March 2024 arXiv papers — page 132

Yanyue Zhang, Pengfei Li, Yilong Lai, Deyu Zhou

As more than 70$\%$ of reviews in the existing opinion summary data set are positive, current opinion summarization approaches are reluctant to generate negative summaries given the input of negative texts. To address such sentiment bias, a direct approach without the over-reliance on a specific framework is to generate additional data based on large languag

Han Qiu, Jiaxing Huang, Peng Gao, Lewei Lu

Inspired by the success of general-purpose models in NLP, recent studies attempt to unify different vision tasks in the same sequence format and employ autoregressive Transformers for sequence prediction. They apply uni-directional attention to capture sequential dependencies and generate task sequences recursively. However, such autoregressive Transformers

Jiwoo Hong, Noah Lee, James Thorne

While recent preference alignment algorithms for language models have demonstrated promising results, supervised fine-tuning (SFT) remains imperative for achieving successful convergence. In this paper, we study the crucial role of SFT within the context of preference alignment, emphasizing that a minor penalty for the disfavored generation style is sufficie

Edi Sutoyo, Andrea Capiluppi

Self-admitted technical debt (SATD) refers to a form of technical debt in which developers explicitly acknowledge and document the existence of technical shortcuts, workarounds, or temporary solutions within the codebase. Over recent years, researchers have manually labeled datasets derived from various software development artifacts: source code comments, m

H. Amarkhail, S. C. İnan, A. V. Kisselev

The sensitivity to anomalous quartic gauge couplings (AQGCs) of the $\gamma\gamma\gamma Z$ interaction is studied in the $\mu^+\mu^- \rightarrow \mu^+\gamma\gamma \mu^-$ scattering at a future muon collider with unpolarized beams. The anomalous $\gamma\gamma\gamma Z$ vertex is described by two couplings, $\zeta_1$ and $\zeta_2$. The differential and total cr

Simon Dufort-Labbé, Pierluca D'Oro, Evgenii Nikishin, Razvan Pascanu

When training neural networks, dying neurons -- units becoming inactive or saturated -- are traditionally seen as harmful. This paper sheds new light on this phenomenon. By exploring the impact of various hyperparameter configurations on dying neurons during training, we gather insights on how to improve upon sparse training approaches to pruning. We introdu

Oana Ignat, Longju Bai, Joan Nwatu, Rada Mihalcea

Current foundation models have shown impressive performance across various tasks. However, several studies have revealed that these models are not effective for everyone due to the imbalanced geographical and economic representation of the data used in the training process. Most of this data comes from Western countries, leading to poor results for underrepr

Lukas Waas

This article is concerned with three different homotopy theories of stratified spaces: The one defined by Douteau and Henriques, the one defined by Haine, and the one defined by Nand-Lal. One of the central questions concerning these theories has been how precisely they connect with geometric and topological examples of stratified spaces, such as piecewise l

Jasper Ischebeck, Ralph Neininger

The Quickselect algorithm (also called FIND) is a fundamental algorithm for selecting ranks or quantiles within a set of data. Gr\"ubel and R\"osler showed that the number of key comparisons required by Quickselect considered as a process of the quantiles $\alpha\in[0,1]$ converges within a natural probabilistic model after normalization in distribution with

Yijun Yang, Hongtao Wu, Angelica I. Aviles-Rivero, Yulun Zhang

Real-world vision tasks frequently suffer from the appearance of unexpected adverse weather conditions, including rain, haze, snow, and raindrops. In the last decade, convolutional neural networks and vision transformers have yielded outstanding results in single-weather video removal. However, due to the absence of appropriate adaptation, most of them fail

Elise Colin, Razvigor Ossikovski

This article primarily aims to unify the various formalisms of multivariate coefficients of variation, leveraging advanced concepts of generalized means, whether weighted or not, applied to the eigenvalues of covariance matrices. We highlight the existence of an infinite number of these coefficients and demonstrate that they are bounded. Moreover, we link th

Marta Colleoni, N. V. Krishnendu, Pierre Mourier, Sayantani Bera

General Relativity (GR) remains the most accurate theory of gravity to date. It has passed many experimental tests in the Solar System as well as binary pulsar, cosmological and gravitational-wave (GW) observations. Some of these tests probe regimes where gravitational fields are weak, the spacetime curvature is small, and the characteristic velocities are n

Andrea Di Benedetto, Claudia E. Wieners, Anna S. von der Heydt

Climate policy has become increasingly politicized in many countries including the US, with some political parties unwilling to pursue strong measures. Therefore, to be successful in mitigation, climate policies must be politically feasible. Currently, climate mitigation pathways are explored in so-called Integrated Assessment Models (IAMs) which evaluate cl

Sobhi Alfayoumi, Joan Melia-Segui, Xavier Vilajosana

This article proposes O-LoRaWAN, an adaptation of the LoRaWAN architecture into a modular network architecture based on the Open RAN (O-RAN) principles. In our vision, standardization of the network components and interfaces will enable the reuse of network functions, and thus, foster an accelerated tailoring of the network functions to the changing applicat

Caizhu Huang, Claudia Di Caterina, Nicola Sartori

Testing the equality of mean vectors across $g$ different groups plays an important role in many scientific fields. In regular frameworks, likelihood-based statistics under the normality assumption offer a general solution to this task. However, the accuracy of standard asymptotic results is not reliable when the dimension $p$ of the data is large relative t

Vjosa Preniqi, Iacopo Ghinassi, Julia Ive, Charalampos Saitis

Moral values play a fundamental role in how we evaluate information, make decisions, and form judgements around important social issues. Controversial topics, including vaccination, abortion, racism, and sexual orientation, often elicit opinions and attitudes that are not solely based on evidence but rather reflect moral worldviews. Recent advances in Natura

H. J. Hilhorst

Let $p_n^G$ be the probability for a planar Poisson-Voronoi cell to be $n$-sided {\it and\,} have only Gabriel neighbors. Using an exact coordinate transformation followed by scaling arguments and a mean-field type calculation, we obtain the asymptotic expansion of $\log p_n^G$ in the limit of large $n$. We determine several statistical properties of a many-

Bastiaan Cnossen, Tobias Lenz, Sil Linskens

Semiadditivity of an $\infty$-category, i.e. the existence of biproducts, provides it with useful algebraic structure in the form of a canonical enrichment in commutative monoids. This ultimately comes from the fact that the $\infty$-category of commutative monoids is the universal semiadditive $\infty$-category equipped with a finite-product-preserving func

Changsheng Quan, Xiaofei Li

In this work, we extend our previously proposed offline SpatialNet for long-term streaming multichannel speech enhancement in both static and moving speaker scenarios. SpatialNet exploits spatial information, such as the spatial/steering direction of speech, for discriminating between target speech and interferences, and achieved outstanding performance. The

Huixing Zhang

The three gap theorem was originally a conjecture by Steinhaus, who asserted that there are at most three distinct gap lengths in the fractional parts of the sequence {\alpha},{2}{\alpha},{\cdots},{N}{\alpha} for any integer {N} and real number {\alpha}. This conjecture has been proved by many different methods, and extended to higher dimensional cases. For

Rebecca R. Baker, Vivek Muthurangu, Marilena Rega, Stephen B. Walsh

23Na MRI can be used to quantify in-vivo tissue sodium concentration (TSC), but the low 23Na signal leads to long scan times and/or noisy or low-resolution images. Reconstruction algorithms such as CS have been proposed to mitigate low SNR; although, these can result in unnatural images, suboptimal denoising and long processing times. Recently, ML has been u

Di Mi, Yanjun Zhang, Leo Yu Zhang, Shengshan Hu

Model extraction attacks (MEAs) enable an attacker to replicate the functionality of a victim deep neural network (DNN) model by only querying its API service remotely, posing a severe threat to the security and integrity of pay-per-query DNN-based services. Although the majority of current research on MEAs has primarily concentrated on neural classifiers, t

Shijian Ma, Shicong Ma, Jianhao Jiao

This paper presents WaveShot, an innovative portable unmanned surface vessel that aims to transform water surface videography by offering a highly maneuverable, cost-effective, and safe alternative to traditional filming methods. WaveShot is designed for the modern demands of film production, advertising, documentaries, and visual arts, equipped with profess

Jun Geng, Bojing Shi

We consider a family of second-order parabolic operators $\partial_t+\mathcal{L}_\varepsilon$ in divergence form with rapidly oscillating, time-dependent and almost-periodic coefficients. We establish uniform interior and boundary H\"older and Lipschitz estimates as well as convergence rate. The estimates of fundamental solution and Green's function are also

Jakob Lass, Emma Y. Lenander, Kristine M. L. Krighaar, Tara N. Tošić

We extend previous inelastic neutron scattering results on the geometrically frustrated antiferromagnet hexagonal-YMnO$_3$, which has been suggested to belong to the class of classical spin liquids. We extend the energy transfer coverage of the diffuse signal up to 6.9 meV within a wide temperature range around the ordering temperature, $T_\mathrm{N}$. The t

Magnus J E Richardson

The steady-state firing rate and firing-rate response of the leaky and exponential integrate-and-fire models receiving synaptic shot noise with excitatory and inhibitory reversal potentials is examined. For the particular case where the underlying synaptic conductances are exponentially distributed, it is shown that the master equation for a population of su

Rory Bunker, Calvin Yeung, Keisuke Fujii

Machine learning has become a common approach to predicting the outcomes of soccer matches, and the body of literature in this domain has grown substantially in the past decade and a half. This chapter discusses available datasets, the types of models and features, and ways of evaluating model performance in this application domain. The aim of this chapter i

Ankit Sonthalia, Alexander Rubinstein, Ehsan Abbasnejad, Seong Joon Oh

It has recently been conjectured that neural network solution sets reachable via stochastic gradient descent (SGD) are convex, considering permutation invariances (Entezari et al., 2022). This means that a linear path can connect two independent solutions with low loss, given the weights of one of the models are appropriately permuted. However, current metho

Nathan Bonin

An analogue of the Markoff equation has recently been introduced by the author and Valentin Ovsienko. A conjecture about the necessary and sufficient conditions for positivity of solutions to this equation is formulated and discussed.

Azka Maula Iskandar Muda, Uğur Teğin

We introduce a novel photonic neural network using photonic crystal fibers, leveraging femtosecond pulse supercontinuum generation for optical computing. Investigating its efficacy across machine learning tasks, we uncover the crucial impact of nonlinear pulse propagation dynamics on network performance. Our findings show that octave-spanning supercontinuum

Cun Xue, Han-Xi Ren, Peng Jia, Qing-Yu Wang

Superconductors play a crucial role in the advancement of high-field electromagnets. Unfortunately, their performance can be compromised by thermomagnetic instabilities, wherein the interplay of rapid magnetic and slow heat diffusion can result in catastrophic flux jumps eventually leading to irreversible damage. This issue has long plagued high-$J_c$ Nb$_3$

Joris Raeymaekers, Canberk Sanli, Dieter Van den Bleeken

Superconformal `type B' quantum mechanical sigma models arise in a variety of interesting contexts, such as the description of D-brane bound states in an AdS$_2$ decoupling limit. Focusing on $N=2B$ models, we study superconformal indices which count short multiplets and provide an alternative to the standard Witten index, as the latter suffers from infrared

Lingyu Li, Chunbo Li

Building upon prior framework of computational Lacanian psychoanalysis with the theory of active inference, this paper aims to further explore the concept of self-identification and its potential applications. Beginning with two classic paradigms in psychology, mirror self-recognition and rubber hand illusion, we suggest that imaginary identification is char

Colin Defant, Leigh Foster, Rupert Li, James Propp

Defant, Li, Propp, and Young recently resolved two enumerative conjectures of Propp concerning the tilings of regions in the hexagonal grid called benzels using two types of prototiles called stones and bones (with varying constraints on allowed orientations of the tiles). Their primary tool, a bijection called compression that converts certain $k$-ribbon ti

P. T. Madathil, C. Wang, S. K. Singh, A. Gupta

Low-disorder two-dimensional electron systems in the presence of a strong, perpendicular magnetic field terminate at very small Landau level filling factors in a Wigner crystal (WC), where the electrons form an ordered array to minimize the Coulomb repulsion. The nature of this exotic, many-body, quantum phase is yet to be fully understood and experimentally

Maria Koutsogiannaki, Shafel Mc Dowall, Ioannis Agiomyrgiannakis

Recently, and under the umbrella of Responsible AI, efforts have been made to develop gender-ambiguous synthetic speech to represent with a single voice all individuals in the gender spectrum. However, research efforts have completely overlooked the speaking style despite differences found among binary and non-binary populations. In this work, we synthesise

Tiago Debarba, Marcus Huber, Nicolai Friis

Measurements can be viewed as interactions between a measured system and a pointer system that imprint information about the system on the pointer. For so-called unbiased interactions, the measurement statistics--the information corresponding to the diagonal of the system's initial density operator--with respect to a chosen measurement basis are transferred

Mikhail Borovoi, Zinovy Reichstein, Philippe Gille

For a connected reductive group $G$ over a local or global field $K$, we define a *diamond* (or *power*) operation $$(\xi,n)\mapsto \xi^{\Diamond n}\,\colon\, H^1(K,G)\times {\mathbb Z}\to H^1(K,G)$$ of raising to power $n$ in the Galois cohomology pointed set (this operation is new when $K$ is a number field). We show that this power operation has many good

Giovanni Franzina

In two spatial dimensions, we discuss the relation between the solvability of Schiffer's overdetermined problem and the optimality, among sets of prescribed area, of the first eigenvalue in the buckling problem for a clamped plate and that of the first eigenvalue of the Stokes operator. For the latter, we deduce that the minimisers under area constraint that

Robbie Holland, Rebecca Kaye, Ahmed M. Hagag, Oliver Leingang

Diseases are currently managed by grading systems, where patients are stratified by grading systems into stages that indicate patient risk and guide clinical management. However, these broad categories typically lack prognostic value, and proposals for new biomarkers are currently limited to anecdotal observations. In this work, we introduce a deep-learning-

Feras Saad, Jacob Burnim, Colin Carroll, Brian Patton

Spatiotemporal datasets, which consist of spatially-referenced time series, are ubiquitous in diverse applications, such as air pollution monitoring, disease tracking, and cloud-demand forecasting. As the scale of modern datasets increases, there is a growing need for statistical methods that are flexible enough to capture complex spatiotemporal dynamics and

Liuhong Chen, Ju Ming, Max D. Gunzburger

A stochastic optimal control problem for incompressible Newtonian channel flow past a circular cylinder is used as a prototype optimal control problem for the stochastic Navier-Stokes equations. The inlet flow and the rotation speed of the cylinder are allowed to have stochastic perturbations. The control acts on the cylinder via adjustment of the rotation s

Lingyun Xu, Bowen Wang, Huiyong Li, Ziyang Cheng

In this letter, we investigate enhancing the physical layer security (PLS) for the dual-function radar-communication (DFRC) system with hybrid beamforming (HBF) architecture, where the base station (BS) achieves downlink communication and radar target detection simultaneously. We consider an eavesdropper intercepting the information transmitted from the BS t

Andrew Parry, Maik Fröbe, Sean MacAvaney, Martin Potthast

Modern sequence-to-sequence relevance models like monoT5 can effectively capture complex textual interactions between queries and documents through cross-encoding. However, the use of natural language tokens in prompts, such as Query, Document, and Relevant for monoT5, opens an attack vector for malicious documents to manipulate their relevance score through

Christos Koutras, Jiani Zhang, Xiao Qin, Chuan Lei

How can we discover join relationships among columns of tabular data in a data repository? Can this be done effectively when metadata is missing? Traditional column matching works mainly rely on similarity measures based on exact value overlaps, hence missing important semantics or failing to handle noise in the data. At the same time, recent dataset discove

Quzhe Huang, Zhenwei An, Nan Zhuang, Mingxu Tao

In this paper, we introduce a novel dynamic expert selection framework for Mixture of Experts (MoE) models, aiming to enhance computational efficiency and model performance by adjusting the number of activated experts based on input difficulty. Unlike traditional MoE approaches that rely on fixed Top-K routing, which activates a predetermined number of exper

Maximilian A. Weissflog, Jinyong Ma, Jihua Zhang, Tongmiao Fan

Nonlinear metasurfaces have recently been established as a new platform for generating photon pairs via spontaneous parametric down-conversion. While for classical harmonic generation in metasurfaces a high level of control over all degrees of freedom of light has been reached, this capability is yet to be developed for photon pair generation. In this work,

Cassius Henrique Xavier Oliveira, Fabio Nogueira Demarqui, Vinicius Diniz Mayrink

The Yang and Prentice (YP) regression models have garnered interest from the scientific community due to their ability to analyze data whose survival curves exhibit intersection. These models include proportional hazards (PH) and proportional odds (PO) models as specific cases. However, they encounter limitations when dealing with multivariate survival data

A. Fiori, M. Razzano, A. K. Harding, M. Kerr

The goal of our work is to study the mode changes of the radio-quiet gamma-ray pulsar PSR J2021+4026 with improved detail. By accurately characterizing variations in the gamma-ray spectrum and pulse profile, we aim to relate the Fermi-LAT observations to theoretical models and interpret the mode changes in terms of variations in the structure of a multipolar

Qinghao Hu, Zhisheng Ye, Zerui Wang, Guoteng Wang

Large Language Models (LLMs) have presented impressive performance across several transformative tasks. However, it is non-trivial to efficiently utilize large-scale cluster resources to develop LLMs, often riddled with numerous challenges such as frequent hardware failures, intricate parallelization strategies, and imbalanced resource utilization. In this p

Djavan De Clercq, Adam Mahdi

Yield forecasting, the science of predicting agricultural productivity before the crop harvest occurs, helps a wide range of stakeholders make better decisions around agricultural planning. This study aims to investigate whether machine learning-based yield prediction models can capably predict Kharif season rice yields at the district level in India several

Étienne André, Engel Lefaucheux, Dylan Marinho

Information leakage can have dramatic consequences on the security of real-time systems. Timing leaks occur when an attacker is able to infer private behavior depending on timing information. In this work, we propose a definition of expiring timed opacity w.r.t. execution time, where a system is opaque whenever the attacker is unable to deduce the reachabili

S. H. Jafari, S. R. Musawi

For a simple graph $G$, the $2$-distance graph, $D_2(G)$, is a graph with the vertex set $V(G)$ and two vertices are adjacent if and only if their distance is $2$ in the graph $G$. In this paper, for graphs $G$ with diameter 2, we show that $diam(D_2(G))$ can be any integer $t\geqslant2$. For graphs $G$ with $diam(G)\geqslant3$, we prove that $\frac{1}{2}dia

Michele Mastella, Tesse Tiemens, Elisabetta Chicca

In this paper, we present a novel spiking neural network model designed to perform frequency decomposition of spike trains. Our model emulates neural microcircuits theorized in the somatosensory cortex, rendering it a biologically plausible candidate for decoding the spike trains observed in tactile peripheral nerves. We demonstrate the capacity of simple ne

Andrea Cavagna, Javier Cristín, Irene Giardina, Tomas S. Grigera

Experiments on bird flocks and midge swarms reveal that these natural systems are well described by an active theory in which conservation laws play a crucial role. By building a symplectic structure that couples the particles' velocities to the generator of their internal rotations (spin), the Inertial Spin Model (ISM) reinstates a second-order temporal dyn

Yunlei Wang

We study the relation between propagation of smallness in the plane and control for heat equations. The former has been proved by Zhu who showed how the value of solutions in some small set propagates to a larger domain. By reviewing his proof, we establish a quantitative version with the explicit dependence of parameters. Using this explicit version, we est

Liwei Yuan, Hideaki Ishii

We study a multi-agent resilient consensus problem, where some agents are of the Byzantine type and try to prevent the normal ones from reaching consensus. In our setting, normal agents communicate with each other asynchronously over multi-hop relay channels with delays. To solve this asynchronous Byzantine consensus problem, we develop the multi-hop weighte

Daniela Alvarado, Seemal Asif

Purpose: Over the last few decades, the development of the hardware and software has enabled the application of advanced systems. In the robotics field, the UI design is an intriguing area to be explored due to the creation of devices with a wide range of functionalities in a reduced size. Moreover, the idea of using the same UI to control several systems ar

Marco Faroni, Dmitry Berenson

Robotic manipulation relies on analytical or learned models to simulate the system dynamics. These models are often inaccurate and based on offline information, so that the robot planner is unable to cope with mismatches between the expected and the actual behavior of the system (e.g., the presence of an unexpected obstacle). In these situations, the robot s

Ke Jia, Jingyu Yao, Xiaobo He, Yupeng Li

Magnetic Weyl semimetal (MWS) is a unique topological state with open surface Fermi arc states and other exotic transport phenomena. However, most reported MWSs show multiple pairs of Weyl points and complicated Fermi surfaces, which increases the difficulty of the investigation into the intrinsic chiral transport property. In this wor, we successfully synth

Vu Minh Hieu Phan, Yutong Xie, Yuankai Qi, Lingqiao Liu

Medical vision language pre-training (VLP) has emerged as a frontier of research, enabling zero-shot pathological recognition by comparing the query image with the textual descriptions for each disease. Due to the complex semantics of biomedical texts, current methods struggle to align medical images with key pathological findings in unstructured reports. Th

Angelos Dimakos, Daniel Woodhall, Seemal Asif

Drones are also known as UAVs are originally designed for military purposes. With the technological advances, they can be seen in most of the aspects of life from filming to logistics. The increased use of drones made it sometimes essential to form a collaboration between them to perform the task efficiently in a defined process. This paper investigates the

Vivek K. Agrawal

AstroSat observed transient neutron star low-mass X-ray binary XTE J1701-462 for a total duration of $\sim$ 135 ks during its 2022 outburst. The source traced a complete `Z' shaped structure in the hardness intensity diagram (HID). The source exhibited an extended horizontal branch and a short-dipping flaring branch in the HID. We find that most suitable spe

Krzysztof Bartoszek, Wojciech Bartoszek

We characterize the family of continuous functions $f\in C([0,1])$ such that the iterates $\widehat{T}^{k}_{i} f$ converge uniformly on $[0,1]$, where $\widehat{T}_i$ is a generalized Kantorovich operator. This gives an affirmative answer to the problem raised in 2021 by Acu and Rasa.

Gregory W. Kyro, Matthew T. Martin, Eric D. Watt, Victor S. Batista

The link between in vitro hERG ion channel inhibition and subsequent in vivo QT interval prolongation, a critical risk factor for the development of arrythmias such as Torsade de Pointes, is so well established that in vitro hERG activity alone is often sufficient to end the development of an otherwise promising drug candidate. It is therefore of tremendous

Bowen Yang, Jie Cheng, Bohuan Xue, Jianhao Jiao

Navigation in complex 3D scenarios requires appropriate environment representation for efficient scene understanding and trajectory generation. We propose a highly efficient and extensible global navigation framework based on a tomographic understanding of the environment to navigate ground robots in multi-layer structures. Our approach generates tomogram sl

Feilong Tang, Zhongxing Xu, Zhaojun Qu, Wei Feng

Recent weakly supervised semantic segmentation (WSSS) methods strive to incorporate contextual knowledge to improve the completeness of class activation maps (CAM). In this work, we argue that the knowledge bias between instances and contexts affects the capability of the prototype to sufficiently understand instance semantics. Inspired by prototype learning

Sergey Savchenko

For a regular tournament $T$ of order $n,$ denote by $c_{8}(T)$ the number of cycles of length $8$ in $T.$ Let $DR_{n}$ be a doubly-regular tournament of order $n\equiv 3\mod4$ (so, the out-sets and in-sets of its vertices are also regular and hence, contain the maximum possible number of cyclic triples) and $RLT_{n}$ be the unique regular locally transitive

Folkmar Bornemann

The large-matrix limit laws of the rescaled largest eigenvalue of the orthogonal, unitary, and symplectic $n$-dimensional Gaussian ensembles -- and of the corresponding Laguerre ensembles (Wishart distributions) for various regimes of the parameter $\alpha$ (degrees of freedom $p$) -- are known to be the Tracy-Widom distributions $F_\beta$ ($\beta=1,2,4$). W

Thilo Spinner, Rebecca Kehlbeck, Rita Sevastjanova, Tobias Stähle

Large language models (LLMs) are widely deployed in various downstream tasks, e.g., auto-completion, aided writing, or chat-based text generation. However, the considered output candidates of the underlying search algorithm are under-explored and under-explained. We tackle this shortcoming by proposing a tree-in-the-loop approach, where a visual representati

Jonas Berx, Karel Proesmans

Biological processes that are able to discriminate between different molecules consume energy and dissipate heat. They operate at different levels of fidelity and speed, and as a consequence there exist fundamental trade-offs between these quantities and the entropy production rate. Usually, the energy source required to operate in a high-fidelity regime com

Ealeal Bear, Noam Soker

We identify a point-symmetric morphology of the supernova remnant (SNR) Cassiopeia A compatible with shaping by at least two, and more likely more than four, pairs of opposite jets, as expected in the jittering jets explosion mechanism (JJEM) of core-collapse supernovae. Using an old Spitzer Telescope infrared map of argon, we identify seven pairs of opposit

Rémi Lemoy

Do cities have just one or several centers? Studies performing radial or monocentric analyses of cities are usually criticised by researchers stating that cities are actually polycentric, and this has been well known for a long time. Reversely, when cities are studied independently of any center, other researchers will wonder how the variables of interest ev

Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan

Sequential recommender systems (SRS) could capture dynamic user preferences by modeling historical behaviors ordered in time. Despite effectiveness, focusing only on the \textit{collaborative signals} from behaviors does not fully grasp user interests. It is also significant to model the \textit{semantic relatedness} reflected in content features, e.g., imag

Yi Zeng, Zhengning Wang, Yuxuan Liu, Tianjiao Zeng

Dark image enhancement aims at converting dark images to normal-light images. Existing dark image enhancement methods take uncompressed dark images as inputs and achieve great performance. However, in practice, dark images are often compressed before storage or transmission over the Internet. Current methods get poor performance when processing compressed da

Gabriel Toshio Hirokawa Higa, Rodrigo Stuqui Monzani, Jorge Fernando da Silva Cecatto, Maria Fernanda Balestieri Mariano de Souza

Smart indoor tourist attractions, such as smart museums and aquariums, usually require a significant investment in indoor localization devices. The smartphone Global Positional Systems use is unsuitable for scenarios where dense materials such as concrete and metal block weaken the GPS signals, which is the most common scenario in an indoor tourist attractio

S. R. Hassan, Gopal Prakash, N. S. Vidhyadhiraja, T. V. Ramakrishnan

In this paper, we present a theoretical framework for understanding the Extremely Correlated Fermi Liquid (ECFL) phenomenon within the $U=\infty$ Hubbard model. Our approach involves deriving equations of motion for the single-particle Green's function $G$ and its associated self-energy $\Sigma$, which involves the product of the bosonic correlation function

Zhen Zhang

Let $A$ be a finite dimensional algebra over an algebraically closed field. We present a relationship between simple-minded systems and coherent rings.

Fabian Michel, Markus Siegle

We study the approximation of a Markov chain on a reduced state space, for both discrete- and continuous-time Markov chains. In this context, we extend the existing theory of formal error bounds for the approximated transient distributions. As a special case, we consider aggregated (or lumped) Markov chains, where the state space reduction is achieved by par

Avichai Snir, Daniel Levy, Dudi Levy, Haipeng Allan Chen

We report the results of surveys we conducted in the US and Israel in 2020, a time when many prices increased following the spread of the pandemic. To assess respondents perceptions of price increases, we focus on goods whose prices have increased during the pandemic, including some essential goods. Consistent with the principle of dual entitlement, we find

M. Julia Flores, Melissa Ruiz-Vásquez, Ana Bastos, René Orth

This paper describes how to analyze the influence of Earth system variables on the errors when providing temperature forecasts. The initial framework to get the data has been based on previous research work, which resulted in a very interesting discovery. However, the aforementioned study only worked on individual correlations of the variables with respect t

Yvon Bossut

In the first part of this work the notion of stable Kim-forking is discussed and some context on this matter is given. In the second part a general way of building some examples of NSOP1 theories as the limit of some Fraisse class satisfying stronger conditions is given. These limits will satisfy existence, that Kim-independence coincide with algebraic indep

Arunima Bhattacharya

This thesis studies the pseudoscalar Higgs boson production via gluon fusion in the EFT framework in a CP-conserving model. First, it presents the di-pseudoscalar Higgs boson production cross-section via gluon fusion till NNLO with the results valid for the pseudoscalar Higgs boson of MSSM and 2HDM with small tan $\beta$ by adjusting the top Yukawa coupling.

Tore Boybeyi, Vuk Mandic, Alexandros Papageorgiou

We study the impact of gravitational wave memory on the distribution of far away light sources in the sky. For the first time we compute the built up of small, but permanent tensor distortions of the metric over cosmological time-scales using realistic models of compact binary coalescences (CBCs) whose rate of occurrence is extrapolated at $z\sim {\cal O}(1)

Anita Silva, Maria Tracy, Katharina Reinecke, Eytan Adar

Though images are ubiquitous across Wikipedia, it is not obvious that the image choices optimally support learning. When well selected, images can enhance learning by dual coding, complementing, or supporting articles. When chosen poorly, images can mislead, distract, and confuse. We developed a large dataset containing 470 questions & answers to 94 Wikipedi

Steffen Lange, Jannik Schmied, Paul Willam, Anja Voss-Böhme

Regulation of cell proliferation is a crucial aspect of tissue development and homeostasis and plays a major role in morphogenesis, wound healing, and tumor invasion. A phenomenon of such regulation is contact inhibition, which describes the dramatic slowing of proliferation, cell migration and individual cell growth when multiple cells are in contact with e

Vinay Chakravarthi Gogineni, Esmaeil S. Nadimi

Machine unlearning has garnered significant attention due to its ability to selectively erase knowledge obtained from specific training data samples in an already trained machine learning model. This capability enables data holders to adhere strictly to data protection regulations. However, existing unlearning techniques face practical constraints, often cau

Steven Christe, Lindsay Glesener, Camilo Buitrago-Casas, Shin-Nosuke Ishikawa

The Focusing Optics X-ray Solar Imager (FOXSI) sounding rocket payload flew for the second time on 2014 December 11. To enable direct Hard X-Ray (HXR) imaging spectroscopy, FOXSI makes use of grazing-incidence replicated focusing optics combined with fine-pitch solid-state detectors. FOXSI's first flight provided the first HXR focused images of the Sun. For

Surajit Basak, Andrzej Ptok

Altermagnetic ruthenium oxide RuO$_{2}$ crystallizes with P4$_{2}$/mnm symmetry. Here we discuss the lattice dynamics of this structure. We show and discuss the phonon dispersion and density of states. The phonon dispersion curves contain several Dirac nodal lines and highly degenerate Dirac points. We present the characteristic frequencies and their irreduc

Xiaoda Wang, Yuan Tang, Tengda Guo, Bo Sang

Machine Learning (ML) has become ubiquitous, fueling data-driven applications across various organizations. Contrary to the traditional perception of ML in research, ML workflows can be complex, resource-intensive, and time-consuming. Expanding an ML workflow to encompass a wider range of data infrastructure and data types may lead to larger workloads and in

Jayakrishna Vijayakumar, Lisa Mathew

Graph grammars form an interesting area of research because of their versatility in modelling diverse situations with graphs as the structures which are to be manipulated. A new class of graph grammars, nc-eNCE Graph Grammars has been introduced recently with an aim of restricting the order of application of graph production rules, thereby generating differe

Robert de Mello Koch, Garreth Kemp, Hendrik J. R. Van Zyl

Bilocal holography provides a constructive approach to the vector model/higher spin gravity duality. It has two ingredients: a change of field variables and a change of space time coordinates. The change of field variables ensures that the loop expansion parameter becomes ${1\over N}$. The change of coordinates solves the Clebsch-Gordan problem of moving fro

Michael Ogezi, Ning Shi

In text-to-image generation, using negative prompts, which describe undesirable image characteristics, can significantly boost image quality. However, producing good negative prompts is manual and tedious. To address this, we propose NegOpt, a novel method for optimizing negative prompt generation toward enhanced image generation, using supervised fine-tunin

Lorenzo Piroli, Georgios Styliaris, J. Ignacio Cirac

We introduce protocols to prepare many-body quantum states with quantum circuits assisted by local operations and classical communication. We show that by lifting the requirement of exact preparation, one can substantially save resources. In particular, the so-called $W$ and, more generally, Dicke states require a circuit depth and number of ancillas per sit

Łukasz Struski, Adam Pardyl, Jacek Tabor, Bartosz Zieliński

Partial Multi-label Learning (PML) is a type of weakly supervised learning where each training instance corresponds to a set of candidate labels, among which only some are true. In this paper, we introduce \our{}, a novel probabilistic approach to this problem that extends the binary cross entropy to the PML setup. In contrast to existing methods, it does no

Amandine Kaiser, Nikki Vercauteren, Sebastian Krumscheid

A single-column model is used to investigate regime transitions within the stable atmospheric boundary layer, focusing on the role of small-scale fluctuations in wind and temperature dynamics and of turbulence intermittency as triggers for these transitions. Previous studies revealed abrupt near-surface temperature inversion transitions within a limited wind

Song Tang, Wenxin Su, Mao Ye, Boyu Wang

In the pursuit of transferring a source model to a target domain without access to the source training data, Source-Free Domain Adaptation (SFDA) has been extensively explored across various scenarios, including Closed-set, Open-set, Partial-set, and Generalized settings. Existing methods, focusing on specific scenarios, not only address a limited subset of

Janne Heittokangas, Zinelaabidine Latreuch

The sizes of subsets of the natural numbers are typically quantified in terms of asymptotic (linear) and logarithmic densities. These concepts have been generalized to weighted $w$-densities, where a specific weight function $w$ plays a key role. In this paper, a parallel theory of asymptotic $\psi$-densities is introduced, where the weight is expressed slig

Shuangping Han, Pengyu Zan, Yu Yan, Yaoxing Bian

Over the past few decades, thin film optoelectronic devices based on transition metal dichalcogenides (TMDs) have made significant progress. However, the sensitivity of the exciton states to environmental change presents challenges for device applications. This work reports on the evolution of photo-induced exciton states in monolayer WS2 in a chamber with l

Jørgen Bang-Jensen, Yun Wang, Anders Yeo

It is well-known and easy to show that even the following version of the directed travelling salesman problem is NP-complete: Given a strongly connected complete digraph $D=(V,A)$, a cost function $w: A\rightarrow \{0,1\}$ and a natural number $K$; decide whether $D$ has a directed Hamiltonian cycle of cost at most $K$. We study the following variant of this