April 2024 arXiv papers — page 182

Maxim Nazarov

This paper was written in 1994 and has attracted a large number of citations since then. The main result was a definition of what is called the affine Brauer algebra in the present version. It is now posted to affirm this terminology.

Max Rose, Hannes Gernandt, Juan E. Machado, Johannes Schiffer

The transformation of fossil fuel-based district heating grids (DHGs) to CO$_2$-neutral DHGs requires the development of novel operating strategies. Model predictive control (MPC) is a promising approach, as knowledge about future heat demand and heat supply can be incorporated into the control, operating constraints can be ensured and the stability of the c

Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Muhammad Zeshan Afzal

In this paper, we address the limitations of the DETR-based semi-supervised object detection (SSOD) framework, particularly focusing on the challenges posed by the quality of object queries. In DETR-based SSOD, the one-to-one assignment strategy provides inaccurate pseudo-labels, while the one-to-many assignments strategy leads to overlapping predictions. Th

Giovanni Abramo, Ciriaco Andrea D'Angelo

Similar to how innovations often find success in fields other than their original domains, in this study we explore whether the same holds true for scientific discoveries. We investigate the flow of knowledge across scientific disciplines, focusing on connections between citing and cited publications. Specifically, we analyze the connections among cited publ

Lishuang Wang, Mengfei Zhao, Enyu Liu, Kebin Sun

The NeuroEvolution of Augmenting Topologies (NEAT) algorithm has received considerable recognition in the field of neuroevolution. Its effectiveness is derived from initiating with simple networks and incrementally evolving both their topologies and weights. Although its capability across various challenges is evident, the algorithm's computational efficienc

Zdravko Marinov, Moon Kim, Jens Kleesiek, Rainer Stiefelhagen

Interactive segmentation plays a crucial role in accelerating the annotation, particularly in domains requiring specialized expertise such as nuclear medicine. For example, annotating lesions in whole-body Positron Emission Tomography (PET) images can require over an hour per volume. While previous works evaluate interactive segmentation models through eithe

Jiechen Chen, Sangwoo Park, Petar Popovski, H. Vincent Poor

Neuromorphic computing leverages the sparsity of temporal data to reduce processing energy by activating a small subset of neurons and synapses at each time step. When deployed for split computing in edge-based systems, remote neuromorphic processing units (NPUs) can reduce the communication power budget by communicating asynchronously using sparse impulse r

Filippo Fabiani, Bartolomeo Stellato, Daniele Masti, Paul J. Goulart

We consider the problem of designing a machine learning-based model of an unknown dynamical system from a finite number of (state-input)-successor state data points, such that the model obtained is also suitable for optimal control design. We adopt a neural network (NN) architecture that, once suitably trained, yields a hybrid system with continuous piecewis

Samir F Matar

Super-hard C5 with lon topology (lon: Lonsdaleite hexagonal diamond) and characterized by the presence of sp3 and sp2 -like carbon sites is devised from crystal chemistry and used as template matrix structure for identifying original carbonitrides C4N and C2N2 with lon topology except for the equiatomic belonging to a new topology (3,4L147). The steric effec

Saptarshi Dasgupta, Akshat Gupta, Shreshth Tuli, Rohan Paul

Manipulating unseen objects is challenging without a 3D representation, as objects generally have occluded surfaces. This requires physical interaction with objects to build their internal representations. This paper presents an approach that enables a robot to rapidly learn the complete 3D model of a given object for manipulation in unfamiliar orientations.

Yiqiang Zhu, Lida Zhu, Yiheng Lim, Shuichi Makita

We demonstrate a method that reduces the noise caused by multi-scattering (MS) photons in an \invivo optical coherence tomography image. This method combines a specially designed image acquisition (i.e., optical coherence tomography scan) scheme and subsequent complex signal processing. For the acquisition, multiple cross-sectional images (frames) are sequen

Yaniv Wolf, Amit Bracha, Ron Kimmel

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian properties remains a challenge, as those are optimized based on a photometric loss. While some concurrent models have t

Jakub Rydzewski

The dynamics of physical systems that require high-dimensional representation can often be captured in a few meaningful degrees of freedom called collective variables (CVs). However, identifying CVs is challenging and constitutes a fundamental problem in physical chemistry. This problem is even more pronounced when CVs information about slow kinetics related

Jihoon Cho, Changhoon Lee, Eunkyung Kim, Jieun Lee

Given the widespread use of cryptography in Enterprise IT, migration to post-quantum cryptography (PQC) is not drop-in replacement at all. Cryptographic agility, or crypto-agility, is a design feature that enables seamless updates to new cryptographic algorithms and standards without the need to modify or replace the surrounding infrastructure. This paper in

Fabrizio Cossu, Dhani Nafday, Krisztian Palotás, Mehdi Biderang

We employ ab-initio electronic structure calculations to investigate the charge-density waves and periodic lattice distortions in bilayer 2H-NbSe$_2$. We demonstrate that the vertical stacking can give rise to a variety of patterns that may lower the symmetry of the charge-density waves exhibited separately by the two composing 1H-NbSe$_2$ monolayers. The ge

Tobias Hartnick, Vera Tonić

We establish two main results for the asymptotic dimension of countable approximate groups. The first one is a Hurewicz type formula for a global morphism of countable approximate groups $f:(\Xi, \Xi^\infty) \to (\Lambda, \Lambda^\infty)$, stating that $\mathrm{asdim} \Xi \leq \mathrm{asdim} \Lambda +\mathrm{asdim} ([\mathrm{ker} f]_c)$. This is analogous to

Michael Mitsios, Georgios Vamvoukakis, Georgia Maniati, Nikolaos Ellinas

Emotion detection in textual data has received growing interest in recent years, as it is pivotal for developing empathetic human-computer interaction systems. This paper introduces a method for categorizing emotions from text, which acknowledges and differentiates between the diversified similarities and distinctions of various emotions. Initially, we estab

Yuzhen Ke, Zoran Utkovski, Mehdi Heshmati, Osvaldo Simeone

An important use case of next-generation wireless systems is device-edge co-inference, where a semantic task is partitioned between a device and an edge server. The device carries out data collection and partial processing of the data, while the remote server completes the given task based on information received from the device. It is often required that pr

Suyun Borjigin

Credential theft and remote attacks are the most serious threats to user authentication mechanisms. The crux of these problems is that we cannot control such behaviors. However, if a password does not contain user secrets, stealing it is useless. If unauthorized inputs are invalidated, remote attacks can be disabled. Thus, credential secrets and account inpu

Carlos Plou, Nerea Gallego, Alberto Sabater, Eduardo Montijano

Event cameras are a promising technology for activity recognition in dark environments due to their unique properties. However, real event camera datasets under low-lighting conditions are still scarce, which also limits the number of approaches to solve these kind of problems, hindering the potential of this technology in many applications. We present Event

Walid Hariri

Scientific articles play a crucial role in advancing knowledge and informing research directions. One key aspect of evaluating scientific articles is the analysis of citations, which provides insights into the impact and reception of the cited works. This article introduces the innovative use of large language models, particularly ChatGPT, for comprehensive

Claudio Novelli, Giuliano Formisano, Prathm Juneja, Giulia Sandri

The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to the collection of

Qixiang Fang, Daniel L. Oberski, Dong Nguyen

Many existing benchmarks of large (multimodal) language models (LLMs) focus on measuring LLMs' academic proficiency, often with also an interest in comparing model performance with human test takers'. While such benchmarks have proven key to the development of LLMs, they suffer from several limitations, including questionable measurement quality (e.g., Do th

Dmitry A. Lyakhov, Dominik L. Michels

We investigate the problem of recovering coefficients in scalar nonlinear ordinary differential equations that can be exactly linearized. This contribution builds upon prior work by Lyakhov, Gerdt, and Michels, which focused on obtaining a linearizability certificate through point transformations. Our focus is on quasi-linear equations, specifically those so

Nilesh Kumar, Miroslav Kolos, Sitangshu Bhattacharya, František Karlický

Semiconducting MXenes are an intriguing two-dimensional (2D) material class with promising electronic and optoelectronic properties. Here, we focused on recently prepared Hf-based MXenes, namely Hf$_3$C$_2$O$_2$ and Hf$_2$CO$_2$. Using the first-principles calculation and excited state corrections, we proved its dynamical stability, reconciled its semiconduc

Marco Rossanese, Placido Mursia Andres, Garcia-Saavedra, Vincenzo Sciancalepore

In this paper, we present two datasets that we make publicly available for research. The data is collected in a testbed comprised of a custom-made Reconfigurable Intelligent Surface (RIS) prototype and two regular OFDM transceivers within an anechoic chamber. First, we discuss the details of the testbed and equipment used, including insights about the design

Xing Huang, Fen-Fen Yang, Chenggui Yuan

In this paper, a general result on the long time $\W_0$-$\widetilde{\W}_1$ type propagation of chaos, propagation of chaos with regularization effect, for mean field interacting particle system driven by L\'{e}vy noise is derived, where $\W_0$ is one half of the total variation distance while $\widetilde{\W}_1$ is the $L^1$-Wasserstein distance. By using the

Eric MSP Veith, Torben Logemann, Aleksandr Berezin, Arlena Wellßow

Autonomous and learning systems based on Deep Reinforcement Learning have firmly established themselves as a foundation for approaches to creating resilient and efficient Cyber-Physical Energy Systems. However, most current approaches suffer from two distinct problems: Modern model-free algorithms such as Soft Actor Critic need a high number of samples to le

Athanasios Karapantelakis, Mukesh Thakur, Alexandros Nikou, Farnaz Moradi

The Third Generation Partnership Project (3GPP) has successfully introduced standards for global mobility. However, the volume and complexity of these standards has increased over time, thus complicating access to relevant information for vendors and service providers. Use of Generative Artificial Intelligence (AI) and in particular Large Language Models (LL

Chiara Mancuso

The latest results from the LHCb collaboration for the search for $CP$ violation in $b$-baryon decays are reported here. The first article presented is the search conducted in the $\Lambda_b^0 \rightarrow p \pi^- \pi^+ \pi^- $ decay, and the subsequent observation of $P$ violation. The following paper describes the search and the first observation of the $\L

T. Martinić-Bilać, S. Meljanac, S. Mignemi

The Yang algebra was proposed a long time ago as a generalization of the Snyder algebra to the case of curved background spacetime. It includes as subalgebras both the Snyder and the de Sitter algebras and can therefore be viewed as a model of noncommutative curved spacetime. A peculiarity with respect to standard models of noncommutative geometry is that it

Tomislav Šikić

For an affine Lie algebra $\hat{\mathfrak g}$ the coefficients of certain vertex operators which annihilate level $k$ standard $\hat{\mathfrak g}$-modules are the defining relations for level $k$ standard modules. In the paper \cite{PS3} combinatorial structure of the leading terms of mentioned relations for level $k=2$ standard $\hat{\mathfrak g}$-modules a

Matias Molina, Rita P. Ribeiro, Bruno Veloso, João Gama

Illegal landfills are a critical issue due to their environmental, economic, and public health impacts. This study leverages aerial imagery for environmental crime monitoring. While advances in artificial intelligence and computer vision hold promise, the challenge lies in training models with high-resolution literature datasets and adapting them to open-acc

Weipan Yang, Yongchao Xing, Yiming Lyu, Zhihao Liang

Microservice architecture has become a dominant architectural style in the service-oriented software industry. Poor practices in the design and development of microservices are called microservice bad smells. In microservice bad smells research, the detection of these bad smells relies on feature data from microservices. However, there is a lack of an approp

Umesh Shankar

In this short paper, we give bijective proofs of two recent equidistribution results connecting cyclic and linear statistics in the spirit of the Foata's ``transformation fondamentale''.

Carolyn Wood, Sally Shrapnel, G J Milburn

Kernel methods are of current interest in quantum machine learning due to similarities with quantum computing in how they process information in high-dimensional feature (Hilbert) spaces. Kernels are believed to offer particular advantages when they cannot be computed classically, so a kernel matrix with indisputably nonclassical elements is desirable provid

Rohit Pandey, Hetvi Waghela, Sneha Rakshit, Aparna Rangari

This work delved into the realm of automatic text generation, exploring a variety of techniques ranging from traditional deterministic approaches to more modern stochastic methods. Through analysis of greedy search, beam search, top-k sampling, top-p sampling, contrastive searching, and locally typical searching, this work has provided valuable insights into

Jiachen Ma, Yijiang Li, Zhiqing Xiao, Anda Cao

Text-to-image (T2I) models can be maliciously used to generate harmful content such as sexually explicit, unfaithful, and misleading or Not-Safe-for-Work (NSFW) images. Previous attacks largely depend on the availability of the diffusion model or involve a lengthy optimization process. In this work, we investigate a more practical and universal attack that d

Maria Barrett, Max Müller-Eberstein, Elisa Bassignana, Amalie Brogaard Pauli

Textual domain is a crucial property within the Natural Language Processing (NLP) community due to its effects on downstream model performance. The concept itself is, however, loosely defined and, in practice, refers to any non-typological property, such as genre, topic, medium or style of a document. We investigate the core notion of domains via human profi

Caihao Weng, Yuanbin Chen, Lipeng Zhu, Ying Wang

In this paper, we investigate a multi-receiver communication system enabled by movable antennas (MAs). Specifically, the transmit beamforming and the double-side antenna movement at the transceiver are jointly designed to maximize the sum-rate of all receivers under imperfect channel state information (CSI). Since the formulated problem is non-convex with hi

Umesh Shankar

Generalising the work of Dey, we define the notion of ultra-synchronicity of sequences of real numbers. Let $B_{n,k},C_{n,k},P_{n,k},Q_{n,k}$ be the number of even permutations with $k$ descents, odd permutations with $k$ descents, even permutations with $k$ excedances and odd permutations with $k$ excedances respectively. We show that the four sequences are

Abdul Haris, Muhammad Munawir Syarif, Hamed Narolla, Rachmat Hidayat

This study aims to develop a framework for multicriteria analysis to evaluate alternatives for sustainable corn agricultural area planning, considering the integration of ecological, economic, and social aspects as pillars of sustainability. The research method uses qualitative and quantitative approaches to integrate ecological, economic, and social aspects

Daniel Adolfsson, Maximilian Hilger

This article describes the method CFEAR Radar odometry, submitted to a competition at the Radar in Robotics workshop, ICRA 20241. CFEAR is an efficient and accurate method for spinning 2D radar odometry that generalizes well across environments. This article presents an overview of the odometry pipeline with new experiments on the public Boreas dataset. We s

Xu Li, Ruiqi Sun, Jiameng Lv, Peng Jia

Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong lensing systems on an unprecedented scale, which requires efficient tools to extract them from billions of astronomical objects. The existing mainstream lens-finding tools are based on ma

Lachezar S. Georgiev, Ludmil Hadjiivanov, Grigori Matein

We investigate a promising conformal field theory realization scheme for topological quantum computation based on the Fibonacci anyons, which are believed to be realized as quasiparticle excitations in the $\mathbb{Z}_3$ parafermion fractional quantum Hall state in the second Landau level with filling factor $\nu=12/5$. These anyons are non-Abelian and are k

Ludmil Hadjiivanov, Lachezar S. Georgiev

Fibonacci anyons provide the simplest possible model of non-Abelian fusion rules: [1] x [1] = [0] + [1]. We propose a conformal field theory construction of topological quantum registers based on Fibonacci anyons realized as quasiparticle excitations in the Z_3 parafermion fractional quantum Hall state. To this end, the results of Ardonne and Schoutens for t

Korbinian Urban, Matteo Biassoni, Marco Carminati, Frank Edzards

The TRISTAN detector is a new detector for electron spectroscopy at the Karlsruhe Tritium Neutrino (KATRIN) experiment. The semiconductor detector utilizes the silicon drift detector technology and will enable the precise measurement of the entire tritium beta decay electron spectrum. Thus, a significant fraction of the parameter space of potential neutrino

Qiliang Fang, Keiichi Maeda, Haonan Ye, Takashi Moriya

We present a systematic study of Type II supernovae (SNe II) originating from progenitors with effective temperatures ($T_{\rm eff}$) and luminosities closely resembling red supergiants (RSGs) observed in pre-SN images and in the Galaxy. Using $\texttt{MESA}$, we compute a large grid of massive stars with $T_{\rm eff}$ ranging from 3200 K to 3800 K at their

Galadrielle Humblot-Renaux, Sergio Escalera, Thomas B. Moeslund

The ability to detect unfamiliar or unexpected images is essential for safe deployment of computer vision systems. In the context of classification, the task of detecting images outside of a model's training domain is known as out-of-distribution (OOD) detection. While there has been a growing research interest in developing post-hoc OOD detection methods, t

W. J. G. de Blok, J. Healy, F. M. Maccagni, D. J. Pisano

The MHONGOOSE (MeerKAT HI Observations of Nearby Galactic Objects: Observing Southern Emitters) survey maps the distribution and kinematics of the neutral atomic hydrogen (HI) gas in and around 30 nearby star-forming spiral and dwarf galaxies to extremely low HI column densities. The HI column density sensitivity (3 sigma over 16 km/s) ranges from ~ 5 x 10^{

T. Yamaga, S. Ajimura, H. Asano, G. Beer

We conducted measurements of $K^- + {^3{\rm He}} \to \pi \!Y \!N + N'$ reactions using a $1~{\rm GeV}/c$ $K^-$-beam, with the objective of understanding the broad decay width of $\bar{K} \!N \!N$ (approximately twice as broad as that of $\Lambda(1405)$ considered to be the $\bar{K} \!N$ quasi-bound state). We successfully reproduced distributions of the $\pi

Max Reinhold Jahnke, Nicholas Braun Rodrigues

We obtain global analytic hypoellipticity for a class of differential operators that can be expressed as a zero-order perturbation of a sum of squares of vector fields with real-analytic coefficients on compact Lie groups. The key conditions are: the vector fields must satisfy H\"ormander's finite type condition; there exists a closed subgroup whose action l

Yusuf Alagöz, Engin Büyükaşık, Baran Yurtsever

Recently, the rings whose injective right modules are R-projective (respectively, max-projective) were investigated and studied in [2]. Such ring are called right almost-QF (respectively, max-QF). In this paper, our aim is to give some further characterization of these rings over more general classes of rings, and address several questions about these rings.

Enrico Baù, Thorsten Gölz, Martin Benoit, Andreas Tittl

Scattering scanning near-field optical microscopy (s-SNOM) is a powerful technique for mid-infrared spectroscopy at nanometer length scales. By investigating objects in aqueous environments through ultrathin membranes, s-SNOM has recently been extended towards label-free nanoscopy of the dynamics of living cells and nanoparticles, assessing both the optical

Dapeng Zhi, Peixin Wang, Si Liu, Luke Ong

The rapid advance of deep reinforcement learning techniques enables the oversight of safety-critical systems through the utilization of Deep Neural Networks (DNNs). This underscores the pressing need to promptly establish certified safety guarantees for such DNN-controlled systems. Most of the existing verification approaches rely on qualitative approaches,

Zekun Wu, Sahan Bulathwela, Maria Perez-Ortiz, Adriano Soares Koshiyama

Stereotype detection is a challenging and subjective task, as certain statements, such as "Black people like to play basketball," may not appear overtly toxic but still reinforce racial stereotypes. With the increasing prevalence of large language models (LLMs) in human-facing artificial intelligence (AI) applications, detecting these types of biases is esse

Kailin Zhao, Xiaolong Jin, Long Bai, Jiafeng Guo

Event detection is one of the fundamental tasks in information extraction and knowledge graph. However, a realistic event detection system often needs to deal with new event classes constantly. These new classes usually have only a few labeled instances as it is time-consuming and labor-intensive to annotate a large number of unlabeled instances. Therefore,

Niko Schmidt

The Antarctic and Greenland ice sheet simulation is challenging due to unknown parameters in the $p$-Stokes equations. In this work, we prove the existence of a solution to a parameter identification for the ice rheology and the friction coefficient. Additionally, we verify G\^ateaux differentiability of the coefficient-to-state operator by extending a simil

Pierre Rougé, Pierre-Henri Conze, Nicolas Passat, Odyssée Merveille

Segmentation in medical imaging is an essential and often preliminary task in the image processing chain, driving numerous efforts towards the design of robust segmentation algorithms. Supervised learning methods achieve excellent performances when fed with a sufficient amount of labeled data. However, such labels are typically highly time-consuming, error-p

Ryosuke Sugimoto, Yusuke Okuma, Koji Nagano, Kentaro Komori

The back-linked Fabry-Perot interferometer (BLFPI) is an interferometer topology proposed for space gravitational wave antennas with the use of inter-satellite Fabry-Perot interferometers. The BLFPI offers simultaneous and independent control over all interferometer length degrees of freedom by controlling the laser frequencies. Therefore, BLFPI does not req

Bart van Baal, Anders Jerkstrand, Annop Wongwathanarat, Thomas Janka

Understanding the explosion mechanism and hydrodynamic evolution of core-collapse supernovae is a long-standing quest in astronomy. The asymmetries caused by the explosion are encoded into the line profiles which appear in the nebular phase of the SN evolution -- with particularly clean imprints in He star explosions. Here, we carry out nine different supern

Kohki Iba, Kouji Yano

We discuss conditionings to avoid two points and one-point local time penalizations with conditioning to avoid another point, for which we adopt various clocks. We also give corrections to some of the previous results of Takeda--Yano for one-point local time penalizations.

Thibault Gauthier, Chad E. Brown

In 1995, McKay and Radziszowski proved that the Ramsey number R(4,5) is equal to 25. Their proof relies on a combination of high-level arguments and computational steps. The authors have performed the computational parts of the proof with different implementations in order to reduce the possibility of an error in their programs. In this work, we prove this t

Esther Hänggi, Iyán Méndez Veiga, Ligong Wang

We consider the wiretap channel, where the individual channel uses have memory or are influenced by an adversary. We analyze the explicit and computationally efficient construction of information-theoretically secure coding schemes which use the inverse of an extractor and an error-correcting code. These schemes are known to achieve secrecy capacity on a lar

Anouar Bahrouni, Abdelhakim Sahbani, Ariel Salort

In this paper, we investigate the monotonicity of solutions for a nonlinear equations involving the fractional Laplacian with variable exponent. We first prove different maximum principles involving this operator. Then we employ the direct moving planes method to obtain monotonicity of solutions to a nonlinear equations in which the fractional laplacian with

Keyang Zhou, Bharat Lal Bhatnagar, Jan Eric Lenssen, Gerard Pons-moll

Generating realistic hand motion sequences in interaction with objects has gained increasing attention with the growing interest in digital humans. Prior work has illustrated the effectiveness of employing occupancy-based or distance-based virtual sensors to extract hand-object interaction features. Nonetheless, these methods show limited generalizability ac

Ioanna Souvatzoglou, Athanasios Papadimitriou, Aitzan Sari, Vasileios Vlagkoulis

Neural Networks (NNs) are increasingly used in the last decade in several demanding applications, such as object detection and classification, autonomous driving, etc. Among different computing platforms for implementing NNs, FPGAs have multiple advantages due to design flexibility and high performance-to-watt ratio. Moreover, approximation techniques, such

Alexander D. Popov

Non-relativistic quantum mechanics was originally formulated to describe particles. Using ideas from the geometric quantization approach, we show how the concept of antiparticles can and should be introduced in the non-relativistic case without appealing to quantum field theory. We discuss this in detail using the example of the one-dimensional harmonic osci

Sandeep Nagar, Ehsan Farahbakhsh, Joseph Awange, Rohitash Chandra

Supervised machine learning methods for geological mapping via remote sensing face limitations due to the scarcity of accurately labelled training data that can be addressed by unsupervised learning, such as dimensionality reduction and clustering. Dimensionality reduction methods have the potential to play a crucial role in improving the accuracy of geologi

Rik W. S. Westdorp, Hermen Jan Hupkes

We study the stability and dynamics of solitons in the Korteweg-de Vries (KdV) equation with small multiplicative forcing. Forcing breaks the conservative structure of the KdV equation, leading to substantial changes in energy over long times. We show that, for small forcing, the inserted energy is almost fully absorbed by the soliton, resulting in a drastic

Qianhui Zhao, Fang Liu, Li Zhang, Yang Liu

Automated generation of feedback on programming assignments holds significant benefits for programming education, especially when it comes to advanced assignments. Automated Program Repair techniques, especially Large Language Model based approaches, have gained notable recognition for their potential to fix introductory assignments. However, the programs us

Gaurish Thakkar, Sherzod Hakimov, Marko Tadić

In recent years, multimodal natural language processing, aimed at learning from diverse data types, has garnered significant attention. However, there needs to be more clarity when it comes to analysing multimodal tasks in multi-lingual contexts. While prior studies on sentiment analysis of tweets have predominantly focused on the English language, this pape

Joonyeol Sim, Joonkyung Kim, Changjoo Nam

In this paper, we consider the problem of Multi-Robot Path Planning (MRPP) in continuous space. The difficulty of the problem arises from the extremely large search space caused by the combinatorial nature of the problem and the continuous state space. We propose a two-level approach where the low level is a sampling-based planner Safe Interval RRT* (SI-RRT*

Tanvir Mahmud, Yapeng Tian, Diana Marculescu

Visual sound source localization poses a significant challenge in identifying the semantic region of each sounding source within a video. Existing self-supervised and weakly supervised source localization methods struggle to accurately distinguish the semantic regions of each sounding object, particularly in multi-source mixtures. These methods often rely on

Anass Bairouk, Mirjana Maras, Simon Herlin, Alexander Amini

Autonomous driving presents a complex challenge, which is usually addressed with artificial intelligence models that are end-to-end or modular in nature. Within the landscape of modular approaches, a bio-inspired neural circuit policy model has emerged as an innovative control module, offering a compact and inherently interpretable system to infer a steering

Ali Taheri, Vahideh Vahidifar

In this paper we prove gradient estimates of both elliptic and parabolic types, specifically, of Souplet-Zhang, Hamilton and Li-Yau types for positive smooth solutions to a class of nonlinear parabolic equations involving the Witten or drifting Laplacian on smooth metric measure spaces. These estimates are established under various curvature conditions and l

Joshua Dimasaka, Christian Geiß, Emily So

As the world marked the midterm of the Sendai Framework for Disaster Risk Reduction 2015-2030, many countries are still struggling to monitor their climate and disaster risk because of the expensive large-scale survey of the distribution of exposure and physical vulnerability and, hence, are not on track in reducing risks amidst the intensifying effects of c

Xiaoqing Meng, Aijie Cheng, Zhengguang Liu

We propose an energy-optimized invariant energy quadratization method to solve the gradient flow models in this paper, which requires only one linear energy-optimized step to correct the auxiliary variables on each time step. In addition to inheriting the benefits of the baseline and relaxed invariant energy quadratization method, our approach has several ot

Piyush Gupta, David Isele, Sangjae Bae

Real-world driving involves intricate interactions among vehicles navigating through dense traffic scenarios. Recent research focuses on enhancing the interaction awareness of autonomous vehicles to leverage these interactions in decision-making. These interaction-aware planners rely on neural-network-based prediction models to capture inter-vehicle interact

Donghoon Han, Seunghyeon Seo, Eunhwan Park, Seong-Uk Nam

Multimodal and large language models (LLMs) have revolutionized the utilization of open-world knowledge, unlocking novel potentials across various tasks and applications. Among these domains, the video domain has notably benefited from their capabilities. In this paper, we present Highlight-CLIP (HL-CLIP), a method designed to excel in the video highlight de

Martijn Oldenhof, Edward De Brouwer, Adam Arany, Yves Moreau

Identifying the chemical structure from a graphical representation, or image, of a molecule is a challenging pattern recognition task that would greatly benefit drug development. Yet, existing methods for chemical structure recognition do not typically generalize well, and show diminished effectiveness when confronted with domains where data is sparse, or co

Tiago B. Gonçalves, Luís Atayde, Noemi Frusciante

We study a symmetric teleparallel gravity with a Lagrangian of logarithmic form. The full model leads to an accelerated universe and for specific values of the free parameters the Hubble rate reduces to the well-known Dvali-Gabadadze-Porrati model, though the evolution of the gravitational potentials are different. We consider different branches of the logar

Kim Hammar, Rolf Stadler

We formulate intrusion tolerance for a system with service replicas as a two-level optimal control problem. On the local level node controllers perform intrusion recovery, and on the global level a system controller manages the replication factor. The local and global control problems can be formulated as classical problems in operations research, namely, th

Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida, Diana Marculescu

Conditional sound separation in multi-source audio mixtures without having access to single source sound data during training is a long standing challenge. Existing mix-and-separate based methods suffer from significant performance drop with multi-source training mixtures due to the lack of supervision signal for single source separation cases during trainin

Luis M. Canonico, Jose H. García, Stephan Roche

We report an efficient numerical approach to compute the different components of the orbital Hall responses in disordered topological materials from the Berry phase theory of magnetization. The theoretical framework is based on the Chebyshev expansion of Green's functions and the off-diagonal elements of the position operator for systems under arbitrary boun

Bernhard Endtmayer, Ulrich Langer, Thomas Richter, Andreas Schafelner

This work reviews goal-oriented a posteriori error control, adaptivity and solver control for finite element approximations to boundary and initial-boundary value problems for stationary and non-stationary partial differential equations, respectively. In particular, coupled field problems with different physics may require simultaneously the accurate evaluat

Paul Best, Santiago Cuervo, Ricard Marxer

Macroscopic intelligibility models predict the expected human word-error-rate for a given speech-in-noise stimulus. In contrast, microscopic intelligibility models aim to make fine-grained predictions about listeners' perception, e.g. predicting phonetic or lexical responses. State-of-the-art macroscopic models use transfer learning from large scale deep lea

Helene C. W. Rytgaard, Mark J. van der Laan

Longitudinal settings involving outcome, competing risks and censoring events occurring and recurring in continuous time are common in medical research, but are often analyzed with methods that do not allow for taking post-baseline information into account. In this work, we define statistical and causal target parameters via the g-computation formula by carr

J. J. Choi, E. J. Jeon, J. Y. Kim, K. W. Kim

The Neutrino Elastic-scattering Observation with NaI(Tl) experiment (NEON) aims to detect coherent elastic neutrino-nucleus scattering~(\cenns) in a NaI(Tl) crystal using reactor anti-electron neutrinos at the Hanbit nuclear power plant complex. A total of 13.3 kg of NaI(Tl) crystals were initially installed in December 2020 at the tendon gallery, 23.7$\pm$0

Yunshan Ma, Yingzhi He, Wenjun Zhong, Xiang Wang

Product bundling has been a prevailing marketing strategy that is beneficial in the online shopping scenario. Effective product bundling methods depend on high-quality item representations, which need to capture both the individual items' semantics and cross-item relations. However, previous item representation learning methods, either feature fusion or grap

Bautista Arenaza, Sebastián Risau-Gusman, Inés Samengo

The marginal correlation between two variables is a measure of their linear dependence. The two original variables need not interact directly, because marginal correlation may arise from the mediation of other variables in the system. The underlying network of direct interactions can be captured by a weighted graphical model. The connection between two varia

Piotr Borodulin-Nadzieja, Barnabás Farkas, Sebastian Jachimek, Anna Pelczar-Barwacz

We study Banach spaces induced by families of finite sets in the most natural (Schreier-like) way, that is, we consider the completion $X_\mc{F}$ of $c_{00}$ with respect to the norm $\sup\{\sum_{k\in F}|x(k)|:F\in\mc{F}\}$ where $\mc{F}$ is an arbitrary (not necessarily compact) family of finite sets covering $\mbb{N}$. Among other results, we discuss the f

Moritz Hauck, Hannah Mohr, Daniel Peterseim

This paper proposes a novel collocation-type numerical stochastic homogenization method for prototypical stochastic homogenization problems with random coefficient fields of small correlation lengths. The presented method is based on a recently introduced localization technique that enforces a super-exponential decay of the basis functions relative to the un

Ataru Tanikawa, Long Wang, Michiko S. Fujii

Gaia mission offers opportunities to search for compact binaries not involved in binary interactions (hereafter inert compact binaries), and results in the discoveries of binaries containing one black hole (BH) or one neutron star (NS), called "Gaia BHs" and "Gaia NSs", respectively. We have assessed if Gaia BHs and NSs can be formed in open clusters through

Joy Qiping Yang, Salman Salamatian, Ziteng Sun, Ananda Theertha Suresh

Let $p$ denote a generative language model. Let $r$ denote a reward model that returns a scalar that captures the degree at which a draw from $p$ is preferred. The goal of language model alignment is to alter $p$ to a new distribution $\phi$ that results in a higher expected reward while keeping $\phi$ close to $p.$ A popular alignment method is the KL-const

Paolo Gazzaneo, Daniel Werner, Tommaso Maria Mazzocchi, Enrico Arrigoni

We investigate the photocurrent and spectral features in a simplified model of a Mott photovoltaic system consisting of a multilayered insulating heterostructure. The central correlated region is coupled to two metallic leads kept at different chemical potentials. A periodic drive applied to the correlated region produces excited doublons and holons across t

Satoru Kuroda

We formalize algorithms computing Pfaffian in the theory of bounded arithmetic for sharpL which is based on Berkowitz algorithm for the determinant. We also prove relations among Pfaffian properties. Furthermore, we give an algorithm for Pfaffian pairs as well.

Haoxiang Ma, Modi Shi, Boyang Gao, Di Huang

We focus on the generalization ability of the 6-DoF grasp detection method in this paper. While learning-based grasp detection methods can predict grasp poses for unseen objects using the grasp distribution learned from the training set, they often exhibit a significant performance drop when encountering objects with diverse shapes and structures. To enhance

Thom Badings, Licio Romao, Alessandro Abate, Nils Jansen

Finite-state abstractions are widely studied for the automated synthesis of correct-by-construction controllers for stochastic dynamical systems. However, existing abstraction methods often lead to prohibitively large finite-state models. To address this issue, we propose a novel abstraction scheme for stochastic linear systems that exploits the system's sta

Zhuolong Li, Xingao Li, Changxing Ding, Xiangmin Xu

Detecting human-object interaction (HOI) has long been limited by the amount of supervised data available. Recent approaches address this issue by pre-training according to pseudo-labels, which align object regions with HOI triplets parsed from image captions. However, pseudo-labeling is tricky and noisy, making HOI pre-training a complex process. Therefore,