May 2023 arXiv papers — page 85

Xiaoyu Zhang, Grant Fitez, Shayaan Subzwari, Nicholas S. Bingham

Ergodic kinetics, which are critical to equilibrium thermodynamics, can be constrained by a system's topology. We study a model nanomagnetic array in which such constraints visibly affect the behavior. In this system, magnetic excitations connect into thermally active one-dimensional strings whose motion can be imaged in real time. At high temperatures, we o

Ozório Holanda, René Meyer, Dmitri Vassilevich

We calculate the anomalous part of the polarization tensor of Dirac fermions in $2+1$ dimensions in the presence of impurities described by the scattering rate $\Gamma$ for arbitrary external frequency and momenta. We consider two different versions of the Pauli--Villars subtractions and discuss their physical consequences.

Paulo Manrique-Mirón

In this manuscript it is considered the eigenvalues $\lambda_j$ of a random tridiagonal Toeplitz matrix $T$. We study the asymptotic behavior of the joint distribution of $({|{\lambda}|_{\min} ,|{\lambda}|_{\max}})$. From this, we obtain the asymptotic distribution of the condition number when $T$ is symmetric. In the non-symmetric case, we understand well t

Sidi Abdelmajid Ait Abdelkader, Ismail Benabdallah, Mohammed Amlieh, Abdelouahad El Fatimy

Creating nanopores in graphene is a powerful tool for engineering its properties. Nanopores in graphene tune their electrical, optical, magnetic, and mechanical properties. However, controlling nanopores formation at the nanoscale level remains a significant challenge. We report an easy method to control nanopore sizes using argon-plasma magnetron sputtering

Paola Cappanera, Marco Gavanelli, Maddalena Nonato, Marco Roma

In Answer Set Programming (ASP), the user can define declaratively a problem and solve it with efficient solvers; practical applications of ASP are countless and several constraint problems have been successfully solved with ASP. On the other hand, solution time usually grows in a superlinear way (often, exponential) with respect to the size of the instance,

Peize Li, Ruining Deng, Yuankai Huo

Tissue examination and quantification in a 3D context on serial section whole slide images (WSIs) were laborintensive and time-consuming tasks. Our previous study proposed a novel registration-based method (Map3D) to automatically align WSIs to the same physical space, reducing the human efforts of screening serial sections from WSIs. However, the registrati

Cesar Bonilla, A. E. Cárcamo Hernández, Sergey Kovalenko, H. Lee

We present a Left-Right symmetric model that provides an explanation for the mass hierarchy of the charged fermions within the framework of the Standard Model. This explanation is achieved through the utilization of both tree-level and radiative seesaw mechanisms. In this model, the tiny masses of the light active neutrinos are generated via a three-loop rad

Yerong Xu, Ciro Pinto, Daniele Rogantini, Stefano Bianchi

Ultra-fast outflows (UFOs) have been revealed in a large number of active galactic nuclei (AGN) and are regarded as promising candidates for AGN feedback on the host galaxy. The nature and launching mechanism of UFOs are not yet fully understood. Here we perform a time- and flux-resolved X-ray spectroscopy on four XMM-Newton observations of a highly accretin

Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou

In this paper, we aim to optimize a contrastive loss with individualized temperatures in a principled and systematic manner for self-supervised learning. The common practice of using a global temperature parameter $\tau$ ignores the fact that ``not all semantics are created equal", meaning that different anchor data may have different numbers of samples with

Farzam Nosrati, Bruno Bellomo, Gabriele De Chiara, Giuseppe Compagno

Production of quantum states exhibiting a high degree of entanglement out of noisy conditions is one of the main goals of quantum information science. Here, we provide a conditional yet efficient entanglement distillation method which functions within the framework of spatially localized operations and classical communication. This method exploits indistingu

Modi Ke, Mahmoud M. Asmar, Wang-Kong Tse

Light drives offer a potential tool for the dynamical control of magnetic interactions in matter. We theoretically investigate the indirect exchange coupling between two parallel chains of magnetic impurities on the surface of a topological insulator, driven by a time-periodic circularly polarized light field in the high-frequency, off-resonant regime. We de

Jafar Abdollahi

The advancement of computer-aided detection systems had a significant impact on clinical analysis and decision-making on human disease. Lung cancer requires more attention among the numerous diseases being examined because it affects both men and women, increasing the mortality rate. LeNet, a deep learning model, is used in this study to detect lung tumors.

Peter Ercius, Ian J. Johnson, Philipp Pelz, Benjamin H. Savitzky

We describe the development, operation, and application of the 4D Camera -- a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at approximately 480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implem

Alexis Morris, Jie Guan, Nadine Lessio, Yiyi Shao

The internet-of-things (IoT) refers to the growing field of interconnected pervasive computing devices and the networking that supports smart, embedded applications. The IoT has multiple human-computer interaction challenges due to its many formats and interlinked components, and central to these is the need to provide sensory information and situational con

Jianjian Wu, Chi-Tsun Cheng, Qingfeng Zhou, Jianlin Liang

Sparse Code Multiple Access (SCMA) and Blind Interference Alignment (BIA) are key enablers for multi-user communication, yet each suffers from distinct limitations: SCMA faces high complexity and limited multiplexing gain, while BIA requires a long temporal channel pattern and incurs significant decoding delay. This paper proposes SBMA (Sparsecode-and-BIA-ba

Luca Di Luzio, Maurizio Giannotti, Federico Mescia, Enrico Nardi

We study the impact of renormalization group effects on QCD axion phenomenology. Focusing on the DFSZ model, we argue that the relevance of running effects for the axion couplings crucially depends on the scale where the heavier Higgs scalars are integrated out. We study the impact of these effects on astrophysical and cosmological bounds as well as on the s

Siwei Wang, Stephanie E Palmer

Neural collapse describes the geometry of activation in the final layer of a deep neural network when it is trained beyond performance plateaus. Open questions include whether neural collapse leads to better generalization and, if so, why and how training beyond the plateau helps. We model neural collapse as an information bottleneck (IB) problem in order to

Tanveer Karim, Mehdi Rezaie, Sukhdeep Singh, Daniel Eisenstein

One important source of systematics in galaxy redshift surveys comes from the estimation of the galaxy window function. Up until now, the impact of the uncertainty in estimating the galaxy window function on parameter inference has not been properly studied. In this paper, we show that the uncertainty and the bias in estimating the galaxy window function wil

Alexander A. Davydov, Stefano Marcugini, Fernanda Pambianco

The smallest possible length of a $q$-ary linear code of covering radius $R$ and codimension (redundancy) $r$ is called the length function and is denoted by $\ell_q(r,R)$. In this work, for $q$ \emph{an arbitrary prime power}, we obtain the following new constructive upper bounds on $\ell_q(3t+1,3)$: $\ell_q(r,3)\lessapprox \sqrt[3]{k}\cdot q^{(r-3)/3}\cdot

Sirshendu Bhattacharyya

A cyclically dominating three-species ecosystem, modeled within the framework of rock-paper-scissor game, is studied in presence of natural death and an effect of the environment. The environmental impact is parameterized along with the death rates in the rate equation of the species densities. Monte-Carlo simulations on this system reveal that the populatio

Siwei Wang, Elizabeth A de Laittre, Jason MacLean, Stephanie E Palmer

Representational drift refers to an unstable mapping between neural activity and input sensory or output behavioral variables. While much work has focused on the effect of representational drift on single, simple external variables, we investigate the differences in representational drift across spatiotemporal features in a moving visual stimulus. The neural

Xuanyu Zhang, Qing Yang

Large-scale language models like ChatGPT and GPT-4 have gained attention for their impressive conversational and generative capabilities. However, the creation of supervised paired question-answering data for instruction tuning presents formidable challenges. This endeavor necessitates substantial human effort for data annotation and wrestles with issues con

Antonio Pich, Eleftheria Solomonidi, Luiz Vale Silva

Urgent theoretical progress is needed in order to provide an estimate in the Standard Model of the recent measurement by LHCb of direct CP violation in charm-meson two-body decays. Rescattering effects must be taken into account for a meaningful theoretical description of the amplitudes involved in such category of observables, as signaled by the presence of

R. Brent Tully

For 100 years since galaxies were found to be flying apart from each other, astronomers have been trying to determine how fast. The expansion, characterized by the Hubble constant, H0, is confused locally by peculiar velocities caused by gravitational interactions, so observers must obtain accurate distances at significant redshifts. Very nearby in our Galax

T. Rick Perche, Matheus H. Zambianco

We present a duality between a particle detector model coupled to the amplitude of a scalar field and coupled to the field's derivative in the limit of large energy gaps. We show that the results of the models can be mapped to each other in a one-to-one fashion modulo a rescaling by the detector's gap. Our analysis is valid for arbitrary scalar fields in cur

Surabhi Datta, Tasneem Kaochar, Hio Cheng Lam, Nelly Nwosu

We introduce an annotated corpus of 600 ophthalmology notes labeled with detailed spatial and contextual information of ophthalmic entities. We extend our previously proposed frame semantics-based spatial representation schema, Rad-SpatialNet, to represent spatial language in ophthalmology text, resulting in the Eye-SpatialNet schema. The spatially-grounded

Thomas Battard, Sebastian Lahs, Claudine Crépin, Daniel Comparat

This paper presents both experimental and theoretical investigations into the spectroscopy of dilute cesium (Cs) atoms within a solid argon (Ar) matrix at cryogenic temperatures. This system is relevant for matrix isolation spectroscopy and in particular for recently proposed methods for investigating phenomena that extend beyond the standard model of partic

Hong Xu, Shireen Y. Elhabian

Statistical shape modeling (SSM) is an essential tool for analyzing variations in anatomical morphology. In a typical SSM pipeline, 3D anatomical images, gone through segmentation and rigid registration, are represented using lower-dimensional shape features, on which statistical analysis can be performed. Various methods for constructing compact shape repre

Vassily Olegovich Manturov, Zheyan Wan

In the present paper, we consider two applications of the pentagon equation. The first deals with actions of flips on edges of triangulations labelled by rational functions in some variables. The second can be formulated as a system of linear equations with variables corresponding to triangles of a triangulation. The general method says that if there is some

Aditi Chaudhary, Karthik Raman, Krishna Srinivasan, Kazuma Hashimoto

Query-document relevance prediction is a critical problem in Information Retrieval systems. This problem has increasingly been tackled using (pretrained) transformer-based models which are finetuned using large collections of labeled data. However, in specialized domains such as e-commerce and healthcare, the viability of this approach is limited by the dear

Alireza Mohammadinodooshan, Niklas Carlsson

The rapid growth of social media as a news platform has raised significant concerns about the influence and societal impact of biased and unreliable news on these platforms. While much research has explored user engagement with news on platforms like Facebook, most studies have focused on publicly shared posts. This focus leaves an important question unanswe

Mauro Dalle Lucca Tosi, Martin Theobald

Online Learning (OL) is a field of research that is increasingly gaining attention both in academia and industry. One of the main challenges of OL is the inherent presence of concept drifts, which are commonly defined as unforeseeable changes in the statistical properties of an incoming data stream over time. The detection of concept drifts typically involve

Marc Illa, Caroline E. P. Robin, Martin J. Savage

The structure and dynamics of quantum many-body systems are the result of a delicate interplay between underlying interactions, which leads to intricate entanglement structures. Despite this apparent complexity, symmetries emerge and have long been used to determine the relevant degrees of freedom and simplify classical descriptions of these systems. In this

Joaquin F. Rodriguez-Nieva, Cheryne Jonay, Vedika Khemani

A characteristic feature of "quantum chaotic" systems is that their eigenspectra and eigenstates display universal statistical properties described by random matrix theory (RMT). However, eigenstates of local systems also encode structure beyond RMT. To capture this, we introduce a quantitative metric for quantum chaos which utilizes the Kullback-Leibler div

Ahmed Rayyan, Xiaoyu Liu, Hae-Young Kee

In a cubic environment, the ground state of spin-orbit coupled $5d^2$ ions is a non-Kramers $E_g$ doublet, which hosts quadrupole and octupole moments. A series of $5d^2$ osmium double perovskites Ba$_2M$OsO$_6$ (M = Mg, Ca, Zn, Cd) have recently been proposed to exhibit multipolar orders. We investigate the structural properties of these materials using $\t

Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin, Mihir Kale

Data scarcity is a crucial issue for the development of highly multilingual NLP systems. Yet for many under-represented languages (ULs) -- languages for which NLP re-search is particularly far behind in meeting user needs -- it is feasible to annotate small amounts of data. Motivated by this, we propose XTREME-UP, a benchmark defined by: its focus on the sca

Mattia Di Mauro, Chiara Arina, Nicolao Fornengo, Jan Heisig

The singlet scalar Higgs portal model provides one of the simplest explanations of dark matter in our Universe. Its Higgs resonant region, $m_\text{DM}\approx m_h/2$, has gained particular attention, being able to reconcile the tension between the relic density measurement and direct detection constraints. Interestingly, this region is also preferred as an e

C. S. Kochanek

Dust absorption is invoked in a number of contexts for hiding a star that has survived some sort of transient event from view. Dust formed in a transient is expanding away from the star and, in spherical models, the mass and energy budgets implied by a high optical depth at late times make such models untenable. Concentrating the dust in a disk or torus can

Boryana Hadzhiyska, Sihan Yuan, Chris Blake, Daniel J. Eisenstein

The joint analysis of different cosmological probes, such as galaxy clustering and weak lensing, can potentially yield invaluable insights into the nature of the primordial Universe, dark energy and dark matter. However, the development of high-fidelity theoretical models that cover a wide range of scales and redshifts is a necessary stepping-stone. Here, we

Matthew R. Buckley, Claudius Krause, Ian Pang, David Shih

Simulating particle detector response is the single most expensive step in the Large Hadron Collider computational pipeline. Recently it was shown that normalizing flows can accelerate this process while achieving unprecedented levels of accuracy, but scaling this approach up to higher resolutions relevant for future detector upgrades leads to prohibitive me

Kyle Kremer, Jim Fuller, Anthony L. Piro, Scott M. Ransom

The detections of four apparently young radio pulsars in the Milky Way globular clusters are difficult to reconcile with standard neutron star formation scenarios associated with massive star evolution. Here we discuss formation of these young pulsars through white dwarf mergers in dynamically-old clusters that have undergone core collapse. Based on observed

Jake S. Bennett, Debora Sijacki, Tiago Costa, Nicolas Laporte

High-redshift quasars ($z\gtrsim6$), powered by black holes (BHs) with large inferred masses, imply rapid BH growth in the early Universe. The most extreme examples have inferred masses of $\sim \! 10^9\,$M$_\odot$ at $z = 7.5$ and $\sim \! 10^{10}\,$M$_\odot$ at $z = 6.3$. Such dramatic growth via gas accretion likely leads to significant energy input into

Byungjun Kim, Patrick Kwon, Kwangho Lee, Myunggi Lee

We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars. Due to the wide variety of human identities, poses, and stochastic details, the generation of 3D human meshes has been a challenging problem. To address this, we decompose the problem into 2D normal map generation and normal map-based 3D reconstruction

Zoltán Péli, Zoltán Trócsányi

We present the one-loop radiative corrections to the muon decay in U(1)$_z$ extensions of the standard model. We compute the mass of the $W$ boson using those corrections and compare it to an approximation of the complete one-loop prediction implemented in automated computational tools. We point out that the truncation of the complete formulas become unrelia

Helen Qu, Masao Sako

Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources. In order to maximize the science return of these observations in the absence of spectroscopic information, we must accurately extract key parameters, such as SN redshifts, with photometric information alon

Sudipta Chattopadhyay, Srikant Sukumar, Vivek Natarajan

We propose an adaptive algorithm for identifying the unknown parameter in a linear exponentially stable single-input single-output infinite-dimensional system. We assume that the transfer function of the infinite-dimensional system can be expressed as a ratio of two infinite series in s (the Laplace variable). We also assume that certain identifiability cond

Keith Burghardt, Ashwin Rao, Siyi Guo, Zihao He

Online manipulation is a pressing concern for democracies, but the actions and strategies of coordinated inauthentic accounts, which have been used to interfere in elections, are not well understood. We analyze a five million-tweet multilingual dataset related to the 2017 French presidential election, when a major information campaign led by Russia called "#

Daniel J. Calderone, Benjamin J. Chasnov, Samuel A. Burden, Lillian J. Ratliff

Leveraging tools from the study of linear fractional transformations and algebraic Riccati equations, a local characterization of consistent conjectural variations equilibrium is given for two player games on continuous action spaces with costs approximated by quadratic functions. A discrete time dynamical system in the space of conjectures is derived, a sol

Michael Novack

We study the regularity of minimizers for a variant of the soap bubble cluster problem: \begin{align*} \min \sum_{\ell=0}^N c_{\ell} P( S_\ell)\,, \end{align*} where $c_\ell>0$, among partitions $\{S_0,\dots,S_N,G\}$ of $\mathbb{R}^2$ satisfying $|G|\leq \delta$ and an area constraint on each $S_\ell$ for $1\leq \ell \leq N$. If $\delta>0$, we prove that for

Sofoklis Kakouros, Katri Hiovain-Asikainen

The North S\'{a}mi (NS) language encapsulates four primary dialectal variants that are related but that also have differences in their phonology, morphology, and vocabulary. The unique geopolitical location of NS speakers means that in many cases they are bilingual in S\'{a}mi as well as in the dominant state language: Norwegian, Swedish, or Finnish. This en

Richard Antonello, Aditya Vaidya, Alexander G. Huth

Representations from transformer-based unidirectional language models are known to be effective at predicting brain responses to natural language. However, most studies comparing language models to brains have used GPT-2 or similarly sized language models. Here we tested whether larger open-source models such as those from the OPT and LLaMA families are bett

Masahiro Kaneko, Naoaki Okazaki

Large Language Models (LLMs) have demonstrated remarkable performance in various tasks and gained significant attention. LLMs are also used for local sequence transduction tasks, including grammatical error correction (GEC) and formality style transfer, where most tokens in a source text are kept unchanged. However, the models that generate all target tokens

Junior da S. Bessa

We prove weighted Orlicz-Sobolev regularity for fully nonlinear elliptic equations with oblique boundary condition under asymptotic conditions of the following problem: $F(D^{2}u,Du,u,x)=f(x)$ in the bounded domain $\Omega\subset \mathbb{R}^{n}$($n\ge 2$) and $\beta\cdot Du+\gamma u= g$ on $\partial \Omega$, under suitable assumptions on the source term $f$,

Pranjal Aggarwal, Aman Madaan, Yiming Yang, Mausam

A popular approach for improving the correctness of output from large language models (LLMs) is Self-Consistency - poll the LLM multiple times and output the most frequent solution. Existing Self-Consistency techniques always generate a constant number of samples per question, where a better approach will be to non-uniformly distribute the available budget b

Jifan Chen, Grace Kim, Aniruddh Sriram, Greg Durrett

Evidence retrieval is a core part of automatic fact-checking. Prior work makes simplifying assumptions in retrieval that depart from real-world use cases: either no access to evidence, access to evidence curated by a human fact-checker, or access to evidence available long after the claim has been made. In this work, we present the first fully automated pipe

Vibhoothi, Angeliki Katsenou, John Squires, François Pitié

Over the past few years, there has been an increase in the demand and availability of High Dynamic Range (HDR) displays and content. To ensure the production of high-quality materials, human evaluation is required. However, ascertaining whether the full playback pipeline is indeed HDR-compliant can be challenging. In this paper, we present a set of recommend

Chen Xu, Xiuyuan Cheng, Yao Xie

Computing optimal transport (OT) for general high-dimensional data has been a long-standing challenge. Despite much progress, most of the efforts including neural network methods have been focused on the static formulation of the OT problem. The current work proposes to compute the dynamic OT between two arbitrary distributions $P$ and $Q$ by optimizing a fl

Yunpeng Liu, Vasileios Lioutas, Jonathan Wilder Lavington, Matthew Niedoba

The development of algorithms that learn multi-agent behavioral models using human demonstrations has led to increasingly realistic simulations in the field of autonomous driving. In general, such models learn to jointly predict trajectories for all controlled agents by exploiting road context information such as drivable lanes obtained from manually annotat

Thomas Bartz-Beielstein

The goal of hyperparameter tuning (or hyperparameter optimization) is to optimize the hyperparameters to improve the performance of the machine or deep learning model. spotPython (``Sequential Parameter Optimization Toolbox in Python'') is the Python version of the well-known hyperparameter tuner SPOT, which has been developed in the R programming environmen

Ipsita Ray, Soumitra Nandi

We study the $\bar{B}\to D(D^*) \ell^-\bar{\nu}_{\ell}$ decays based on the up-to-date available inputs from experiments and the lattice. First, we review the standard model (SM) predictions of the different observables associated with these decay channels. In the analyses, we consider new physics (NP) effects in the channels with the heavy ($\tau$), as well

Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo

The progress of autonomous web navigation has been hindered by the dependence on billions of exploratory interactions via online reinforcement learning, and domain-specific model designs that make it difficult to leverage generalization from rich out-of-domain data. In this work, we study data-driven offline training for web agents with vision-language found

Shuaichen Chang, Eric Fosler-Lussier

Large language models (LLMs) with in-context learning have demonstrated remarkable capability in the text-to-SQL task. Previous research has prompted LLMs with various demonstration-retrieval strategies and intermediate reasoning steps to enhance the performance of LLMs. However, those works often employ varied strategies when constructing the prompt text fo

Patrick Moylan

Both Poincar\'e in his 1900 Festschrift paper \cite{Poincare} and Einstein in his 1905 \textsl{Annalen der Physik} article \cite{Einstein} were led to $E=mc^2$ by considering electromagnetic processes taking place in vacuo. Poincar\'e's treatment is based on a generalization of the law of conservation of momentum to include radiation. Einstein's analysis rel

Lecheng Ren, Anders Schreiber, Atul Sharma, Diandian Wang

We determine tree level, all-order celestial operator product expansions (OPEs) of gluons and gravitons in the maximally helicity violating (MHV) sector. We start by obtaining the all-order collinear expansions of MHV amplitudes using the inverse soft recursion relations that they satisfy. These collinear expansions are recast as celestial OPE expansions in

M. Scialpi, F. Mannucci, C. Marconcini, G. Venturi

The novel Gaia Multi Peak (GMP) technique has proven to be able to successfully select dual and lensed AGN candidates at sub-arcsec separations. Both populations are important because dual AGN represent one of the central, still largely untested, predictions of lamdaCDM cosmology, and compact lensed quasars allow to probe the central regions of the lensing g

Ted Dobson

We introduce two refinements of the class of $5/2$-groups, inspired by the classes of automorphism groups of configurations and automorphism groups of unit circulant digraphs. We show that both of these classes have the property that any two regular cyclic subgroups of a group $G$ in either of these classes are conjugate in $G$. This generalizes two results

Alain Bensoussan, Tak Kwong Wong, Sheung Chi Phillip Yam, Hongwei Yuan

In this article, by using several new crucial {\it a priori} estimates which are still absent in the literature, we provide a comprehensive resolution of the first order generic mean field type control problems and also establish the global-in-time classical solutions of their Bellman and master equations. Rather than developing the analytical approach via t

Ben Reggio, Nouman Butt, Andrew Lytle, Patrick Draper

The Pauli strings appearing in the decomposition of an operator can be can be grouped into commuting families, reducing the number of quantum circuits needed to measure the expectation value of the operator. We detail an algorithm to completely partition the full set of Pauli strings acting on any number of qubits into the minimal number of sets of commuting

Zineng Tang, Ziyi Yang, Chenguang Zhu, Michael Zeng

We present Composable Diffusion (CoDi), a novel generative model capable of generating any combination of output modalities, such as language, image, video, or audio, from any combination of input modalities. Unlike existing generative AI systems, CoDi can generate multiple modalities in parallel and its input is not limited to a subset of modalities like te

Yujie Qian, Jiang Guo, Zhengkai Tu, Connor W. Coley

Reaction diagram parsing is the task of extracting reaction schemes from a diagram in the chemistry literature. The reaction diagrams can be arbitrarily complex, thus robustly parsing them into structured data is an open challenge. In this paper, we present RxnScribe, a machine learning model for parsing reaction diagrams of varying styles. We formulate this

Rida Qadri, Renee Shelby, Cynthia L. Bennett, Remi Denton

This paper presents a community-centered study of cultural limitations of text-to-image (T2I) models in the South Asian context. We theorize these failures using scholarship on dominant media regimes of representations and locate them within participants' reporting of their existing social marginalizations. We thus show how generative AI can reproduce an out

Gabe Cunningham, Elías Mochán, Antonio Montero

A map on a surface whose automorphism group has a subgroup acting regularly on its vertices is called a Cayley map. Here we generalize that notion to maniplexes and polytopes. We define $\mathcal{M}$ to be a \emph{Cayley extension} of $\mathcal{K}$ if the facets of $\mathcal{M}$ are isomorphic to $\mathcal{K}$ and if some subgroup of the automorphism group o

Daniel Wines, Ramya Gurunathan, Kevin F. Garrity, Brian DeCost

The Joint Automated Repository for Various Integrated Simulations (JARVIS) infrastructure at the National Institute of Standards and Technology (NIST) is a large-scale collection of curated datasets and tools with more than 80000 materials and millions of properties. JARVIS uses a combination of electronic structure, artificial intelligence (AI), advanced co

Ronak Pradeep, Kai Hui, Jai Gupta, Adam D. Lelkes

Popularized by the Differentiable Search Index, the emerging paradigm of generative retrieval re-frames the classic information retrieval problem into a sequence-to-sequence modeling task, forgoing external indices and encoding an entire document corpus within a single Transformer. Although many different approaches have been proposed to improve the effectiv

Akshita Jha, Aida Davani, Chandan K. Reddy, Shachi Dave

Stereotype benchmark datasets are crucial to detect and mitigate social stereotypes about groups of people in NLP models. However, existing datasets are limited in size and coverage, and are largely restricted to stereotypes prevalent in the Western society. This is especially problematic as language technologies gain hold across the globe. To address this g

Qing-Jie Yuan, Shao-Ping Hu, Zi-Hao Huang, Kilar Zhang

AGT conjecture reveals a connection between 4D $\mathcal{N}=2$ gauge theory and 2D conformal field theory. Though some special instances have been proven, others remain elusive and the attempts on its full proof never stop. When the $\Omega$ background parameters satisfy $-\epsilon_1/\epsilon_2\equiv \beta =1$, the story simplifies a bit. A proof of the corr

Vitaly Roman'kov

The Andrews-Curtis conjecture remains one of the outstanding open problems in combinatorial group theory. It claims that every normally generating $r$-tuple of a free group $F_r$ of rank $r\geq 2$ can be reduced to a basis by means of Nielsen transformations and arbitrary conjugations. These transformations generate the so-called Andrews-Curtis group AC($F_r

Nathalia Nascimento, Paulo Alencar, Donald Cowan

The advent of automation in particular Software Engineering (SE) tasks has transitioned from theory to reality. Numerous scholarly articles have documented the successful application of Artificial Intelligence to address issues in areas such as project management, modeling, testing, and development. A recent innovation is the introduction of ChatGPT, an ML-i

Gabrielle Nornberg, Disson dos Prazeres, Alexander Quaas

In this article we study the fundamental solutions or "$\alpha$-harmonic functions" for some nonlinear positive homogeneous nonlocal elliptic problems in conical domains, such as \begin{eqnarray*}\label{ecbir1a1} {\mathcal F }(u)=0\ \ \hbox{in} \ \ \mathcal{C}_\omega,\quad u=0\ \ \hbox{in} \ \ \mathbb{R}^n\setminus \mathcal{C}_\omega ,\ \ \end{eqnarray*} whe

Teng Xue, Sylvain Calinon

Long-term non-prehensile planar manipulation is a challenging task for planning and control, requiring determination of both continuous and discrete contact configurations, such as contact points and modes. This leads to the non-convexity and hybridness of contact optimization. To overcome these difficulties, we propose a novel approach that incorporates hum

Soham Deshmukh, Benjamin Elizalde, Rita Singh, Huaming Wang

In the domain of audio processing, Transfer Learning has facilitated the rise of Self-Supervised Learning and Zero-Shot Learning techniques. These approaches have led to the development of versatile models capable of tackling a wide array of tasks, while delivering state-of-the-art performance. However, current models inherently lack the capacity to produce

Teemu Hankala, Miika Hannula, Juha Kontinen, Jonni Virtema

We study the complexity of the problem of training neural networks defined via various activation functions. The training problem is known to be existsR-complete with respect to linear activation functions and the ReLU activation function. We consider the complexity of the problem with respect to the sigmoid activation function and other effectively continuo

Agathe Senellart, Clément Chadebec, Stéphanie Allassonnière

We propose a new multimodal variational autoencoder that enables to generate from the joint distribution and conditionally to any number of complex modalities. The unimodal posteriors are conditioned on the Deep Canonical Correlation Analysis embeddings which preserve the shared information across modalities leading to more coherent cross-modal generations.

Ben You

This work presents a comprehensive analysis to regularize the Soft Actor-Critic (SAC) algorithm with automatic temperature adjustment. The the policy evaluation, the policy improvement and the temperature adjustment are reformulated, addressing certain modification and enhancing the clarity of the original theory in a more explicit manner.

José Edson Sampaio

In this article, we prove that for a definable set in an o-minimal structure with connected link (at 0 or infinity), the inner distance of the link is equivalent to the inner distance of the set restricted to the link. With this result, we obtain several consequences. We present also several relations between the local and the global Lipschitz geometry of si

Tushar Das, David Simmons

We study the exact Hausdorff and packing dimensions of the $prime$ $Cantor$ $set$, $\Lambda_P$, which comprises the irrationals whose continued fraction entries are prime numbers. We prove that the Hausdorff measure of the prime Cantor set cannot be finite and positive with respect to any sufficiently regular dimension function, thus negatively answering a q

Hye Sun Yun, Iain J. Marshall, Thomas A. Trikalinos, Byron C. Wallace

Medical systematic reviews play a vital role in healthcare decision making and policy. However, their production is time-consuming, limiting the availability of high-quality and up-to-date evidence summaries. Recent advancements in large language models (LLMs) offer the potential to automatically generate literature reviews on demand, addressing this issue.

Marc Boulé

This paper presents the calculation of the electrical power transported by the electromagnetic fields of two parallel wires carrying opposite DC currents. The Poynting vector is developed in bipolar coordinates and symbolically integrated over different surfaces. For perfectly conducting wires, the purely longitudinal power in the space surrounding the wires

Deepanway Ghosal, Preksha Nema, Aravindan Raghuveer

The task of table summarization involves generating text that both succinctly and accurately represents the table or a specific set of highlighted cells within a table. While significant progress has been made in table to text generation techniques, models still mostly generate descriptive summaries, which reiterates the information contained within the tabl

Ji Qi, Z. H. Aitken, Qingxiang Pei, Anne Marie Z. Tan

Dual-phase $\gamma$-TiAl and $\alpha_2$-Ti$_{3}$Al alloys exhibit high strength and creep resistance at high temperatures. However, they suffer from low tensile ductility and fracture toughness at room temperature. Experimental studies show unusual plastic behaviour associated with ordinary and superdislocations, making it necessary to gain a detailed unders

Constantia Alexandrou, Simone Bacchio, Krzysztof Cichy, Martha Constantinou

Staple-shaped Wilson line operators are necessary for the study of transverse momentum-dependent parton distribution functions (TMDPDFs) in lattice QCD and beyond. In this work, we study the renormalization of such operators in the general case of an asymmetric staple. We analyze the mixing pattern of these operators using their symmetry properties, where we

Jairo A. Alzate, Gustavo Bruzual, Marina Kounkel, Gladis Magris

We develop statistical methods within a Bayesian framework to infer the star formation history from photometric surveys of pre-main sequence populations. Our procedures include correcting for biases due to extinction in magnitude-limited surveys, and using distributions from subsets of stars with individual extinction measurements. We also make modest correc

Valliamai Ramanathan, Anil Prabhakar, Prabha Mandayam

In the well-established framework of quantum key distribution (QKD), differential phase shift (DPS) protocols have known information-theoretic security bounds defining tolerable error rates under optimal adversaries. In this work, we revisit the security of 3- and n-pulse DPS QKD by explicitly analyzing two specific, physically implementable individual attac

Douglas D. Novaes, Pedro C. C. R. Pereira

Important information about the dynamical structure of a differential system can be revealed by looking into its invariant compact manifolds, such as equilibria, periodic orbits, and invariant tori. This knowledge is significantly increased if asymptotic properties of the trajectories nearby such invariant manifolds can be determined. In this paper, we prese

Christopher Oliver, Sebabrata Mukherjee, Mikael C. Rechtsman, Iacopo Carusotto

We extend the $t-z$ mapping formalism of time-dependent paraxial optics by identifying configurations displaying a synthetic magnetic vector potential, leading to a non-trivial band topology in propagating geometries. We consider an inhomogeneous 1D array of coupled optical waveguides beyond the standard monochromatic approximation, and show that the wave eq

Zijian Zhang, Linglong Dai

Thanks to the recent advances in metamaterials, reconfigurable intelligent surface (RIS) has emerged as a promising technology for future 6G wireless communications. Benefiting from its high array gain, low cost, and low power consumption, RISs are expected to greatly enlarge signal coverage, improve system capacity, and increase energy efficiency. In this a

Yongsheng Yu, Hao Wang, Tiejian Luo, Heng Fan

Vanilla image completion approaches exhibit sensitivity to large missing regions, attributed to the limited availability of reference information for plausible generation. To mitigate this, existing methods incorporate the extra cue as a guidance for image completion. Despite improvements, these approaches are often restricted to employing a single modality

Aditya K. Aiyer, Luc Deike, Michael E. Mueller

Due to the multitude of scales present in realistic oceanic conditions, resolving the surface stress is computationally intensive, motivating modeling approaches. In this work, a dynamic wave drag model is developed for Large Eddy Simulation to quantify the effects of multiscale dynamically rough surfaces on the atmospheric boundary layer. The waves are vert

J. Martin Laming, Natsuha Kuroda

We outline and discuss a model for the enhanced abundances of trans-Fe elements in impulsive Solar Energetic Particle (SEP) events, where large mass dependent abundance enhancements are frequently seen. It comes about as a variation of the ponderomotive force model for the First Ionization Potential (FIP) Effect, i.e. the increase in coronal abundance of ele

Larry Lüer, Marius Peters, Dan Bornstein, Vincent M. Le Corre

In single-junction photovoltaic (PV) devices, the maximum achievable power conversion efficiency (PCE) is mainly limited by thermalization and transmission losses, because polychromatic solar irradiation cannot be matched to a single bandgap. Several concepts are being investigated to reduce these losses, such as the classical vertical multijunction cells, '