April 2024 arXiv papers — page 159

Xize Liang, Chao Chen, Shuang Qiu, Jie Wang

Preference alignment is pivotal for empowering large language models (LLMs) to generate helpful and harmless responses. However, the performance of preference alignment is highly sensitive to the prevalent noise in the preference data. Recent efforts for this problem either marginally alleviate the impact of noise without the ability to actually reduce its p

Lucas Böttcher, Gregory Wheeler

The field of neuroscience and the development of artificial neural networks (ANNs) have mutually influenced each other, drawing from and contributing to many concepts initially developed in statistical mechanics. Notably, Hopfield networks and Boltzmann machines are versions of the Ising model, a model extensively studied in statistical mechanics for over a

Samuel Beck, Nina Doerr, Kuno Kurzhals, Alexander Riedlinger

Sports visualization has developed into an active research field over the last decades. Many approaches focus on analyzing movement data recorded from unstructured situations, such as soccer. For the analysis of choreographed activities like formation dancing, however, the goal differs, as dancers follow specific formations in coordinated movement trajectori

Evelyn J. Johnston, Gaspar Galaz, Matias Blaña, Philippe Amram

Aims. The central region of the Giant Low Surface Brightness galaxy Malin 1 has long been known to have a complex morphology with evidence of a bulge, disc, and potentially a bar hosting asymmetric star formation. In this work, we use VLT/MUSE data to resolve the central region of Malin 1 in order to determine its structure. Methods. We use careful light pro

Qiushi Li, Yan Zhang, Ju Ren, Qi Li

Image data have been extensively used in Deep Neural Network (DNN) tasks in various scenarios, e.g., autonomous driving and medical image analysis, which incurs significant privacy concerns. Existing privacy protection techniques are unable to efficiently protect such data. For example, Differential Privacy (DP) that is an emerging technique protects data wi

David Winkelmann, Charlotte Köhler

The growing e-grocery sector faces challenges in becoming profitable due to heightened customer expectations and logistical complexities. This paper addresses the impact of uncertainty in customer demand on inventory planning for online grocery retailers. Given the perishable nature of grocery products and intense market competition, retailers must ensure pr

Hoon Lee, Hong Ki Kim, Seung Hyun Oh, Sang Hyun Lee

Future wireless network technology provides automobiles with the connectivity feature to consolidate the concept of vehicular networks that collaborate on conducting cooperative driving tasks. The full potential of connected vehicles, which promises road safety and quality driving experience, can be leveraged if machine learning models guarantee the robustne

Wenyi Mo, Tianyu Zhang, Yalong Bai, Bing Su

Text-to-image generative models, specifically those based on diffusion models like Imagen and Stable Diffusion, have made substantial advancements. Recently, there has been a surge of interest in the delicate refinement of text prompts. Users assign weights or alter the injection time steps of certain words in the text prompts to improve the quality of gener

Rafael Vieira, Edgard P. M. Amorim

Continuous-time quantum walks (CTQWs) provide a versatile framework for exploring quantum transport on graphs. In this work, we investigate how the introduction of edge-weight modulation at a single vertex can suppress its occupation probability. We show that when the edges connected to the root vertex are enhanced by a factor $J$, the probability of detecti

Roberta Iuliana Luca, Alexandra Baicoianu, Ioana Cristina Plajer

Multispectral and hyperspectral images are increasingly popular in different research fields, such as remote sensing, astronomical imaging, or precision agriculture. However, the amount of free data available to perform machine learning tasks is relatively small. Moreover, artificial intelligence models developed in the area of spectral imaging require input

Jette Petzold, Reinhard von Hanxleden

Model checking is a proven approach for checking whether the behavior model of a safety-critical system fulfills safety properties that are stated as LTL formulas.We propose rules for generating such LTL formulas automatically based on the result of the risk analysis technique System-Theoretic Process Analysis (STPA). Additionally, we propose a synthesis of

Dan Goreac, Jonas Kirchhoff, Bernhard Maschke

The definition of conservative-irreversible functions is extended to smooth manifolds. The local representation of these functions is studied and reveals that not each conservative-irreversible function is given by the weighted product of almost Poisson brackets. The biquadratic functions given by conservative-irreversible functions are studied and reveal a

JiSun Huh, Sangwook Kim, Seunghyun Seo, Heesung Shin

The number of inversion sequences avoiding two patterns $101$ and $102$ is known to be the same as the number of permutations avoiding three patterns $2341$, $2431$, and $3241$. This sequence also counts the number of Schr\"{o}der paths without triple descents, restricted bicolored Dyck paths, $(101,021)$-avoiding inversion sequences, and weighted ordered tr

Domingos Barbosa, Bruno Coelho, Miguel Bergano, Constança Alves

The Pampilhosa da Serra Space Observatory (PASO) is located in the center of the continental Portuguese territory, in the heart of a certified Dark Sky destination by the Starlight Foundation (Aldeias do Xisto) and has been an instrumental asset to advance science, education and astrotourism certifications. PASO hosts astronomy and Space Situational Awarenes

I. Bubanja, H. Jung, A. Lelek, N. Raicevic

The internal motion of partons inside hadrons has been studied through its impact on very low transverse momentum spectra of Drell-Yan (DY) pairs created in hadron-hadron collisions. We study DY production at next-to-leading order using the Parton Branching (PB) method which describes the evolution of transverse momentum dependent parton distributions. The m

İlker Işık, Ebru Aydin Gol

The re-energization of electrical distribution systems in a post-disaster scenario is of grave importance as most modern infrastructure systems rely heavily on the presence of electricity. This paper introduces a method to coordinate the field teams for the optimal energization of an electrical distribution system after an earthquake-induced blackout. The pr

Patricia Lamirande, Eamonn A. Gaffney, Michael Gertz, Philip K. Maini

Purpose: Standard of care for various retinal diseases involves recurrent intravitreal injections. This motivates mathematical modelling efforts to identify influential factors for drug residence time, aiming to minimise administration frequency. We sought to describe the vitreal diffusion of therapeutics in nonclinical species used during drug development a

Kilian Bönisch, Claude Duhr, Sara Maggio

We study a class of meromorphic modular forms characterised by Fourier coefficients that satisfy certain divisibility properties. We present new candidates for these so-called magnetic modular forms, and we conjecture properties that these functions should obey. In particular, we conjecture that magnetic modular forms are closed under the standard operators

Mikito Kohno, Yoshiaki Sofue

We performed correlation analyses between the $^{12}$CO and $^{13}$CO $J=$1-0 line intensities in order to derive the variability of the CO-to-H$_2$ conversion factor ($X_{\rm CO, iso}$) in the central molecular zone (CMZ) of our Galaxy. New high-resolution $X_{\rm CO, iso}$ maps at a resolution of $\sim 30$" and the longitude-velocity diagram (LVD) at resol

David Hansen, Christian Johansson

We study localized versions of the spectral action of Fargues--Scholze, using methods from higher algebra. As our main motivation and application, we deduce a formula for the cohomology of moduli spaces of local shtukas under certain genericity assumptions, and discuss its relation with the Kottwitz conjecture.

Doosung Park

For a regular immersion of schemes $Z\to X$ and a cohomology theory of fs log schemes, we formulate the logarithmic Gysin sequence using the "logarithmic compactification" $(\mathrm{Bl}_Z X,E)$ instead of the open complement $X-Z$, where $E$ is the exceptional divisor. We show that all $\mathbb{A}^1$-invariant cohomology theories produced from motivic spectr

Sheng Chai, Gus Chadney

Access to smart meter data is essential to rapid and successful transitions to electrified grids, underpinned by flexibility delivered by low carbon technologies, such as electric vehicles (EV) and heat pumps, and powered by renewable energy. Yet little of this data is available for research and modelling purposes due consumer privacy protections. Whilst man

Jan Krause, Nino Walenta, Jonas Hilt, Ronald Freund

We introduce iQSync, a clock offset recovery method designed for implementation on low-level hardware, such as FPGAs or microcontrollers, for quantum key distribution (QKD). iQSync requires minimal memory, only a simple instruction set (e.g. no floating-point operations), and can be evaluated with sublinear time complexity, typically involving no more than a

Arthur Witt

The emerging technology of quantum computing has the potential to change the way how problems will be solved in the future. This work presents a centralized network control algorithm executable on already existing quantum computer which are based on the principle of quantum annealing like the D-Wave Advantage. We introduce a resource reoccupation algorithm f

Clemens C. Christoph, Amirhossein Kazemipour, Michel R. Vogt, Yu Zhang

The human shoulder, with its glenohumeral joint, tendons, ligaments, and muscles, allows for the execution of complex tasks with precision and efficiency. However, current robotic shoulder designs lack the compliance and compactness inherent in their biological counterparts. A major limitation of these designs is their reliance on external sensors like rotar

Brenda B. Malabarba, K. P. Khemchandani, A. Martinez Torres, Seung-il Nam

In view of the renewing experimental interest for searching strangeness $+1$ baryons at J-PARC, we study the existence of light baryon resonances with strangeness +1 generated in the $K$-$(N^*/\Delta^*)$ system, where $N^*$ represents either $N^*(1535)$/$N^*(1650)$/$N^*(1700)$, and $\Delta^*$ corresponds to $\Delta(1620)$. The description of the properties o

Alessandro Annarelli, Tiziana Catarci, Laura Palagi

Pursuing sustainable development has become a global imperative, underscored adopting of the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDG). At the heart of this agenda lies the recognition of social sustainability as a pivotal component, emphasizing the need for inclusive societies where every individual can thrive. D

Marco Danilo Claudio Torri, Lino Miramonti

In this paper, we aim to explore the interplay between neutrinos and quantum gravity, illustrating some proposals about the use of these particles as probes for the supposed quantized structure of spacetime. The residual signatures of a more fundamental theory of quantum gravity can manifest themselves modifying the free particle dispersion relations and the

Hao-Cheng Weng, John G. Rarity, Krishna C. Balram, Joe A. Smith

To exploit the sub-nanometre dimensions of qubits for large-scale quantum information processing, corresponding control architectures require both energy and space efficiency, with the on-chip footprint of unit-cell electronics ideally micron-scale. However, the spin coherence of qubits in close packing is severely deteriorated by microwave crosstalk from ne

Soham Mukherjee, Manfred Claassen, Paul-Christian Bürkner

We develop a framework for derivative Gaussian process latent variable models (DGP-LVMs) that can handle multi-dimensional output data using modified derivative covariance functions. The modifications account for complexities in the underlying data generating process such as scaled derivatives, varying information across multiple output dimensions as well as

Laura Weigl, Anton Schiela

We consider Newton's method for finding zeros of mappings from a manifold $\mathcal X$ into a vector bundle $\mathcal E$. In this setting a connection on $\mathcal E$ is required to render the Newton equation well defined, and a retraction on $\mathcal X$ is needed to compute a Newton update. We discuss local convergence in terms of suitable differentiabilit

Antoni Szczurek

I present possible future studies of light-by-light scattering using FoCal@ALICE and ALICE 3 detectors. Different mechanisms are discussed. The PbPb$\to$PbPb$\gamma \gamma$ cross section is calculated within equivalent photon approximation in the impact parameter space. Several differential distributions are presented and discussed. We predict cross section

Vladan Stojnić, Yannis Kalantidis, Giorgos Tolias

Vision-Language Models (VLMs) have demonstrated impressive performance on zero-shot classification, i.e. classification when provided merely with a list of class names. In this paper, we tackle the case of zero-shot classification in the presence of unlabeled data. We leverage the graph structure of the unlabeled data and introduce ZLaP, a method based on la

Michel R. Vogt, Maximilian Eberlein, Clemens C. Christoph, Felix Baumann

The need for compliant and proprioceptive actuators has grown more evident in pursuing more adaptable and versatile robotic systems. Hydraulically Amplified Self-Healing Electrostatic (HASEL) actuators offer distinctive advantages with their inherent softness and flexibility, making them promising candidates for various robotic tasks, including delicate inte

Leif Feddersen, Catherine Cleophas

Demand forecasts are the crucial basis for numerous business decisions, ranging from inventory management to strategic facility planning. While machine learning (ML) approaches offer accuracy gains, their interpretability and acceptance are notoriously lacking. Addressing this dilemma, we introduce Hierarchical Neural Additive Models for time series (HNAM).

Tuba Girgin, Emre Girgin, Yigit Yildirim, Emre Ugur

Trustworthiness is a crucial concept in the context of human-robot interaction. Cooperative robots must be transparent regarding their decision-making process, especially when operating in a human-oriented environment. This paper presents a comprehensive end-to-end framework aimed at fostering trustworthy bidirectional human-robot interaction in collaborativ

Filip Seitl, Tomáš Kovářík, Soheyla Mirshahi, Jan Kryštůfek

Advances in large language models have notably enhanced the efficiency of information extraction from unstructured and semi-structured data sources. As these technologies become integral to various applications, establishing an objective measure for the quality of information extraction becomes imperative. However, the scarcity of labeled data presents signi

Amin Dada, Marie Bauer, Amanda Butler Contreras, Osman Alperen Koraş

Large Language Models (LLMs) are expected to significantly contribute to patient care, diagnostics, and administrative processes. Emerging biomedical LLMs aim to address healthcare-specific challenges, including privacy demands and computational constraints. Assessing the models' suitability for this sensitive application area is of the utmost importance. Ho

Akhil Padmanabha, Jessie Yuan, Janavi Gupta, Zulekha Karachiwalla

Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who are unable to complete activities of daily living. Speech interfaces, especially ones that utilize Large Language Models (LLMs), can enable individuals to effectively and naturally

Boris Aronov, Tsuri Farhana, Matthew J. Katz, Indu Ramesh

It is unlikely that the discrete Fr\'echet distance between two curves of length $n$ can be computed in strictly subquadratic time. We thus consider the setting where one of the curves, $P$, is known in advance. In particular, we wish to construct data structures (distance oracles) of near-linear size that support efficient distance queries with respect to $

Paul Irofti, Iulian-Andrei Hîji, Andrei Pătraşcu, Nicolae Cleju

We study in this paper the improvement of one-class support vector machines (OC-SVM) through sparse representation techniques for unsupervised anomaly detection. As Dictionary Learning (DL) became recently a common analysis technique that reveals hidden sparse patterns of data, our approach uses this insight to endow unsupervised detection with more control

M. A. Maia, I. B. C. M. Rocha, D. Kovačević, F. P. van der Meer

In this work, a hybrid physics-based data-driven surrogate model for the microscale analysis of heterogeneous material is investigated. The proposed model benefits from the physics-based knowledge contained in the constitutive models used in the full-order micromodel by embedding them in a neural network. Following previous developments, this paper extends t

Linus Behn, Lars Diening, Simon Nowak, Toni Scharle

We extend the De Giorgi iteration technique to the vectorial setting. For this we replace the usual scalar truncation operator by a vectorial shortening operator. As an application, we prove local boundedness for local and nonlocal nonlinear systems. Furthermore, we show convex hull properties, which are a generalization of the maximum principle to the case

Ye Wei, Bo Peng, Ruiwen Xie, Yangtao Chen

A tremendous range of design tasks in materials, physics, and biology can be formulated as finding the optimum of an objective function depending on many parameters without knowing its closed-form expression or the derivative. Traditional derivative-free optimization techniques often rely on strong assumptions about objective functions, thereby failing at op

Ó. Jiménez-Arranz, S. Roca-Fàbrega, M. Romero-Gómez, X. Luri

We present KRATOS, a comprehensive suite of 28 open access pure N-body simulations of isolated and interacting LMC-like galaxies, to study the formation of substructures in their disc after the interaction with an SMC-mass galaxy. The primary objective of this paper is to provide theoretical models that help interpreting the formation of general structures o

Lu Zhang

In this paper, our focus lies on a fundamental geometric invariant known as Riesz capacity, which holds an essential position in potential theory. We establish the Hadamard variational formula for Riesz capacity of convex bodies. As a meaningful application, we derive a Serrin-type symmetry result for an overdetermined problem.

Sarah Sterz, Kevin Baum, Sebastian Biewer, Holger Hermanns

Human oversight is currently discussed as a potential safeguard to counter some of the negative aspects of high-risk AI applications. This prompts a critical examination of the role and conditions necessary for what is prominently termed effective or meaningful human oversight of these systems. This paper investigates effective human oversight by synthesizin

Daniel Chen

Complete non-ambiguous trees have been studied in various contexts. Recently, a conjecture was made about their determinants, and subsequently proved by Aval. An alternative proof is given here.

Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin

We introduce Score identity Distillation (SiD), an innovative data-free method that distills the generative capabilities of pretrained diffusion models into a single-step generator. SiD not only facilitates an exponentially fast reduction in Fr\'echet inception distance (FID) during distillation but also approaches or even exceeds the FID performance of the

Kouki Sato

A slice-torus invariant is an $\mathbb{R}$-valued homomorphism on the knot concordance group whose value gives a lower bound for the 4-genus such that the equality holds for any positive torus knot. Such invariants have been discovered in many of knot homology theories, while it is known that any slice-torus invariant does not factor through the topological

Zhihao Guan, Jia-Qi Yang, Yang Yang, Hengshu Zhu

Job recommendation aims to provide potential talents with suitable job descriptions (JDs) consistent with their career trajectory, which plays an essential role in proactive talent recruitment. In real-world management scenarios, the available JD-user records always consist of JDs, user profiles, and click data, in which the user profiles are typically summa

Nikos Sioulas, Themistocles Zikopoulos, Chen Shi, Marco Velli

We analyze in-situ observations of imbalanced solar wind turbulence to evaluate MHD turbulence models grounded in "Critical Balance" (CB) and "Scale-Dependent Dynamic Alignment" (SDDA). At energy injection scales, both outgoing and ingoing modes exhibit a weak cascade; a simultaneous tightening of SDDA is noted. Outgoing modes persist in a weak cascade acros

Maxime Breden, Hugo Chu

We develop computer-assisted tools to study semilinear equations of the form \begin{equation*} -\Delta u -\frac{x}{2}\cdot \nabla{u}= f(x,u,\nabla u) ,\quad x\in\mathbb{R}^d. \end{equation*} Such equations appear naturally in several contexts, and in particular when looking for self-similar solutions of parabolic PDEs. We develop a general methodology, allow

Alba de las Heras, Carlos Hernández-García, Javier Serrano, Aleksandar Prodanov

High-order harmonic generation driven by intense extreme ultraviolet (EUV) fields merges quantum optics and attosecond science, giving rise to an appealing route for the generation of coherent EUV and soft X-ray light for high-resolution imaging and spectroscopies. We theoretically investigate ultrafast resonant dynamics during the interaction of He atoms wi

Minsheng Huang, Chengbao Yao, Pan Wang, Lidong Cheng

We present a novel one-fluid cavitation model of a specific Mie-Gr\"uneisen equation of state(EOS), named polynomial EOS, based on an artificial neural network. Not only the physics-informed equation but also the experimental data are embedded into the proposed model by an optimization problem. The physics-informed data-driven model provides the concerned pr

Md Aquib Molla, Sanchari Goswami

We study the signal percolation through heart-like biological system. Starting from an initial distribution of waiting and inactive cells with probabilities $p$ and $(1-p)$ respectively, the signal propagation is observed in terms of active cells. As the signal enters the system from one end, the number of arrival of active sites at the other end is studied

Narendranath Mitra

Srinivasa Ramanujan posed a problem on infinite nested radical of the square root in the Journal of Indian Mathematical Society in 1911. He had generated the problem years before in the form of an example illustrating a more general theorem. Of course, how we would figure the solution out without Ramanujan theorem was scarcely obvious. Generation of infinite

Xiangyang Zhu, Renrui Zhang, Bowei He, Ziyu Guo

To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot segmentation methods first pre-train models on 'seen' classes, and then evaluate their generalization performance on 'unseen' classes. However, the prior pre-training stage not only introduces excessive time overhead but also incur

Joachim Schaeffer, Giacomo Galuppini, Jinwook Rhyu, Patrick A. Asinger

Batteries are dynamic systems with complicated nonlinear aging, highly dependent on cell design, chemistry, manufacturing, and operational conditions. Prediction of battery cycle life and estimation of aging states is important to accelerate battery R&D, testing, and to further the understanding of how batteries degrade. Beyond testing, battery management sy

Mahesh Lorik Yadav, Harish Guruprasad Ramaswamy, Chandrashekar Lakshminarayanan

There currently exist two extreme viewpoints for neural network feature learning -- (i) Neural networks simply implement a kernel method (a la NTK) and hence no features are learned (ii) Neural networks can represent (and hence learn) intricate hierarchical features suitable for the data. We argue in this paper neither interpretation is likely to be correct

Nikoleta Ilić, Katja Poppenhaeger, Anna Barbara Queiroz, Cristina Chiappini

The dynamical evolution of tight star-planet systems is influenced by tidal interactions between the star and the planet, as was shown recently. The rate at which spins and orbits in such a system evolve depends on the stellar and planetary tidal dissipation efficiency. Here, we present a method to constrain the modified tidal quality factor $Q'_*$ of a plan

Vitalii Vertogradov, Ali Övgün

In this paper, we introduce a new approach to study the behavior of the photon sphere and shadow radius. Our method uses extended gravitational decoupling and reveals two important analytic results. First, the additional matter field alters the photon sphere radius: it increases if $g'(r_{ph}^{(0)})>0$ and decreases if $g'(r_{ph}^{(0)})<0$ (where $g'$ repres

Andreas Eggenberger, Alexander Eichler

Stochastic physics is a central pillar of modern research in many fields, but is rarely presented to undergrad students in a hands-on experiment. Here, we demonstrate how a human-scale, simple, and affordable experimental setup can be used to fill this gap, and to illustrate many advanced concepts in a step-by-step approach. Based on a metal wire (such as a

Negar Arabzadeh, Charles L. A. Clarke

Information retrieval systems increasingly incorporate generative components. For example, in a retrieval augmented generation (RAG) system, a retrieval component might provide a source of ground truth, while a generative component summarizes and augments its responses. In other systems, a large language model (LLM) might directly generate responses without

Camelia Jana, Santabrata Das

We develop and discuss a model formalism to study the properties of mass outflows that are emerged out from a relativistic, magnetized, viscous, advective accretion flow around a rotating black hole. In doing so, we consider the toroidal component as the dominant magnetic fields and synchrotron process is the dominant cooling mechanism inside the accretion d

Hele-Andra Kuulmets, Taido Purason, Agnes Luhtaru, Mark Fishel

This paper explores cost-efficient methods to adapt pretrained Large Language Models (LLMs) to new lower-resource languages, with a specific focus on Estonian. Leveraging the Llama 2 model, we investigate the impact of combining cross-lingual instruction-tuning with additional monolingual pretraining. Our results demonstrate that even a relatively small amou

Christos Siargkas, Vasileios Papapanagiotou, Anastasios Delopoulos

Transportation mode recognition (TMR) is a critical component of human activity recognition (HAR) that focuses on understanding and identifying how people move within transportation systems. It is commonly based on leveraging inertial, location, or both types of signals, captured by modern smartphone devices. Each type has benefits (such as increased effecti

Jorge A. Vila

The interconnected processes of protein folding, mutations, epistasis, and evolution have all been the subject of extensive analysis throughout the years due to their significance for structural and evolutionary biology. The origin (molecular basis) of epistasis (the non-additive interactions between mutations) is still, nonetheless, unknown. The existence o

Paola Natalia Cañas, Mikel García, Nerea Aranjuelo, Marcos Nieto

This paper describes the methodology for building a dynamic risk assessment for ADAS (Advanced Driving Assistance Systems) algorithms in parking scenarios, fusing exterior and interior perception for a better understanding of the scene and a more comprehensive risk estimation. This includes the definition of a dynamic risk methodology that depends on the sit

José Cáceres, Ignacio M. Pelayo

A vertex $v$ of a connected graph $G$ is said to be a boundary vertex of $G$ if for some other vertex $u$ of $G$, no neighbor of $v$ is further away from $u$ than $v$. The boundary $\partial(G)$ of $G$ is the set of all of its boundary vertices. The boundary distance matrix $\hat{D}_G$ of a graph $G=([n],E)$ is the square matrix of order $\kappa$, being $\ka

Paola Cattabriga

Godel numbering is an arithmetization of sintax which defines provability by coding a primitive recursive predicate, Pf(x,v). A multiplicity of researches and results all around this well-known recursive predicate are today widespread in many areas of logic and AI. Not equally investigated is the refutability predicate defined by Godel numbering within the s

Jiayin Zhu, Linlin Yang, Angela Yao

We present InstructHumans, a novel framework for instruction-driven {animatable} 3D human texture editing. Existing text-based 3D editing methods often directly apply Score Distillation Sampling (SDS). SDS, designed for generation tasks, cannot account for the defining requirement of editing -- maintaining consistency with the source avatar. This work shows

Sita A. Vriend, Sandeep Vidyapu, Amer Rama, Kun-Ting Chen

We conducted an eye-tracking user study with 13 participants to investigate the influence of stimulus-question ordering and question modality on participants using visual question-answering (VQA) tasks. We examined cognitive load, task performance, and gaze allocations across five distinct experimental designs, aiming to identify setups that minimize the cog

Annerose Eichel, Sabine Schulte im Walde

We present a novel dataset for physical and abstract plausibility of events in English. Based on naturally occurring sentences extracted from Wikipedia, we infiltrate degrees of abstractness, and automatically generate perturbed pseudo-implausible events. We annotate a filtered and balanced subset for plausibility using crowd-sourcing, and perform extensive

Robert L. Benedetto, William DeGroot, Xinyu Ni, Jesse Seid

Let $K$ be a field, and let $f\in K(z)$ be a rational function of degree $d\geq 2$. The Galois group of the field extension generated by the preimages of $x_0\in K$ under all iterates of $f$ naturally embeds in the automorphism group of an infinite $d$-ary rooted tree. In some cases the Galois group can be the full automorphism group of the tree, but in othe

Mingyuan Zhang, Yosuke Mizuno, Christian M. Fromm, Ziri Younsi

The recent 230 GHz observations from the Event Horizon Telescope collaboration can image the innermost structure of the M87 galaxy showing the shadow of the black hole, a photon ring, and a ring-like structure that agrees with thermal synchrotron emission from the accretion disc. However, at lower frequencies, M87 is characterized by a large-scale jet with c

Giovanni Del Monte, Emanuela Zaccarelli

We perform extensive Molecular Dynamics simulations of an ensemble of realistic microgel particles in swollen conditions in a wide range of packing fractions $\zeta$. We compare neutral and charged microgels, where we consider charges distribution adherent to experimental conditions. Through a detailed analysis of single-particle behavior, we are able to ide

Annerose Eichel, Tana Deeg, André Blessing, Milena Belosevic

We present a comprehensive computational study of the under-investigated phenomenon of personal name compounds (PNCs) in German such as Willkommens-Merkel ('Welcome-Merkel'). Prevalent in news, social media, and political discourse, PNCs are hypothesized to exhibit an evaluative function that is reflected in a more positive or negative perception as compared

L. A. Head, D. Grodent, B. Bonfond, A. Moirano

Auroral emissions are a reflection of magnetospheric processes, and, at Jupiter, it is not entirely certain how the morphology of the UV main emission (ME) varies with magnetospheric compression or the strength of the central current sheet. This work leverages the observations from Juno-UVS to link ME variability with magnetospheric states. Novel arc-detecti

Oliver Herbort, Peter Woitke, Christiane Helling, Aubrey L. Zerkle

Life as we know it requires the presence of liquid water and the availability of nutrients, which are mainly based on the elements C, H, N, O, P, and S (CHNOPS) and trace metal micronutrients. We aim to understand the presence of these nutrients within atmospheres that show the presence of water cloud condensates, potentially allowing the existence of aerial

Emma D'Aniello, Martina Maiuriello

In the present paper we investigate different variants of supercyclicity, precisely $\mathbb R^+$-, $\mathbb R$- and $\mathbb C$-supercyclicity in the context of composition operators. We characterize $\mathbb R$-supercyclic composition operators on $L^p$, $1 \leq p < \infty$. Then, we turn our attention to dissipative composition operators, and we show that

Victor Manuel Aricheta, Russelle Guadalupe

We explore the modularity of the continued fractions $I(\tau), J(\tau), T_1(\tau), T_2(\tau)$ and $U(\tau)=I(\tau)/J(\tau)$ of order $10$, where $I(\tau)$ and $J(\tau)$ are introduced by Rajkhowa and Saikia, which are special cases of certain identities of Ramanujan. In particular, we show that these fractions can be expressed in terms of an $\eta$-quotient

Oliver Gross, Ulrich Pinkall, Moritz Wahl

We study stationary points of the bending energy of curves $\gamma\colon[a,b]\to\mathbb{R}^n$ subject to constraints on the arc-length and the curve's holonomy while simultaneously allowing for a variable bending stiffness along the arc-length of the curve. Physically, this can be understood as a model for an elastic wire with isotropic cross-section of vary

Chenyang Wu, Yifan Duan, Xinran Zhang, Yu Sheng

Localization and mapping are critical tasks for various applications such as autonomous vehicles and robotics. The challenges posed by outdoor environments present particular complexities due to their unbounded characteristics. In this work, we present MM-Gaussian, a LiDAR-camera multi-modal fusion system for localization and mapping in unbounded scenes. Our

Chayanin Tangwiriyasakul, Pedro Borges, Stefano Moriconi, Paul Wright

Stroke is a leading cause of disability and death. Effective treatment decisions require early and informative vascular imaging. 4D perfusion imaging is ideal but rarely available within the first hour after stroke, whereas plain CT and CTA usually are. Hence, we propose a framework to extract a predicted perfusion map (PPM) derived from CT and CTA images. I

Tobias Boege, Kaie Kubjas, Pratik Misra, Liam Solus

We study submodels of Gaussian DAG models defined by partial homogeneity constraints imposed on the model error variances and structural coefficients. We represent these models with colored DAGs and investigate their properties for use in statistical and causal inference. Local and global Markov properties are provided and shown to characterize the colored D

Sourabh Manna, Rohit Medwal, John Rex Mohan, Yasuhiro Fukuma

Mutually coupled spin Hall nano-oscillators (SHNO) can exhibit binarized phase state, offering pathways to realize Ising machines and efficient neuromorphic hardware. Conventionally, phase binarization is achieved in coupled SHNOs via injecting an external microwave at twice of the oscillator frequency in presence of a biasing magnetic field. However, this t

Yuri Bizzoni, Pascale Feldkamp, Ida Marie Lassen, Mia Jacobsen

In this study, we employ a classification approach to show that different categories of literary "quality" display unique linguistic profiles, leveraging a corpus that encompasses titles from the Norton Anthology, Penguin Classics series, and the Open Syllabus project, contrasted against contemporary bestsellers, Nobel prize winners and recipients of prestig

Mirko Serino, Wojciech Broniowski, Enrique Ruiz Arriola

The two point correlation function of the stress-energy-momentum tensor describes the propagation of a space-time "micro-earthquake" in the vacuum. In the framework of the path integral formulation of field theory in curved space-time, we derive the Ward-Takashi identity for two-point Green's function of the stress-energy-momentum tensor for a general case o

N. N. Shchechilin, N. Chamel, J. M. Pearson, A. I. Chugunov

We previously studied the inner crust and the pasta mantle of a neutron star within the 4th-order extended Thomas-Fermi (ETF) approach with consistent proton shell corrections added perturbatively via the Strutinsky integral (SI) theorem together with the contribution due to pairing. To speed up the computations and avoid numerical problems, we adopted param

Sarit Maitra, Sukanya Kundu, Aishwarya Shankar

The majority of modern consumer-level energy is generated by real-time smart metering systems. These frequently contain anomalies, which prevent reliable estimates of the series' evolution. This work introduces a hybrid modeling approach combining statistics and a Convolutional Autoencoder with a dynamic threshold. The threshold is determined based on Mahala

Kenta Kumagai

We consider the Gelfand problem with general supercritical nonlinearities in the two-dimensional unit ball. In this paper, we prove the non-existence of an unstable solution for any positive small parameter $\lambda$. The result implies that once the bifurcation curve emanates from the starting point, then the curve never approaches $\lambda=0$. As a result,

Benjamin Doerr, Martin S. Krejca, Nguyen Vu

The target set selection problem (TSS) asks for a set of vertices such that an influence spreading process started in these vertices reaches the whole graph. The current state of the art for this NP-hard problem are three recently proposed randomized search heuristics, namely a biased random-key genetic algorithm (BRKGA) obtained from extensive parameter tun

Michael Aich, Philipp Hess, Baoxiang Pan, Sebastian Bathiany

Climate change exacerbates extreme weather events like heavy rainfall and flooding. As these events cause severe socioeconomic damage, accurate high-resolution simulation of precipitation is imperative. However, existing Earth System Models (ESMs) struggle to resolve small-scale dynamics and suffer from biases. Traditional statistical bias correction and dow

Ilham Asmouh, Alexander Ostermann

Nonlinear diffusion-reaction systems model a multitude of physical phenomena. A common situation is biological development modeling where such systems have been widely used to study spatiotemporal phenomena in cell biology. Systems of coupled diffusion-reaction equations are usually subject to some complicated features directly related to their multiphysics

Kan Chen, Bo Wang

Based on a contact lagrangian that incorporates the SU(3) flavor and SU(2) spin symmetries, we discuss the symmetry properties of the interactions among the heavy flavor meson-baryon $P_{\psi}^N$, $P_{\psi s}^\Lambda$ (with quark components [$n\bar{c}$][$nnc$], [$s\bar{c}$][$nnc$], or [$n\bar{c}$][$nsc$]) systems and di-baryon $H_{\Omega_{ccc}}^N$, $H^{\Lamb

Martin S. Krejca, Carsten Witt

We propose a new, flexible approach for dynamically maintaining successful mutation rates in evolutionary algorithms using $k$-bit flip mutations. The algorithm adds successful mutation rates to an archive of promising rates that are favored in subsequent steps. Rates expire when their number of unsuccessful trials has exceeded a threshold, while rates curre

Florian Schreier-Aigner

The (dual) Cauchy identity has an easy algebraic proof utilising a commutation relation between the up and (dual) down operators. By using Fomin's growth diagrams, a bijective proof of the commutation relation can be "bijectivised" to obtain RSK like correspondences. In this paper we give a concise overview of this machinery and extend it to Littlewood type

Sayak Datta, Richard Brito, Scott A. Hughes, Talya Klinger

Tidal heating in a binary black hole system is driven by the absorption of energy and angular momentum by the black hole's horizon. Previous works have shown that this phenomenon becomes particularly significant during the late stages of an extreme mass ratio inspiral (EMRI) into a rapidly spinning massive black hole, a key focus for future low-frequency gra

Zhiguo Ding, Robert Schober, Pingzhi Fan, H. Vincent Poor

Multiple access techniques are fundamental to the design of wireless communication systems, since many crucial components of such systems depend on the choice of the multiple access technique. Because of the importance of multiple access, there has been an ongoing quest during the past decade to develop next generation multiple access (NGMA). Among those pot