force, and subject to the optical potential created by two lattices of optical tweezers. The lattices of optical tweezers are parallel to each other, shifted, and rotated by a twist angle. Due to a negative interference between the potential of the two lattices, flat ch

Bo He, Xiang Song, Vincent Gao, Christos Faloutsos

Low-quality listings and bad actor behavior in online retail websites threatens e-commerce business as these result in sub-optimal buying experience and erode customer trust. When a new listing is created, how to tell it has good-quality? Is the method effective, fast, and scalable? Previous approaches often have three limitations/challenges: (1) unable to h

Chunhua Li, Nakib H Protik, Pablo Ordejón, David Broido

Diamond is one of the most studied materials because of its unique combination of remarkable electrical, mechanical, thermal and optical properties. Using a fully self-consistent ab initio theory of coupled electron-phonon transport, we reveal another striking behavior: a huge drag enhancement of the thermopower of lightly doped diamond. Thermopower values o

Elena Di Domenico, Carmine Monetta, Marialaura Noce

Let $G$ be a finite group of order $n$, and denote by $\rho(G)$ the product of element orders of $G$. The aim of this work is to provide some upper bounds for $\rho(G)$ depending only on $n$ and on its least prime divisor, when $G$ belongs to some classes of non-cyclic groups.

Hongzhi Huang

In this paper, we present finite topological type theorems for open manifolds with non-negative Ricci curvature, under almost maximal local rewinding volume. Unlike previous related research, our theorems remove the constraints of sectional curvature or conjugate radius, which were crucial additional assumptions on metric regularity in prior results. Notably

Hamid Arian Zad, Azam Zoshki, Nerses Ananikian, Michal Jaščur

The whole entanglement measure so-called geometric $\Pi_4$ average of tangles and bipartite entanglement of the antiferromagnetic spin-1/2 XXX Heisenberg model on a tetranuclear square cluster with cyclic four-spin interaction are rigorously examined by the help of thermal negativities. The model comprises two nearest-neighbor exchange couplings $J_1$ and $J

Eduardo M. Castro, Marcelo V. Flamarion, Roberto Ribeiro-Jr

The study of the Euler equations in flows with constant vorticity has piqued the curiosity of a considerable number of researchers over the years. Much research has been conducted on this subject under the assumption of steady flow. In this work, we provide a numerical approach that allows us to compute solitary waves in flows with constant vorticity and ana

Eric Naslund

Let $A\subset\mathbb{R}_{>0}$ be a finite set of distances, and let $G_{A}(\mathbb{R}^{n})$ be the graph with vertex set $\mathbb{R}^{n}$ and edge set $\{(x,y)\in\mathbb{R}^{n}:\ \|x-y\|_{2}\in A\}$, and let $\chi(\mathbb{R}^{n},A)=\chi\left(G_{A}(\mathbb{R}^{n})\right)$. Erd\H{o}s asked about the growth rate of the $m$-distance chromatic number \[ \bar{\chi

Fabrício Ceschin, Marcus Botacin, Heitor Murilo Gomes, Felipe Pinagé

Malware is a major threat to computer systems and imposes many challenges to cyber security. Targeted threats, such as ransomware, cause millions of dollars in losses every year. The constant increase of malware infections has been motivating popular antiviruses (AVs) to develop dedicated detection strategies, which include meticulously crafted machine learn

Cecilia Y. Chen, Jared S. Ginsberg, Samuel L. Moore, M. Mehdi Jadidi

Manipulating the nanostructure of materials is critical for numerous applications in electronics, magnetics, and photonics. However, conventional methods such as lithography and laser-writing require cleanroom facilities or leave residue. Here, we describe a new approach to create atomically sharp line defects in hexagonal boron nitride (hBN) at room tempera

Chi-Liang Liu, Hung-yi Lee, Wen-tau Yih

We propose structured prompt tuning, a simple and effective method to improve prompt tuning. Instead of prepending a sequence of tunable embeddings to the input, we generate the soft prompt embeddings through a hypernetwork. Our approach subsumes the standard prompt tuning, allows more flexibility in model design and can be applied to both single-task and mu

Arkady Onishchik

Here, I study the problem of classification of non-split supermanifolds having as retract the split supermanifold $(M,\Omega)$, where $\Omega$ is the sheaf of holomorphic forms on a given complex manifold $M$ of dimension $> 1$. I propose a general construction associating with any $d$-closed $(1,1)$-form $\omega$ on $M$ a supermanifold with retract $(M,\Ome

Michael Howard

Deploying an application into a Kubernetes cluster requires sending a manifest file to the cluster's control plane interface. This action is typically performed through a kubectl client which is configured and authorized to communicate with the control plane's Uniform Resource Locator (URL). An application typically requires many Kubernetes resources such as

Aleksandros Sobczyk, Mathieu Luisier

A classical result of Johnson and Lindenstrauss states that a set of $n$ high dimensional data points can be projected down to $O(\log n/\epsilon^2)$ dimensions such that the square of their pairwise distances is preserved up to a small distortion $\epsilon\in(0,1)$. It has been proved that the JL lemma is optimal for the general case, therefore, improvement

Matthew W. Cotton, Ramin Golestanian, Jaime Agudo-Canalejo

We present a thermodynamically consistent model describing the dynamics of a multi-component mixture where one enzyme component catalyzes a reaction between other components. We find that the catalytic activity alone can induce phase separation for sufficiently active systems and large enzymes, without any equilibrium interactions between components. In the

Xuemiao Chen

In this paper, we first prove a complete version of the Donaldson-Uhlenbeck-Yau theorem over normal varieties, including normal Kaehler varieties and projective normal varieties with multiple polarizations. In particular, this gives the polystability of reflexive sheaves under symmetric and exterior powers and tensor products. As a consequence of the singula

Ngoc-Quan Pham, Alex Waibel, Jan Niehues

Multilingual speech recognition with supervised learning has achieved great results as reflected in recent research. With the development of pretraining methods on audio and text data, it is imperative to transfer the knowledge from unsupervised multilingual models to facilitate recognition, especially in many languages with limited data. Our work investigat

Scott Lawrence, Hyunwoo Oh, Yukari Yamauchi

Lattice scalar field theories encounter a sign problem when the coupling constant is complex. This is a close cousin of the real-time sign problems that afflict the lattice Schwinger-Keldysh formalism, and a more distant relative of the fermion sign problem that plagues calculations of QCD at finite density. We demonstrate the methods of complex normalizing