March 2024 arXiv papers — page 108

Marco Castellano, Lorenzo Napolitano, Adriano Fontana, Guido Roberts-Borsani

We spectroscopically confirm the $M_{\rm UV} = -20.5$ mag galaxy GHZ2/GLASS-z12 to be at redshift $z=12.34$. The source was selected via NIRCam photometry in GLASS-JWST ERS data, providing the first evidence of a surprising abundance of bright galaxies at $z \gtrsim 10$. The NIRSpec PRISM spectrum shows detections of N IV, C IV, He II, O III, C III, O II, an

Elnaz Zafarani-Moattar, Mohammad Reza Kangavari, Amir Masoud Rahmani

Topic detection is a complex process and depends on language because it somehow needs to analyze text. There have been few studies on topic detection in Persian, and the existing algorithms are not remarkable. Therefore, we aimed to study topic detection in Persian. The objectives of this study are: 1) to conduct an extensive study on the best algorithms for

Wei Lin, Antoni B. Chan

Existing class-agnostic counting models typically rely on a single type of prompt, e.g., box annotations. This paper aims to establish a comprehensive prompt-based counting framework capable of generating density maps for concerned objects indicated by various prompt types, such as box, point, and text. To achieve this goal, we begin by converting prompts fr

T. Adamantopoulos, M. Merte, F. Freimuth, D. Go

While the understanding of altermagnetism is still at a very early stage, it is expected to play a role in various fields of condensed matter research, for example spintronics, caloritronics and superconductivity. In the field of optical magnetism, it is still unclear to which extent altermagnets as a class can exhibit a distinct behavior. Here we choose RuO

Florent Fessler, Martin Wittman, Juliane Simmchen, Antonio Stocco

The ability to design artificial micro/nanomachines able to perform sophisticated tasks crucially depends on the understanding of their interaction with biosystems and their compatibility with the biological environment. Here, Janus colloids fuelled only by glucose and light were designed, which can autonomously interact with cell-like compartments and trigg

Swayamtrupta Panda, Szymon Kozłowski, Mariusz Gromadzki, Marcin Wrona

We use the spectroscopic data collected by the Magellanic Quasars Survey (MQS) as well as the photometric V- and I-band data from the Optical Gravitational Lensing Experiment (OGLE) to measure the physical parameters for active galactic nuclei (AGNs) located behind the Magellanic Clouds. The flux-uncalibrated MQS spectra were obtained with the 4-m Anglo-Aust

Sajad Faramarzi, Farzan Haddadi, Sajjad Amini, Masoud Ahookhosh

Conventional matrix completion methods approximate the missing values by assuming the matrix to be low-rank, which leads to a linear approximation of missing values. It has been shown that enhanced performance could be attained by using nonlinear estimators such as deep neural networks. Deep fully connected neural networks (FCNNs), one of the most suitable a

Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao

To deduce new facts on a knowledge graph (KG), a link predictor learns from the graph structure and collects local evidence to find the answer to a given query. However, existing methods suffer from a severe scalability problem due to the utilization of the whole KG for prediction, which hinders their promise on large scale KGs and cannot be directly address

Shanshan Zhang, Wen Chen, Qingqing Wu, Ziwei Liu

This paper studies the fair transmission design for an intelligent reflecting surface (IRS) aided rate-splitting multiple access (RSMA). IRS is used to establish a good signal propagation environment and enhance the RSMA transmission performance. The fair rate adaption problem is constructed as a max-min optimization problem. To solve the optimization proble

Huimin Huang, Wensheng Zhang

This paper investigates the convergence rate for Tikhonov regularization of the problem of identifying the coefficient $a \in L^{\infty}(\Omega)$ in the Robin-boundary equation $-\mathrm{div}(a\nabla u)-bu=f,~ x \in \Omega \subset \mathbb R^M,~ M \geq 1$ and $u=0,~ x ~on~ \partial\Omega$, where $f(x)\in L^{\infty}(\Omega)$. Assume we only know the imprecise

Yueqian Wang, Xiaojun Meng, Jianxin Liang, Yuxuan Wang

Video-text Large Language Models (video-text LLMs) have shown remarkable performance in answering questions and holding conversations on simple videos. However, they perform almost the same as random on grounding text queries in long and complicated videos, having little ability to understand and reason about temporal information, which is the most fundament

Jiang Wei, Chen Yanjun

We explore the properties of 4110 nuclides from Z = 5 to Z = 82 with the Sky3D code and the composition of the outer crust in the magnetars under extreme magnetic fields. The effects of the variation of the nuclear masses due to the magnetic fields on the outer crust are comprehensively studied. The neutron-drip transition pressure, the equation of state and

Krzysztof Gogol, Robin Fritsch, Malte Schlosser, Johnnatan Messias

This paper studies liquid staking tokens (LSTs) on automated market makers (AMMs), both theoretically and empirically. LSTs are tokenized representations of staked assets on proof-of-stake blockchains. First, we model LST-liquidity on AMMs theoretically, categorizing suitable AMM types for LST liquidity and deriving formulas for the necessary returns from tr

Jesse S. Schelfhout, Thomas M. Hird, Kenneth M. Hughes, Christopher J. Foot

The leading experimental determinations of the fine-structure constant, $\alpha$, currently rely on atomic photon-recoil measurements from Ramsey-Bord\'e atom interferometry with large momentum transfer to provide an absolute mass measurement. We propose an experimental scheme for an intermediate-scale differential atom interferometer to measure the photon-r

M. A. Anacleto, F. A. Brito, E. Passos

In this paper, we analysis the dynamics, at the quantum level, of the self-dual field minimally coupled to bosons with Lorentz symmetry breaking. We quantize the model by applying the Dirac bracket canonical quantization procedure. In addition, we test the relativistic invariance of the model by computing the boson-boson elastic scattering amplitude. Therefo

Qinchun Ma, Yuhan Wen, Xue-Bing Wu, Huapeng Gu

In our previous work on broadband photometric reverberation mapping (PRM), we proposed the ICCF-Cut process to obtain the time lags of H$\alpha$ emission line from two broadband lightcurves via subtracting the continuum emission from the line band. Extending the work, we enlarge our sample to the Zwicky Transient Facility (ZTF) database. We adopt two criteri

Eder Kikianty, Miek Messerschmidt, Luan Naude, Mark Roelands

Inspired by the theories of Kaplansky-Hilbert modules and probability theory in vector lattices, we generalise functional analysis by replacing the scalars $\mathbb{R}$ or $\mathbb{C}$ by a real or complex Dedekind complete unital $f$-algebra $\mathbb{L}$; such an algebra can be represented as a suitable space of continuous functions. We set up the basic the

Guido Kueppers, Jean-Pierre Busch, Lennart Reiher, Lutz Eckstein

Connectivity is a main driver for the ongoing megatrend of automated mobility: future Cooperative Intelligent Transport Systems (C-ITS) will connect road vehicles, traffic signals, roadside infrastructure, and even vulnerable road users, sharing data and compute for safer, more efficient, and more comfortable mobility. In terms of communication technology fo

F. Minotti, G. Modanese

Aharonov-Bohm electrodynamics predicts the existence of traveling waves of pure potentials, with zero electromagnetic fields, denoted as gauge waves, or g-waves for short. In general, these waves cannot be shielded by matter since their lack of electromagnetic fields prevents the material from reacting to them. However, a not-locally-conserved electric curre

Xinli Hao, Yile Chen, Chen Yang, Zhihui Du

With the development of astronomical facilities, large-scale time series data observed by these facilities is being collected. Analyzing anomalies in these astronomical observations is crucial for uncovering potential celestial events and physical phenomena, thus advancing the scientific research process. However, existing time series anomaly detection metho

Zetao Lin, Thibault Maurel-Oujia, Benjamin Kadoch, Philipp Krah

This work investigates the behavior of impurities in edge plasma of tokamaks using high-resolution numerical simulations based on Hasegawa--Wakatani equations. Specifically, it focuses on the behavior of inertial particles, which has not been extensively studied in the field of plasma physics. Our simulations utilize one-way coupling of a large number of ine

O. Gomonay, V. P. Kravchuk, R. Jaeschke-Ubiergo, K. V. Yershov

We present a phenomenological theory of altermagnets, that captures their unique magnetization dynamics and allows modelling magnetic textures in this new magnetic phase. Focusing on the prototypical d-wave altermagnets, e.g. RuO$_2$, we can explain intuitively the characteristic lifted degeneracy of their magnon spectra, by the emergence of an effective sub

Dongwon Son, Jaehyung Kim, Sanghyeon Son, Beomjoon Kim

The usage of 3D vision algorithms, such as shape reconstruction, remains limited because they require inputs to be at a fixed canonical rotation. Recently, a simple equivariant network, Vector Neuron (VN) has been proposed that can be easily used with the state-of-the-art 3D neural network (NN) architectures. However, its performance is limited because it is

Younghun Kim, Hansol Kim, Jeongsoo Kang, Wonjae Choi

Large scale quantum circuits are required to exploit the advantages of quantum computers. Despite significant advancements in quantum hardware, scalability remains a challenge, with errors accumulating as more qubits and gates are added. To overcome this limitation, quantum error-correction codes have been introduced. Although the success of quantum error co

Marcos Fernández-Rodríguez, Bruno Silva, Sandro Queirós, Helena R. Torres

Surgical instrument segmentation in laparoscopy is essential for computer-assisted surgical systems. Despite the Deep Learning progress in recent years, the dynamic setting of laparoscopic surgery still presents challenges for precise segmentation. The nnU-Net framework excelled in semantic segmentation analyzing single frames without temporal information. T

Saddam Hussain

We investigate the dynamics of an algebraically coupled quintessence field with a dark matter fluid, focusing on particle production through the action principle via a modified interaction Lagrangian. The interaction parameter serves as the source of dark matter particle production and entropy generation. As particle creation occurs due to the interaction be

Jin Cui, Fumiyo Fukumoto, Xinfeng Wang, Yoshimi Suzuki

Aspect-category-based sentiment analysis (ACSA), which aims to identify aspect categories and predict their sentiments has been intensively studied due to its wide range of NLP applications. Most approaches mainly utilize intrasentential features. However, a review often includes multiple different aspect categories, and some of them do not explicitly appear

Gangqiang Chen

Assume $z_0$ lies in the open unit disk $\mathbb{D}$ and $g$ is an analytic self-map of $\mathbb{D}$. We will determine the region of values of $g''(z_0)$ in terms of $z_0$, $g(z_0)$ and the hyperbolic derivative of $g$ at $z_0$, and give the form of all the extremal functions. In particular, we obtain a smaller sharp upper bound for $|g''(z_0)|$ than Rusche

Matthew Southerby, Robert Apsimon

In this paper, a self-consistent transverse beam dynamics framework is demonstrated, that incorporates acceleration into the transverse beam dynamics studies for a proton linac machine. Two focusing schemes are developed and discussed; the FODO-like scheme, and the minimum aperture scheme. The FODO-like scheme is a simple scheme, requiring only one quadrupol

Feng Li, Yixuan Wu, Zichao Liang, Runmin Cong

Diffusion models (DM) have achieved remarkable promise in image super-resolution (SR). However, most of them are tailored to solving non-blind inverse problems with fixed known degradation settings, limiting their adaptability to real-world applications that involve complex unknown degradations. In this work, we propose BlindDiff, a DM-based blind SR method

Matthew Southerby, Robert Apsimon

In this paper, a fast cell to cell tracking algorithm (FC2CT) is developed, that determines the change in 6D phase space of a particle beam through rf accelerating cavities operated in both Standing and Traveling Wave modes. The performance is compared to well trusted tracking codes - ASTRA and RF-Track - for proton beams with relativistic beta = 0.5. The FC

Nizar Bousselmi, Nelly Pustelnik, Julien M. Hendrickx, François Glineur

Selecting the fastest algorithm for a specific signal/image processing task is a challenging question. We propose an approach based on the Performance Estimation Problem framework that numerically and automatically computes the worst-case performance of a given optimization method on a class of functions. We first propose a computer-assisted analysis and com

Daniele Caliari, Henrik Petri

The Random Utility Model (RUM) is the leading model to represent the aggregate choices of a heterogeneous population of preference maximizers. We show that if (and only if) preferences are sufficiently uncorrelated, RUM choices can also be generated by a population of decision makers who do not maximize any preference. In proving this result, we also charact

Pradip Laha, P. A. Ameen Yasir, Peter van Loock

Harnessing entanglement and quantum coherence plays a central role in advancing quantum technologies. In quantum optical light-atom platforms, these two fundamental resources are often associated with a Jaynes-Cummings model description describing the coherent exchange of a photon between an optical resonator mode and a two-level spin. In a generic nonlinear

Peng Jia, Chao Lv, Yushan Li, Yongyang Sun

In recent years, there has been a gradual increase in the performance of Complementary Metal Oxide Semiconductor (CMOS) cameras. These cameras have gained popularity as a viable alternative to charge-coupled device (CCD) cameras in a wide range of applications. One particular application is the CMOS camera installed in small space telescopes. However, the li

Prince Kumar, Srikanth Tamilselvam, Dinesh Garg

While text summarization is a well-known NLP task, in this paper, we introduce a novel and useful variant of it called functionality extraction from Git README files. Though this task is a text2text generation at an abstract level, it involves its own peculiarities and challenges making existing text2text generation systems not very useful. The motivation be

Sebastiano Cultrera di Montesano, Ondřej Draganov, Herbert Edelsbrunner, Morteza Saghafian

Given a finite set, $A \subseteq \mathbb{R}^2$, and a subset, $B \subseteq A$, the \emph{MST-ratio} is the combined length of the minimum spanning trees of $B$ and $A \setminus B$ divided by the length of the minimum spanning tree of $A$. The question of the supremum, over all sets $A$, of the maximum, over all subsets $B$, is related to the Steiner ratio, a

Stefano Berrone, Fabio Vicini

In the present work we introduce a novel refinement algorithm for two-dimensional elliptic partial differential equations discretized with Virtual Element Method (VEM). The algorithm improves the numerical solution accuracy and the mesh quality through a controlled refinement strategy applied to the generic polygonal elements of the domain tessellation. The

Ahcen Aliouat, Elsa Dupraz

In goal-oriented communications, the objective of the receiver is often to apply a Deep-Learning model, rather than reconstructing the original data. In this context, direct learning over compressed data, without any prior decoding, holds promise for enhancing the time-efficient execution of inference models at the receiver. However, conventional entropic-co

Lukas Seemann, Angelika Knothe, Martina Hentschel

Ballistic, gate-defined devices in two-dimensional materials offer a platform for electron optics phenomena influenced by the material's properties and gate control. We study the ray trajectory dynamics of all-electronic, gate-defined cavities in bilayer graphene to establish how distinct regimes of the internal and outgoing charge carrier dynamics can be tu

Lisa-Marie Krug, Leon Cryssos, Juergen Bundesmann, Alina Dittwald

Positron annihilation experiments on an laboratory scale depend on the supply and the availability of $\beta^+$ emitters. Here we present the production of positron sources based on the $^{27}$Al(p,x)$^{22}$Na reaction by irradiation of Al with a 68\,MeV proton beam. We simulated the energy loss, range and radial scattering of the protons in Al in order to d

Louis Thiry, Long Li, Etienne Mémin, Guillaume Roullet

With a new unifying model for layered rotating shallow-water (RSW) and quasi-geostrophic (QG) equations, this paper sheds light on the relation between these two sets of equations. We propose here a new formulation of the quasi-geostrophic equations as a projection of the rotating shallow-water equations. This QG formulation uses the same prognostic variable

Kees Kok, Lin Zhou

In this paper, we generalise the construction of the functorial pullback of refined unramified cohomology between smooth schemes, by following the ideas of Fulton's intersection theory and Rost's cycle modules. We also define standard actions of algebraic cycles on the refined unramified cohomology groups of smooth proper schemes avoiding Chow's moving lemma

F. Daem, A. Matzkin

Understanding how the interference pattern produced by a quantum particle in Young's double-slit setup builds up -- the "only mystery" of quantum mechanics according to Feynman -- is still a matter of discussion and speculation. Recent works have revisited the possibility of acquiring which-way information based on weak measurements. Weak measurements preser

Enrico Le Donne, Luca Nalon

We consider 2-step free-Carnot groups equipped with sub-Finsler distances. We prove that the metric spheres are codimension-one rectifiable from the Euclidean viewpoint. The result is obtained by studying how the Lipschitz constant for the distance function behaves near abnormal geodesics.

Anita Halder, Declan Nell, Antik Sihi, Akash Bajaj

The recent emergence of van der Waals (vdW) ferromagnets has opened new opportunities for designing spintronic devices. We theoretically investigate the coherent spin-dependent transport properties of the vdW ferromagnet Fe$_4$GeTe$_2$, by using density functional theory combined with the non-equilibrium Green's functions method. We find that the conductance

Adrian Kliks

In the last few years, a very original concept of holographic communication has gained a lot of interest among scientists from all over the world. The specificity of this approach, on the one hand, is very different from the known and currently used solutions, on the other hand, it creates great development opportunities in the field of wireless communicatio

Sebastian Krebs, Tom Herter

In this paper, an Ultra-Wideband (UWB) positioning system is introduced, that leverages six identical custom-designed boards, each featuring an ESP32 microcontroller and a DWM3000 module from Quorvo. The system is capable of achieving localization with an accuracy of up to 10 cm, by utilizing Two-Way-Ranging (TWR) measurements between one designated tag and

G. A. P. Ribeiro, Gustavo Rigolin

We show that the teleportation protocol can be efficiently used to detect quantum critical points using finite temperature data even if all resources needed to its implementation lie within the system under investigation. Contrary to a previous proposal, there is no need to use an external qubit as the input state to be teleported to one of the qubits within

Tobias Kramer

The dynamics of excitonic energy transfer in molecular complexes triggered by interaction with laser pulses offers a unique window into the underlying physical processes. The absorbed energy moves through the network of interlinked pigments and in photosynthetic complexes reaches a reaction center. The efficiency and time-scale depend not only on the exciton

Chuang Lin, Yi Jiang, Lizhen Qu, Zehuan Yuan

In recent research, significant attention has been devoted to the open-vocabulary object detection task, aiming to generalize beyond the limited number of classes labeled during training and detect objects described by arbitrary category names at inference. Compared with conventional object detection, open vocabulary object detection largely extends the obje

Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib

Annotators exhibit disagreement during data labeling, which can be termed as annotator label uncertainty. Annotator label uncertainty manifests in variations of labeling quality. Training with a single low-quality annotation per sample induces model reliability degradations. In this work, we first examine the effects of annotator label uncertainty in terms o

Shengyu Fan, Xianglong Deng, Zhuoyu Tian, Zhicheng Hu

Fully Homomorphic Encryption (FHE), a novel cryptographic theory enabling computation directly on ciphertext data, offers significant security benefits but is hampered by substantial performance overhead. In recent years, a series of accelerator designs have significantly enhanced the performance of FHE applications, bringing them closer to real-world applic

Malte Mosbach, Sven Behnke

Interactive grasping from clutter, akin to human dexterity, is one of the longest-standing problems in robot learning. Challenges stem from the intricacies of visual perception, the demand for precise motor skills, and the complex interplay between the two. In this work, we present Teacher-Augmented Policy Gradient (TAPG), a novel two-stage learning framewor

Seungmo Kim

This paper examines how wireless communication affects the performance of various blockchain consensus mechanisms, focusing on their scalability and decentralization. It introduces an analytical framework for quantifying these effects, backed by extensive simulations, underscoring its broad applicability to various consensus mechanisms despite wireless commu

Aswathy Velutharambath, Amelie Wührl, Roman Klinger

If a person firmly believes in a non-factual statement, such as "The Earth is flat", and argues in its favor, there is no inherent intention to deceive. As the argumentation stems from genuine belief, it may be unlikely to exhibit the linguistic properties associated with deception or lying. This interplay of factuality, personal belief, and intent to deceiv

Malte Luttermann, Mattis Hartwig, Tanya Braun, Ralf Möller

Lifted inference exploits symmetries in probabilistic graphical models by using a representative for indistinguishable objects, thereby speeding up query answering while maintaining exact answers. Even though lifting is a well-established technique for the task of probabilistic inference in relational domains, it has not yet been applied to the task of causa

Corentin Vazia, Alexandre Bousse, Jacques Froment, Béatrice Vedel

This paper proposes a novel approach to spectral computed tomography (CT) material decomposition that uses the recent advances in generative diffusion models (DMs) for inverse problems. Spectral CT and more particularly photon-counting CT (PCCT) can perform transmission measurements at different energy levels which can be used for material decomposition. It

Arthur Thuy, Dries F. Benoit

Image classification with neural networks (NNs) is widely used in industrial processes, situations where the model likely encounters unknown objects during deployment, i.e., out-of-distribution (OOD) data. Worryingly, NNs tend to make confident yet incorrect predictions when confronted with OOD data. To increase the models' reliability, they should quantify

P. Wittig, F. Dominguez, P. Recher

Valley chiral kagom\'e networks can arise in various situations, like for example, in double-aligned graphene-hexagonal boron nitride and periodically strained graphene. Here, we construct a phenomenological scattering model based on the symmetries of the network to investigate the energy spectrum and magnetotransport in this system. Additionally, we conside

Mingcai Ding, Xiaoliang Song, Bo Yu

The optimization problem of sparse and low-rank matrix recovery is considered, which involves a least squares problem with a rank constraint and a cardinality constraint. To overcome the challenges posed by these constraints, an asymptotic difference-of-convex (ADC) method that employs a Moreau smoothing approach and an exact penalty approach is proposed to

Mingxiao Li, Bo Wan, Marie-Francine Moens, Tinne Tuytelaars

In recent years, diffusion models have made remarkable strides in text-to-video generation, sparking a quest for enhanced control over video outputs to more accurately reflect user intentions. Traditional efforts predominantly focus on employing either semantic cues, like images or depth maps, or motion-based conditions, like moving sketches or object boundi

Rodrigo C. V. Coelho, José A. Moreira, Duarte M. C. Pedro, Margarida M. Telo da Gama

A surface in contact with the isotropic phase of a passive liquid crystal can induce nematic order over distances that range from microscopic to macroscopic when the nematic-isotropic interface undergoes an orientational-wetting transition. If the nematic is active, what happens to the interface? Does it propagate and, if it does, is its structure different

Francisco Oyarzún, Vincent Chambouleyron, Benoit Neichel, Thierry Fusco

The use of artificial Laser Guide Stars (LGS) is planned for the new generation of giant segmented mirror telescopes, to extend the sky coverage of their adaptive optics systems. The LGS, being a 3D object at a finite distance will have a large elongation that will affect its use with the Shack-Hartmann (SH) wavefront sensor. In this paper, we compute the ex

Julien Bauland, Gouranga Manna, Thibaut Divoux, Thomas Gibaud

Colloidal gels undergo a phenomenon known as physical aging, i.e., a continuous change of their physical properties with time after the gel point. To date, most of the research effort on aging in gels has been focused on suspensions of hard colloidal particles. In this letter, we tackle the case of soft colloidal "micelles" comprised of proteins, where gelat

Masanari Kimura, Hideitsu Hino

Importance weighting is a fundamental procedure in statistics and machine learning that weights the objective function or probability distribution based on the importance of the instance in some sense. The simplicity and usefulness of the idea has led to many applications of importance weighting. For example, it is known that supervised learning under an ass

Simon Ans, Frédéric Zamkotsian, Guillaume Demésy

A topology optimization method is presented and applied to a blazed diffraction grating in reflection under conical incidence. This type of gratings is meant to disperse the incident light on one particular diffraction order and this property is fundamental in spectroscopy. Conventionally, a blazed metallic grating is made of a sawtooth profile designed to w

Soikat Hasan Ahmed, Jan Finkbeiner, Emre Neftci

Event cameras offer high temporal resolution and dynamic range with minimal motion blur, making them promising for robust object detection. While Spiking Neural Networks (SNNs) on neuromorphic hardware are often considered for energy-efficient and low latency event-based data processing, they often fall short of Artificial Neural Networks (ANNs) in accuracy

Ying Lei, Shuai Ma, Yuling Sun

Migration and aging-related dilemmas have limited the opportunities for late-life migrants to rebuild social connections and access support. While research on migrants has drawn increasing attention in HCI, limited attention has been paid to the increasing number of late-life migrants. This paper reports a qualitative study examining the social connections a

Irem Islek, Sule Gunduz Oguducu

Recommendation systems can provide accurate recommendations by analyzing user shopping history. A richer user history results in more accurate recommendations. However, in real applications, users prefer e-commerce platforms where the item they seek is at the lowest price. In other words, most users shop from multiple e-commerce platforms simultaneously; dif

Arkajit Datta, Tushar Verma, Rajat Chawla, Mukunda N. S

In recent advancements within the domain of Large Language Models (LLMs), there has been a notable emergence of agents capable of addressing Robotic Process Automation (RPA) challenges through enhanced cognitive capabilities and sophisticated reasoning. This development heralds a new era of scalability and human-like adaptability in goal attainment. In this

Andrés Muñoz, Daniel Borrajo

User Interface (UI) understanding has been an increasingly popular topic over the last few years. So far, there has been a vast focus solely on web and mobile applications. In this paper, we introduce the harder task of computer UI understanding. With the goal of enabling research in this field, we have generated a dataset with a set of videos where a user i

Fabio Aratore, Valerio Bozza

Light rays passing very close to black holes may wind several times before escaping. For any given electromagnetic source around the black hole, a distant observer would thus observe two infinite sequences of images on either side of the black hole. These images are generated by light rays performing an increasing numbers of loops. The strong deflection limi

Arthur Thuy, Dries F. Benoit

Uncertainty is a key feature of any machine learning model and is particularly important in neural networks, which tend to be overconfident. This overconfidence is worrying under distribution shifts, where the model performance silently degrades as the data distribution diverges from the training data distribution. Uncertainty estimation offers a solution to

Malte Luttermann, Johann Machemer, Marcel Gehrke

To allow for tractable probabilistic inference with respect to domain sizes, lifted probabilistic inference exploits symmetries in probabilistic graphical models. However, checking whether two factors encode equivalent semantics and hence are exchangeable is computationally expensive. In this paper, we efficiently solve the problem of detecting exchangeable

Peng Zheng, Tao Liu, Zili Yi, Rui Ma

With the development of neural radiance fields and generative models, numerous methods have been proposed for learning 3D human generation from 2D images. These methods allow control over the pose of the generated 3D human and enable rendering from different viewpoints. However, none of these methods explore semantic disentanglement in human image synthesis,

Subhajit Chattopadhyay

Dependence modeling of multivariate count data has garnered significant attention in recent years. Multivariate elliptical copulas are typically preferred in statistical literature to analyze dependence between repeated measurements of longitudinal data since they allow for different choices of the correlation structure. But these copulas lack in flexibility

Fadillah Adamsyah Maani, Numan Saeed, Aleksandr Matsun, Mohammad Yaqub

Deep learning (DL) models have been advancing automatic medical image analysis on various modalities, including echocardiography, by offering a comprehensive end-to-end training pipeline. This approach enables DL models to regress ejection fraction (EF) directly from 2D+time echocardiograms, resulting in superior performance. However, the end-to-end training

HaoRan Zhang, WenHuan Wang

Let $\mathcal {F}$ be a given family of graphs. A graph $G$ is $\mathcal {F}$-free if it does not contain any member of $\mathcal {F}$ as a subgraph. Let $C_{l, l}$ be a graph obtained from $2C_l$ such that the two cycles share a common vertex, where $l\geqslant3 $. A $\mathrm{Theta}$ graph is obtained from a cycle $C_k$ by adding an additional edge between

Juan José Seoane, Jorge Parra, Juan Navarro-Arenas, María Recaman

Silicon photonics arises as a viable solution to address the stringent resource demands of emergent technologies, such as neural networks. Within this framework, photonic memories are fundamental building blocks of photonic integrated circuits that have not yet found a standardized solution due to several trade-off among different metrics such as energy cons

Anita Lande, Anil Khairnar

Let $R$ be a ring with involution $*$ and $Z^*(R)$ denotes the set of all non-zero zero-divisors of $R$. We associate a simple (undirected) graph $\Gamma'(R)$ with vertex set $Z^*(R)$ and two distinct vertices $x$ and $y$ are adjacent in $\Gamma'(R)$ if and only if $x^ny^*=0$ or $y^nx^*=0$, for some positive integer $n$. We find the diameter and girth of $\G

Qiqi Zhou, Yichen Zhu

This paper investigates the Neural Tangent Kernel (NTK) to search vision transformers without training. In contrast with the previous observation that NTK-based metrics can effectively predict CNNs performance at initialization, we empirically show their inefficacy in the ViT search space. We hypothesize that the fundamental feature learning preference withi

Guoxi Zhang, Han Bao, Hisashi Kashima

In preference-based reinforcement learning (PbRL), a reward function is learned from a type of human feedback called preference. To expedite preference collection, recent works have leveraged \emph{offline preferences}, which are preferences collected for some offline data. In this scenario, the learned reward function is fitted on the offline data. If a lea

A. M. Vibhakar, D. D. Khalyavin, F. Orlandi, J. M. Moya

We demonstrate the spontaneous reversal of spin chirality in a single crystal sample of the intermetallic magnet EuAl$_4$. We solve the nanoscopic nature of each of the four magnetically phases of EuAl$_4$ using resonant magnetic x-ray scattering, and demonstrate all four phases order with single-k incommensurate magnetic modulation vectors. Below 15.4 K the

Tobia Boschi, Francesca Bonin, Rodrigo Ordonez-Hurtado, Cécile Rousseau

This paper introduces a novel Functional Graph Convolutional Network (funGCN) framework that combines Functional Data Analysis and Graph Convolutional Networks to address the complexities of multi-task and multi-modal learning in digital health and longitudinal studies. With the growing importance of health solutions to improve health care and social support

Wolfram Bauer, Abdellah Laaroussi, Daisuke Tarama

Four subriemannian (SR) structures over the Euclidean sphere $\mathbb{S}^7$ are considered in accordance to the previous literature. The defining bracket generating distribution is chosen as the horizontal space in the Hopf fibration, the quaternionic Hopf fibration or spanned by a suitable number of canonical vector fields. In all cases the induced SR geode

Benjamin Strandli Fermann, John Nyberg, Espen W. Remme, Jahn Frederik Grue

Cardiac valve event timing plays a crucial role when conducting clinical measurements using echocardiography. However, established automated approaches are limited by the need of external electrocardiogram sensors, and manual measurements often rely on timing from different cardiac cycles. Recent methods have applied deep learning to cardiac timing, but they

K. Suzuki, P. T. Dang, H. Homma, A. A. Fathnan

We present an effective method for transmitting electromagnetic waves as surface waves with a tape-based metasurface design. This design incorporates silver square patches periodically patterned on an adhesive tape substrate. Specifically, our study proposes a strategy to enhance the efficiency of power transfer in high-frequency bands by guiding signals as

Tobias Wand, Oliver Kamps, Benjamin Skjold

Cooperation between individuals is emergent in all parts of society, yet mechanistic reasons for this emergence is ill understood in the literature. A specific example of this is insurance. Recent work has, though, shown that assuming the risk individuals face is proportional to their wealth and optimising the time average growth rate rather than the ensembl

Stefan Andronic, Simona Nistor

In this paper we determine a larger gap of the mean curvature for a class of proper biharmonic submanifolds with parallel mean curvature vector field in Euclidean spheres. When the bounds of the gap are reached, we obtain splitting results of the submanifold.

Niklas Leimeroth, Jochen Rohrer, Karsten Albe

Silicon oxycarbides show outstanding versatility due to their highly tunable composition and microstructure. Consequently, a key challenge is a thorough knowledge of structure-property relations in the system. In this work, we fit an atomic cluster expansion potential to a set of actively learned DFT training data spanning a wide configurational space. We de

Yogesh Kumar, Pekka Marttinen

We introduce eCLIP, an enhanced version of the CLIP model that integrates expert annotations in the form of radiologist eye-gaze heatmaps. It tackles key challenges in contrastive multi-modal medical imaging analysis, notably data scarcity and the "modality gap" -- a significant disparity between image and text embeddings that diminishes the quality of repre

Jordi-Lluís Figueras, Alex Haro

In this paper, we present evidence of the stability of a simplified model of the Solar System, a flat (Newtonian) Sun-Jupiter-Saturn system with realistic data: masses of the Sun and the planets, their semi-axes, eccentricities and (apsidal) precessions of the planets close to the real ones. The evidence is based on convincing numerics that a KAM theorem can

Paul Baconnier, Olivier Dauchot, Vincent Démery, Gustavo Düring

Self-alignment describes the property of a polar active unit to align or anti-align its orientation towards its velocity. In contrast to mutual alignment, where the headings of multiple active units tend to directly align to each other -- as in the celebrated Vicsek model --, self-alignment impacts the dynamics at the individual level by coupling the rotatio

Y. Omiya, K. Nakazawa, T. Tamura, H. Akamatsu

Abell 3667 is a nearby merging cluster with a prominent cold front and a pair of two bright radio relics. Assuming a head-on merger, the origin of the cold front is often considered to be a remnant of the cluster core stripped by its surrounding ICM. Some authors have proposed an offset merger scenario in which the subcluster core rotates after the first cor

Yuki Amari, Nobuyuki Sawado, Shintaro Yamamoto

The spectral flow is ubiquitous in the physics of soliton-fermion interacting systems. We study the spectral flows related to a continuous deformation of background soliton solutions, which enable us to develop insight into the emergence of fermionic zero modes and the localization mechanism of fermion densities. We investigate a $\CP^2$ nonlinear sigma mode

Kyoung-Min Kim, Ki-Seok Kim

Understanding the influence of quenched random potential is crucial for comprehending the exotic electronic transport of non-Fermi liquid metals near metallic quantum critical points. In this study, we identify a stable fixed point governing the quantum critical behavior of two-dimensional non-Fermi liquid metals in the presence of a random potential disorde

Hao Li, Yuanyuan Gao, Chenming Wu, Dingwen Zhang

This paper presents GGRt, a novel approach to generalizable novel view synthesis that alleviates the need for real camera poses, complexity in processing high-resolution images, and lengthy optimization processes, thus facilitating stronger applicability of 3D Gaussian Splatting (3D-GS) in real-world scenarios. Specifically, we design a novel joint learning

Qian Wang, Jia-Chen Gu, Zhen-Hua Ling

Audio-text retrieval (ATR), which retrieves a relevant caption given an audio clip (A2T) and vice versa (T2A), has recently attracted much research attention. Existing methods typically aggregate information from each modality into a single vector for matching, but this sacrifices local details and can hardly capture intricate relationships within and betwee

Ruiyang Hao, Siqi Fan, Yingru Dai, Zhenlin Zhang

The value of roadside perception, which could extend the boundaries of autonomous driving and traffic management, has gradually become more prominent and acknowledged in recent years. However, existing roadside perception approaches only focus on the single-infrastructure sensor system, which cannot realize a comprehensive understanding of a traffic area bec