July 2023 arXiv papers — page 140

Han Wu, Lei Chen, Paul Malinowski, Jianwei Huang

The ability to reversibly toggle between two distinct states in a non-volatile method is important for information storage applications. Such devices have been realized for phase-change materials, which utilizes local heating methods to toggle between a crystalline and an amorphous state with distinct electrical properties. To expand such kind of switching b

Kate Sanders, David Etter, Reno Kriz, Benjamin Van Durme

Everyday news coverage has shifted from traditional broadcasts towards a wide range of presentation formats such as first-hand, unedited video footage. Datasets that reflect the diverse array of multimodal, multilingual news sources available online could be used to teach models to benefit from this shift, but existing news video datasets focus on traditiona

Giuseppe Longobardi, Alessandro Treves

Parametric approaches to grammatical diversity range from Chomsky's 1981 classical Principles & Parameters model to minimalist reinterpretations: in some proposals of the latter framework, parameters need not be an extensional list given at the initial state S0 of the mind, but can be constructed through a bio-program in the course of language development. I

Vittorio De Falco

Epicyclic frequencies are usually observed in X-ray binaries and constitute a powerful astrophysical mean to probe the strong gravitational field around a compact object. We consider them in the equatorial plane around a general stationary and axially symmetric wormhole. We first search for the wormholes' existence, distinguishing them from a Kerr black hole

Dmitry Galakhov, Alexei Morozov, Nikita Tselousov

We explicitly construct cut-and-join operators and their eigenfunctions -- the Super-Schur functions -- for the case of the affine super-Yangian $\mathsf{Y}(\widehat{\mathfrak{gl}}_{1|1})$. This is the simplest non-trivial (semi-Fock) representation, where eigenfunctions are labeled by the superanalogue of 2d Young diagrams, and depend on the supertime varia

Lawrence Frolov, Samuel Leigh, A. Shadi Tahvildar-Zadeh

In this paper we prove that the static solution of the Cauchy problem for a massless real scalar field that is sourced by a point charge in $1+1$ dimensions is asymptotically stable under perturbation by compactly-supported radiation. This behavior is due to the process of back-reaction. Taking the approach of Kiessling, we rigorously derive the expression f

Severin Diepolder, Andrea Araldo, Tarek Chouaki, Santa Maiti

Shared Mobility Services (SMS), e.g., Demand-Responsive Transit (DRT) or ride-sharing, can improve mobility in low-density areas, often poorly served by conventional Public Transport (PT). Such improvement is mostly quantified via basic performance indicators, like wait or travel time. However, accessibility indicators, measuring the ease of reaching surroun

Shrey Aryan, Matthew Rosenzweig, Gigliola Staffilani

Motivated by the possibility of noise to cure equations of finite-time blowup, recent work arXiv:2109.09892 by the second and third named authors showed that with quantifiable high probability, random diffusion restores global existence for a large class of active scalar equations in arbitrary dimension with possibly singular velocity fields. This class incl

Artur Alho, José Natário, Paolo Pani, Guilherme Raposo

The purpose of this review it to present a renewed perspective of the problem of self-gravitating elastic bodies under spherical symmetry. It is also a companion to the papers [Phys. Rev. D105, 044025 (2022)], [Phys. Rev. D106, L041502 (2022)], and [arXiv:2306.16584 [gr-qc]], where we introduced a new definition of spherically symmetric elastic bodies in gen

Martin Bojowald, Ari Gluckman

A recent quasiclassical description of a tunneling universe model is shown to exhibit chaotic dynamics by an analysis of fractal dimensions in the plane of initial values. This result relies on non-adiabatic features of the quantum dynamics, captured by new quasiclassical methods. Chaotic dynamics in the early universe, described by such models, implies that

Kim Klinger-Logan, Ksenia Fedosova

In \cite{CGPWW2021}, it was conjectured that a particular shifted sum of even divisor sums vanishes, and in \cite{SDK}, a formal argument was given for this vanishing. Shifted convolution sums of this form appear when computing the Fourier expansion of coefficients for the low energy scattering amplitudes in type IIB string theory \cite{GMV2015} and have app

Claudio Andrea Manzari, Jorge Martin Camalich, Jonas Spinner, Robert Ziegler

Proto-neutron stars formed during core-collapse supernovae are hot and dense environments that contain a sizable population of muons. If these interact with new long-lived particles with masses up to roughly 100 MeV, the latter can be produced and escape from the stellar plasma, causing an excessive energy loss constrained by observations of SN 1987A. In thi

Debojyoti Garain, Pritam Banerjee, Shaswata Chowdhury, Tapobrata Sarkar

Low energy imprints of modifications to general relativity are often found in pressure balance equations inside stars. These modifications are then amenable to tests via astrophysical phenomena, using observational effects in stellar astrophysics that crucially depend on such equations. One such effect is tidal disruption of stars in the vicinity of black ho

Yu-Mei Wu, Zu-Cheng Chen, Qing-Guo Huang

The pulsar timing array (PTA) collaborations have recently reported compelling evidence for the presence of a stochastic signal consistent with a gravitational-wave background. In this letter, we combine the latest data sets from NANOGrav, PPTA and EPTA collaborations to explore the cosmological interpretations for the detected signal from first-order phase

Andrea Ottolini, Stefan Steinerberger

We consider the optimal transport problem between a set of $n$ red points and a set of $n$ blue points subject to a concave cost function such as $c(x,y) = \|x-y\|^{p}$ for $0< p < 1$. Our focus is on a particularly simple matching algorithm: match the closest red and blue point, remove them both and repeat. We prove that it provides good results in any metr

Yacine Aoun, Sébastien Ott, Yvan Velenik

The motivation for this paper is the analysis of the fixed-density Ising lattice gas in the presence of a gravitational field. This is a seen as a particular instance of an Ising model with a slowly varying magnetic field in the fixed magnetization ensemble. We first characterize the typical magnetization profiles in the regime in which the contribution of t

Xie-Hang Yu, Zhiyuan Wang, Pavel Kos

Quantum dynamics with local interactions in lattice models display rich physics, but is notoriously hard to study. Dual-unitary circuits allow for exact answers to interesting physical questions in clean or disordered one- and higher-dimensional quantum systems. However, this family of models shows some non-universal features, like vanishing correlations ins

Seher Ozcelik, Sinan Unver, Ilke Ali Gurses, Rustu Turkay

Segmentation networks are not explicitly imposed to learn global invariants of an image, such as the shape of an object and the geometry between multiple objects, when they are trained with a standard loss function. On the other hand, incorporating such invariants into network training may help improve performance for various segmentation tasks when they are

Ilayda Canyakmaz, Wayne Lin, Georgios Piliouras, Antonios Varvitsiotis

We study online convex optimization where the possible actions are trace-one elements in a symmetric cone, generalizing the extensively-studied experts setup and its quantum counterpart. Symmetric cones provide a unifying framework for some of the most important optimization models, including linear, second-order cone, and semidefinite optimization. Using to

Xuanlin Li, Yunhao Fang, Minghua Liu, Zhan Ling

Large vision-language models have achieved outstanding performance, but their size and computational requirements make their deployment on resource-constrained devices and time-sensitive tasks impractical. Model distillation, the process of creating smaller, faster models that maintain the performance of larger models, is a promising direction towards the so

Markus Anderljung, Joslyn Barnhart, Anton Korinek, Jade Leung

Advanced AI models hold the promise of tremendous benefits for humanity, but society needs to proactively manage the accompanying risks. In this paper, we focus on what we term "frontier AI" models: highly capable foundation models that could possess dangerous capabilities sufficient to pose severe risks to public safety. Frontier AI models pose a distinct r

Alberto Montina, Stefan Wolf

A projective measurement cannot decrease the von Neumann entropy if the outcome is ignored. However, under certain sound assumptions and using the quantum violation of Leggett-Garg inequalities, we have previously demonstrated that this property is not inherited by a classical simulation of such a measurement process. In the simulation, a measurement erases

Yongcan Yu, Lijun Sheng, Ran He, Jian Liang

Test-time adaptation (TTA) is a technique aimed at enhancing the generalization performance of models by leveraging unlabeled samples solely during prediction. Given the need for robustness in neural network systems when faced with distribution shifts, numerous TTA methods have recently been proposed. However, evaluating these methods is often done under dif

Pratyush Maini, Sachin Goyal, Zachary C. Lipton, J. Zico Kolter

Large web-sourced multimodal datasets have powered a slew of new methods for learning general-purpose visual representations, advancing the state of the art in computer vision and revolutionizing zero- and few-shot recognition. One crucial decision facing practitioners is how, if at all, to curate these ever-larger datasets. For example, the creators of the

Yiming Yan, Tao Wang, Chengqi Zhao, Shujian Huang

Automatic metrics play a crucial role in machine translation. Despite the widespread use of n-gram-based metrics, there has been a recent surge in the development of pre-trained model-based metrics that focus on measuring sentence semantics. However, these neural metrics, while achieving higher correlations with human evaluations, are often considered to be

Zijun Yao, Yuanyong Chen, Xin Lv, Shulin Cao

We present Visual Knowledge oriented Programming platform (VisKoP), a knowledge base question answering (KBQA) system that integrates human into the loop to edit and debug the knowledge base (KB) queries. VisKoP not only provides a neural program induction module, which converts natural language questions into knowledge oriented program language (KoPL), but

Jonathan Pei, Kevin Yang, Dan Klein

We propose Prefix-Adaptive Decoding (PREADD), a flexible method for controlled text generation. Unlike existing methods that use auxiliary expert models to control for attributes, PREADD does not require an external model, instead relying on linearly combining output logits from multiple prompts. Specifically, PREADD contrasts the output logits generated usi

April Qiu Cheng, Michael Zevin, Salvatore Vitale

One of the goals of gravitational-wave astrophysics is to infer the number and properties of the formation channels of binary black holes (BBHs); to do so, one must be able to connect various models with the data. We explore benefits and potential issues with analyses using models informed by population synthesis. We consider 5 possible formation channels of

Morten Akhøj, James Benn, Erlend Grong, Stefan Sommer

In this paper we demonstrate how sub-Riemannian geometry can be used for manifold learning and surface reconstruction by combining local linear approximations of a point cloud to obtain lower dimensional bundles. Local approximations obtained by local PCAs are collected into a rank $k$ tangent subbundle on $\mathbb{R}^d$, $k<d$, which we call a principal sub

Petr Gurka, Jan Lang, Zdeněk Mihula

Optimal weighted Sobolev-Lorentz embeddings with homogeneous weights in open convex cones are established, with the exact value of the optimal constant. These embeddings are non-compact, and this paper investigates the structure of their non-compactness quantitatively. Opposite to the previous results in this direction, the non-compactness in this case does

Valerio Arnaboldi, Mattia Giovanni Campana, Franca Delmastro

Wi-Fi Direct is a promising technology for the support of device-to-device communications (D2D) on commercial mobile devices. However, the standard as-it-is is not sufficient to support the real deployment of networking solutions entirely based on D2D such as opportunistic networks. In fact, WiFi Direct presents some characteristics that could limit the auto

Apoorva Khare

Recently, a general version of the Hoffmann-Jorgensen inequality was shown jointly with Rajaratnam [Ann. Probab. 2017], which (a) improved the result even for real-valued variables, but also (b) simultaneously unified and extended several versions in the Banach space literature, including that by Hitczenko and Montgomery-Smith [Ann. Probab. 2001], as well as

Dominique Rathel-Fournier

We study Lagrangian cobordism groups of closed symplectic surfaces of genus $g \geq 2$ whose relations are given by unobstructed, immersed Lagrangian cobordisms. Building upon work of Abouzaid and Perrier, we compute these cobordism groups and show that they are isomorphic to the Grothendieck group of the derived Fukaya category of the surface. The proofs re

Yannick Couzinie, Yusuke Nishiya, Hirofumi Nishi, Taichi Kosugi

We propose an annealing scheme usable on modern Ising machines for crystal structures prediction (CSP) by taking into account the general n-body atomic interactions, and in particular three-body interactions which are necessary to simulate covalent bonds. The crystal structure is represented by discretizing a unit cell and placing binary variables which expr

Sneha Singhania, Simon Razniewski, Gerhard Weikum

The widespread usage of latent language representations via pre-trained language models (LMs) suggests that they are a promising source of structured knowledge. However, existing methods focus only on a single object per subject-relation pair, even though often multiple objects are correct. To overcome this limitation, we analyze these representations for th

Géraldine Servant, Peera Simakachorn

Models that produce Axion-Like-Particles (ALP) after cosmological inflation due to spontaneous $U(1)$ symmetry breaking also produce cosmic string networks. Those axionic strings lose energy through gravitational wave emission during the whole cosmological history, generating a stochastic background of gravitational waves that spans many decades in frequency

Zhe Yu, Chengjie Fu, Zong-Kuan Guo

We study the inflationary model with a spectator scalar field $\chi$ coupled to both the inflaton and Ricci scalar. The interaction between the $\chi$ field and the gravity, denoted by $\xi R\chi^2$, can trigger the tachyonic instability of certain modes of the $\chi$ field. As a result, the $\chi$ field perturbations are amplified and serve as a gravitation

Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu

Order execution is a fundamental task in quantitative finance, aiming at finishing acquisition or liquidation for a number of trading orders of the specific assets. Recent advance in model-free reinforcement learning (RL) provides a data-driven solution to the order execution problem. However, the existing works always optimize execution for an individual or

Alex Milne, Xianghua Xie

Control of surface texture in strip steel is essential to meet customer requirements during galvanizing and temper rolling processes. Traditional methods rely on post-production stylus measurements, while on-line techniques offer non-contact and real-time measurements of the entire strip. However, ensuring accurate measurement is imperative for their effecti

Sagnik Chatterjee, Vyacheslav Kungurtsev

In this work, we propose a novel architecture (and several variants thereof) based on quantum cryptographic primitives with provable privacy and security guarantees regarding membership inference attacks on generative models. Our architecture can be used on top of any existing classical or quantum generative models. We argue that the use of quantum gates ass

Alina Kononov, Thomas Hentschel, Stephanie B. Hansen, Andrew D. Baczewski

Real-time time-dependent density functional theory (TDDFT) is presently the most accurate available method for computing electronic stopping powers from first principles. However, obtaining application-relevant results often involves either costly averages over multiple calculations or ad hoc selection of a representative ion trajectory. We consider a broadl

Thomas Jun Jewell, Andrew L. Krause, Philip K. Maini, Eamonn A. Gaffney

Throughout developmental biology and ecology, transport can be driven by nonlocal interactions. Examples include cells that migrate based on contact with pseudopodia extended from other cells, and animals that move based on their vision of other animals. Nonlocal integro-PDE models have been used to investigate contact attraction and repulsion in cell popula

Michele Cantiello, John P. Blakeslee

The Surface Brightness Fluctuation (SBF) method is a powerful tool for determining distances to early-type galaxies. The method measures the intrinsic variance in a galaxy's surface brightness distribution to determine its distance with an accuracy of about 5%. Here, we discuss the mathematical formalism behind the SBF technique, its calibration, and the pra

Weiliang Chen, Qianqian Ren, Jinbao Li

Representing urban regions accurately and comprehensively is essential for various urban planning and analysis tasks. Recently, with the expansion of the city, modeling long-range spatial dependencies with multiple data sources plays an important role in urban region representation. In this paper, we propose the Attentive Graph Enhanced Region Representation

Zijun Yao, Yantao Liu, Xin Lv, Shulin Cao

Deep text understanding, which requires the connections between a given document and prior knowledge beyond its text, has been highlighted by many benchmarks in recent years. However, these benchmarks have encountered two major limitations. On the one hand, most of them require human annotation of knowledge, which leads to limited knowledge coverage. On the

P. H. A. Konzen

Neutral particle transport problems are fundamental in the modeling of energy transfer by radiation (photons) and by neutrons with many important applications. In this work, the novel ANN-MoC method for solving unidimensional neutral particle transport problems is presented. Following the Method of Discrete Ordinates (DOM) and decoupling with a Source Iterat

Michael J. Mior

Schema discovery is an important aspect to working with data in formats such as JSON. Unlike relational databases, JSON data sets often do not have associated structural information. Consumers of such datasets are often left to browse through data in an attempt to observe commonalities in structure across documents to construct suitable code for data process

Lucia Bagnoli, Slaven Kožić

We construct a new class of quantum vertex algebras associated with the normalized Yang $R$-matrix. They are obtained as Yangian deformations of certain $\mathcal{S}$-commutative quantum vertex algebras and their $\mathcal{S}$-locality takes the form of a single $RTT$-relation. We establish some preliminary results on their representation theory and then fur

Stanislav Minsker, Nate Strawn

This paper is devoted to the statistical and numerical properties of the geometric median, and its applications to the problem of robust mean estimation via the median of means principle. Our main theoretical results include (a) an upper bound for the distance between the mean and the median for general absolutely continuous distributions in R^d, and example

Bhavna Gopal, Arjun Sridhar, Tunhou Zhang, Yiran Chen

Search spaces hallmark the advancement of Neural Architecture Search (NAS). Large and complex search spaces with versatile building operators and structures provide more opportunities to brew promising architectures, yet pose severe challenges on efficient exploration and exploitation. Subsequently, several search space shrinkage methods optimize by selectin

Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their evaluation becomes increasingly critical, not only at the task level, but also at the society level for better understanding

Zhenting Wang, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas

Recent text-to-image diffusion models have shown surprising performance in generating high-quality images. However, concerns have arisen regarding the unauthorized data usage during the training or fine-tuning process. One example is when a model trainer collects a set of images created by a particular artist and attempts to train a model capable of generati

Yin Tang, W. Zhu

Quantum inverse problem is defined as how to determine a local Hamiltonian from a single eigenstate? This question is valid not only in Hermitian system but also in non-Hermitian system. So far, most attempts are limited to Hermitian systems, while the possible non-Hermitian solution remains outstanding. In this work, we generalize the quantum covariance mat

Jonathan Ariel Barmak

By a result of Babai, with finitely many exceptions, every group $G$ admits a semi-regular poset representation with three orbits, that is, a poset $P$ with automorphism group $\textrm{Aut}(P) \simeq G$ such that the action of $\textrm{Aut}(P)$ on the underlying set is free and with three orbits. Among finite groups, only the trivial group and $\mathbb{Z}_2$

Soumita Hazra, J. Harshan

In wireless security, cognitive adversaries are known to inject jamming energy on the victim's frequency band and monitor the same band for countermeasures thereby trapping the victim. Under the class of cognitive adversaries, we propose a new threat model wherein the adversary, upon executing the jamming attack, measures the long-term statistic of Kullback-

Tim Schopf, Dennis N. Schneider, Florian Matthes

Sentence embeddings enable us to capture the semantic similarity of short texts. Most sentence embedding models are trained for general semantic textual similarity tasks. Therefore, to use sentence embeddings in a particular domain, the model must be adapted to it in order to achieve good results. Usually, this is done by fine-tuning the entire sentence embe

Behzad Akbari, Zikai Wang, Haibin Zhu, Lucas Wan

In situations involving teams of diverse robots, assigning appropriate roles to each robot and evaluating their performance is crucial. These roles define the specific characteristics of a robot within a given context. The stream actions exhibited by a robot based on its assigned role are referred to as the process role. Our research addresses the depiction

MicroBooNE collaboration, P. Abratenko, O. Alterkait, D. Andrade Aldana

We report measurements of radon progeny in liquid argon within the MicroBooNE time projection chamber (LArTPC). The presence of specific radon daughters in MicroBooNE's 85 metric tons of active liquid argon bulk is probed with newly developed charge-based low-energy reconstruction tools and analysis techniques to detect correlated $^{214}$Bi-$^{214}$Po radio

Jie Zhang, Masanori Suganuma, Takayuki Okatani

Previous works on unsupervised industrial anomaly detection mainly focus on local structural anomalies such as cracks and color contamination. While achieving significantly high detection performance on this kind of anomaly, they are faced with logical anomalies that violate the long-range dependencies such as a normal object placed in the wrong position. In

J. S. Dowker

The Dirac APS eta invariant on a Berger sphere of dimension $2n-1$ is discovered, numerically, to coincide, up to spin factors, with the Dirac conformal anomaly on a round sphere of even dimension, $n$. The analytical expression, given in terms of a generalised Bernoulli polynomial, is shown to equal a known conjecture for the eta invariant. Weingart's gener

Michael Vignal, Gayle Geschwind, Marcos D. Caballero, H. J. Lewandowski

Content-focused research-based assessment instruments typically use items (i.e., questions) as the unit of assessment for scoring, reporting, and validation. Couplet scoring employs an alternative unit of assessment called a couplet, which is essentially an item viewed and scored through the lens of a specific assessment objective. With couplet scoring, a si

Simon Badger, Jakub Kryś, Ryan Moodie, Simone Zoia

We compute the two-loop QED helicity amplitudes for the scattering of a lepton pair with an off-shell and an on-shell photon, $0\to\ell\bar\ell\gamma\gamma^*$, using the approximation of massless leptons. We express all master integrals relevant for the scattering of four massless particles with a single external off-shell leg up to two loops in a basis of a

Taeho Ryu, Selma de Mink, Rob Farmer, Ruediger Pakmor

Multi-body dynamical interactions of binaries with other objects are one of the main driving mechanisms for the evolution of star clusters. It is thus important to bring our understanding of three-body interactions beyond the commonly employed point-particle approximation. To this end we here investigate the hydrodynamics of three-body encounters between sta

Dustin Davis, Karl Gebhardt, Erin Mentuch Cooper, William P. Bowman

We describe the ensemble properties of the $1.9 < z < 3.5$ Lyman Alpha Emitters (LAEs) found in the HETDEX survey's first public data release, HETDEX Public Source Catalog 1 (Mentuch Cooper et al. 2023). Stacking the low-resolution ($R \sim$ 800) spectra greatly increases the signal-to-noise ratio, revealing spectral features otherwise hidden by noise, and w

Sai Wang, Zhi-Chao Zhao, Qing-Hua Zhu

Recently, strong evidence for a gravitational wave background has been reported by collaborations of pulsar timing arrays (PTA). In the framework of scalar-induced gravitational waves (SIGWs), we concurrently investigate the second and third order gravitational waves by jointly analyzing PTA data, alongside big-bang nucleosynthesis (BBN), and cosmic microwav

Daniele Manuzzi

The LHCb experiment has been reporting remarkable $C\!P$-violation (CPV) measurements concerning the sectors of $b$ and $c$ quarks. Recently, the new measurements of time-integrated CPV with $D^0\to K^+ K^-$ decays led to the first evidence ($3.8\sigma$) of CPV in a single charmed decay. The first search for CPV in the $D_{(s)}^+\to K^+K^+K^-$ decays was exe

Kenza Tazi, Jihao Andreas Lin, Ross Viljoen, Alex Gardner

Gaussian Processes (GPs) offer an attractive method for regression over small, structured and correlated datasets. However, their deployment is hindered by computational costs and limited guidelines on how to apply GPs beyond simple low-dimensional datasets. We propose a framework to identify the suitability of GPs to a given problem and how to set up a robu

Anar Assanova, Carsten Trunk, Roza Uteshova

We study a two-point boundary value problem for a linear differen\-tial-algebraic equation with constant coefficients by using the method of parameterization. The parameter is set as the value of the continuously differentiable component of the solution at the left endpoint of the interval. Applying the Weierstrass canonical form to the matrix pair associate

Juan S. Cruz, Florian Niedermann, Martin S. Sloth

It has recently been speculated that the NANOGrav observations point towards a first-order phase transition in the dark sector at the GeV scale [1]. Here, we show that such a phase transition might already have been predicted in the Hot New Early Dark Energy model (Hot NEDE) [2],[3]. There, it was argued that two dark sector phase transitions are the signatu

Francesco Della Corte, Gian Paolo Clemente, Nino Savelli

We investigate the quantification of demographic risk in a framework consistent with the market-consistent valuation imposed by Solvency II. We provide compact formulas for evaluating inflows and outflows of a portfolio of insurance policies based on a cohort approach. In this context, we maintain the highest level of generality in order to consider both tra

Ke Liang, Sihang Zhou, Yue Liu, Lingyuan Meng

Multimodal knowledge graphs (MKGs), which intuitively organize information in various modalities, can benefit multiple practical downstream tasks, such as recommendation systems, and visual question answering. However, most MKGs are still far from complete, which motivates the flourishing of MKG reasoning models. Recently, with the development of general art

Jonathan Feldman

Over the last decade, there has been a vast increase in eating disorder diagnoses and eating disorder-attributed deaths, reaching their zenith during the Covid-19 pandemic. This immense growth derived in part from the stressors of the pandemic but also from increased exposure to social media, which is rife with content that promotes eating disorders. This st

Manuel Gomes, Miguel Oliveira, Vítor Santos

Despite the growing interest in innovative functionalities for collaborative robotics, volumetric detection remains indispensable for ensuring basic security. However, there is a lack of widely used volumetric detection frameworks specifically tailored to this domain, and existing evaluation metrics primarily focus on time and memory efficiency. To bridge th

Keqi Deng, Philip C. Woodland

Neural transducers provide a natural way of streaming ASR. However, they augment output sequences with blank tokens which leads to challenges for domain adaptation using text data. This paper proposes a label-synchronous neural transducer (LS-Transducer), which extracts a label-level encoder representation before combining it with the prediction network outp

Doyoon Kim, Kwan Woo

We establish trace and extension theorems for evolutionary equations with the Caputo fractional derivatives in (weighted) $L_p$ spaces. To achieve this, we identify weighted Sobolev and Besov spaces with mixed norms that accommodate solution spaces and their initial values well-suited for equations involving time-fractional derivatives. Our analysis encompas

Zhi-Wei Sun

In this paper, we evaluate some series of the form $$\sum_{k=1}^\infty\frac{ak^2+bk+c}{k(3k-1)(3k-2)m^k\binom{4k}k}.$$ For example, we prove that $$\sum_{k=1}^\infty\frac{(5k^2-4k+1)8^{k}}{k(3k-1)(3k-2)\binom{4k}k}=\frac{3}2\pi$$ and $$\sum_{k=1}^\infty\frac{415k^2-343k+62}{k(3k-1)(3k-2)(-8)^k\binom{4k}k}=-3\log2.$$ We also pose many new conjectural series i

Shilpi Roy, Saurabh Basu, Ivan M. Khaymovich

Models with correlated disorders are rather common in physics. In some of them, like the Aubry-Andr\'e (AA) model, the localization phase diagram can be found from the (self)duality with respect to the Fourier transform. In the others, like the all-to-all translation-invariant Rosenzweig-Porter (TI RP) ensemble or the Hilbert-space structure of the many-body

Abhay Goyal, Nimay Parekh, Lam Yin Cheung, Koustuv Saha

Machine learning algorithms can sometimes exacerbate health disparities based on ethnicity, gender, and other factors. There has been limited work at exploring potential biases within algorithms deployed on a small scale, and/or within minoritized communities. Understanding the nature of potential biases may improve the prediction of various health outcomes.

Dennis Dobler, Eni Musta

Comparing the survival times among two groups is a common problem in time-to-event analysis, for example if one would like to understand whether one medical treatment is superior to another. In the standard survival analysis setting, there has been a lot of discussion on how to quantify such difference and what can be an intuitive, easily interpretable, summ

Augusto Aubry, Antonio De Maio, Luca Pallotta

Multifunction phased array radars (MPARs) exploit the intrinsic flexibility of their active electronically steered array (ESA) to perform, at the same time, a multitude of operations, such as search, tracking, fire control, classification, and communications. This paper aims at addressing the MPAR resource allocation so as to satisfy the quality of service (

Riccardo Bertoglio, Veronica Carini, Stefano Arrigoni, Matteo Matteucci

Agricultural robots have the potential to increase production yields and reduce costs by performing repetitive and time-consuming tasks. However, for robots to be effective, they must be able to navigate autonomously in fields or orchards without human intervention. In this paper, we introduce a navigation system that utilizes LiDAR and wheel encoder sensors

Florian Brandl, Felix Brandt

We characterize Nash equilibrium by postulating coherent behavior across varying games. Nash equilibrium is the only solution concept that satisfies the following axioms: (i) strictly dominant actions are played with positive probability, (ii) if a strategy profile is played in two games, it is also played in every convex combination of these games, and (iii

Andrew D. Gow, Tays Miranda, Sami Nurmi

We investigate the production of primordial black holes (PBHs) in a mixed inflaton-curvaton scenario with a quadratic curvaton potential, assuming the curvaton is in de Sitter equilibrium during inflation with $\langle \chi\rangle =0$. In this setup, the curvature perturbation sourced by the curvaton is strongly non-Gaussian, containing no leading Gaussian t

Geonwoo Ko, Jinhong Jung

Signed graphs are complex systems that represent trust relationships or preferences in various domains. Learning node representations in such graphs is crucial for many mining tasks. Although real-world signed relationships can be influenced by multiple latent factors, most existing methods often oversimplify the modeling of signed relationships by relying o

I. N. Burenev, F. Colomo, A. Maroncelli, A. G. Pronko

We consider the four-vertex model with a special choice of fixed boundary conditions giving rise to limit shape phenomena. More generally, the considered boundary conditions relate vertex models to scalar products of off-shell Bethe states, boxed plane partitions, and fishnet diagrams in quantum field theory. In the scaling limit, the model exhibits the emer

Simon Burton

Path calculus, or graphical linear algebra, is a string diagram calculus for the category of matrices over a base ring. It is the usual string diagram calculus for a symmetric monoidal category, where the monoidal product is the direct sum of matrices. We categorify this story to develop a surface diagram calculus for the bicategory of matrices over a base b

Mostafa M. Amin, Erik Cambria, Björn W. Schuller

The employment of foundation models is steadily expanding, especially with the launch of ChatGPT and the release of other foundation models. These models have shown the potential of emerging capabilities to solve problems, without being particularly trained to solve. A previous work demonstrated these emerging capabilities in affective computing tasks; the p

Francesco Cordoni, Alessio Sancetta

A methodology for high dimensional causal inference in a time series context is introduced. It is assumed that there is a monotonic transformation of the data such that the dynamics of the transformed variables are described by a Gaussian vector autoregressive process. This is tantamount to assume that the dynamics are captured by a Gaussian copula. No knowl

Jishnu Jaykumar P, Kamalesh Palanisamy, Yu-Wei Chao, Xinya Du

We propose a novel framework for few-shot learning by leveraging large-scale vision-language models such as CLIP. Motivated by unimodal prototypical networks for few-shot learning, we introduce Proto-CLIP which utilizes image prototypes and text prototypes for few-shot learning. Specifically, Proto-CLIP adapts the image and text encoder embeddings from CLIP

Shamil Asgarli, Dragos Ghioca

A plane curve $C$ in $\mathbb{P}^2$ defined over $\mathbb{F}_q$ is called plane-filling if $C$ contains every $\mathbb{F}_q$-point of $\mathbb{P}^2$. Homma and Kim, building on the work of Tallini, proved that the minimum degree of a smooth plane-filling curve is $q+2$. We study smooth plane-filling curves of degree $q+3$ and higher.

Marco Calautti, Sergio Greco, Cristian Molinaro, Irina Trubitsyna

Data exchange, the problem of transferring data from a source schema to a target schema, has been studied for several years. The semantics of answering positive queries over the target schema has been defined in early work, but little attention has been paid to more general queries. A few proposals of semantics for more general queries exist but they either

Zhen Gao, Shicong Liu, Yu Su, Zhongxiang Li

This paper focuses on advancing outdoor wireless systems to better support ubiquitous extended reality (XR) applications, and close the gap with current indoor wireless transmission capabilities. We propose a hybrid knowledge-data driven method for channel semantic acquisition and multi-user beamforming in cell-free massive multiple-input multiple-output (MI

Guozheng Dai, Zhonggen Su, Hanchao Wang

This paper investigates the nonasymptotic properties of the spectral norm of some random matrices with independent columns. In particular, we consider an $m\times n$ random matrix $BA$, where $A$ is an $N\times n$ random matrix with independent mean-zero subexponential entries, and $B$ is an $m\times N$ deterministic matrix. We prove that the $L_{p}$ norm of

Shadi Sartipi, Mastaneh Torkamani-Azar, Mujdat Cetin

Recently, physiological data such as electroencephalography (EEG) signals have attracted significant attention in affective computing. In this context, the main goal is to design an automated model that can assess emotional states. Lately, deep neural networks have shown promising performance in emotion recognition tasks. However, designing a deep architectu

Yuan He, Jiaoyan Chen, Hang Dong, Ian Horrocks

Integrating deep learning techniques, particularly language models (LMs), with knowledge representation techniques like ontologies has raised widespread attention, urging the need of a platform that supports both paradigms. Although packages such as OWL API and Jena offer robust support for basic ontology processing features, they lack the capability to tran

Yifan Jing, Akshat Mudgal

Let $G$ be a connected compact group equipped with the normalised Haar measure $\mu$. Our first result shows that given $\alpha, \beta>0$, there is a constant $c = c(\alpha,\beta)>0$ such that for any compact sets $A,B\subseteq G$ with $ \alpha\mu(B)\geq\mu(A)\geq \mu(B) $ and $ \mu(A)+\mu(B)\leq 1-\beta$, there exist $b_1,\dots b_c\in B$ such that \[ \mu(A\

Minki Hhan, Takashi Yamakawa, Aaram Yun

This paper studies the quantum computational complexity of the discrete logarithm (DL) and related group-theoretic problems in the context of generic algorithms -- that is, algorithms that do not exploit any properties of the group encoding. We establish a generic model of quantum computation for group-theoretic problems, which we call the quantum generic gr

Jean-Christophe Bourin

This is the Habilitation Thesis manuscript presented at Besan\c{c}on on January 5, focusing on Matrix Analysis, Matrix Inequalities and Matrix Decompositions. There are also some topics in (Hilbert space) Operator Theory. The text should be of interest for a large audience of researchers and students in pure and applied mathematics. We may divide it into fiv

Ramón Pozuelo, André V. G. Cavalieri, Philipp Schlatter, Ricardo Vinuesa

The widest spanwise scales in turbulent channel flows are studied through the use of three periodic channel-flow simulations at friction Reynolds number $\mathrm{Re}_{\tau}=550$. The length and height of the channels are the same in all cases ($L_x/h=8\pi$ and $L_y/h=2$ respectively), while the width is progressively doubled: $L_z/h = \{4\pi, 8\pi, 16\pi\}$.

Saheli Sarkar, Lars Franke, Nikolas Grivas, Markus Garst

The stability of a quantum critical point in the $O(N)$ universality class with respect to an elastic coupling, that preserves $O(N)$ symmetry, is investigated for isotropic elasticity in the framework of the renormalization group (RG) close to the upper critical dimension $d=3-\epsilon$. With respect to the Wilson-Fisher fixed point, we find that the elasti