March 2024 arXiv papers — page 10

Ieva Petrulionyte, Julien Mairal, Michael Arbel

In this paper, we introduce a new functional point of view on bilevel optimization problems for machine learning, where the inner objective is minimized over a function space. These types of problems are most often solved by using methods developed in the parametric setting, where the inner objective is strongly convex with respect to the parameters of the p

You Wu, Kean Liu, Xiaoyue Mi, Fan Tang

Concept personalization methods enable large text-to-image models to learn specific subjects (e.g., objects/poses/3D models) and synthesize renditions in new contexts. Given that the image references are highly biased towards visual attributes, state-of-the-art personalization models tend to overfit the whole subject and cannot disentangle visual characteris

Haikuo Shao, Huihong Shi, Wendong Mao, Zhongfeng Wang

Vision Transformers (ViTs) have achieved significant success in computer vision. However, their intensive computations and massive memory footprint challenge ViTs' deployment on embedded devices, calling for efficient ViTs. Among them, EfficientViT, the state-of-the-art one, features a Convolution-Transformer hybrid architecture, enhancing both accuracy and

Kamal Thapa, Olena S. Iadlovska, Bijaya Basnet, Hao Wang

We explore the structure and magnetic field response of edge dislocations in Grandjean-Cano wedge cells filled with chiral mixtures of the ferroelectric nematic mesogen DIO. Upon cooling, the ordering changes from paraelectric in the cholesteric phase N* to antiferroelectric in the smectic SmZ_A* and to ferroelectric in the cholesteric N_F*. Dislocations of

Kaitao Meng, Christos Masouros

In this work, we study integrated sensing and communication (ISAC) networks intending to effectively balance sensing and communication (S&C) performance at the network level. Through the simultaneous utilization of multi-point (CoMP) coordinated joint transmission and distributed multiple-input multiple-output (MIMO) radar techniques, we propose a cooperativ

Pham Duy Khanh, Vu Vinh Huy Khoa, Juan Enrique Martínez-Legaz, Boris S. Mordukhovich

The paper is devoted to establishing relationships between global and local monotonicity, as well as their maximality versions, for single-valued and set-valued mappings between finite-dimensional and infinite-dimensional spaces. We first show that for single-valued operators with convex domains in locally convex topological spaces, their continuity ensures

Raphael de Omena

This work investigates invariants, including the GSV-index, the local Euler obstruction, and the Brasselet number, within the context of isolated complete intersection singularities (ICIS). The goal is to forge connections among these invariants, facilitating the extraction of both topological and geometric insights through algebraic methods. The Bruce-Rober

Sanghyun Woo, Kwanyong Park, Inkyu Shin, Myungchul Kim

Multi-target multi-camera tracking is a crucial task that involves identifying and tracking individuals over time using video streams from multiple cameras. This task has practical applications in various fields, such as visual surveillance, crowd behavior analysis, and anomaly detection. However, due to the difficulty and cost of collecting and labeling dat

Federico Campanini, Carmelo Antonio Finocchiaro

Let $f:A\longrightarrow B, g:A\longrightarrow C$ be ring homomorphisms and let $\mathfrak{b}$ (resp., $\mathfrak{c}$) be an ideal of $B$ (resp., $C$) satisfying $f^{-1}(\mathfrak{b})=g^{-1}(\mathfrak{c})$. Recently Kabbaj, Louartiti and Tamekkante defined and studied the following subring $$A\bowtie^{f,g}(\mathfrak{b},\mathfrak{c}) :=\{(f(a)+b, g(a)+c)\mid a

Patricio E. Cubillos

Over the past decade, exoplanet atmospheric characterization has became what some might call the cosmology of astronomy. In an attempt to extract and understand the weak planetary signals (a few percent down to a few tens of ppm times that of their host-star signals), researchers have developed dozens of idealized planetary atmospheric models. Physical inter

Aleksandr V. Petrov, Sean MacAvaney, Craig Macdonald

Transformer-based Cross-Encoders achieve state-of-the-art effectiveness in text retrieval. However, Cross-Encoders based on large transformer models (such as BERT or T5) are computationally expensive and allow for scoring only a small number of documents within a reasonably small latency window. However, keeping search latencies low is important for user sat

Kaiyuan Cui, Xinyan Wang, Zicheng Zhang, Weichen Zhao

Continuous graph neural models based on differential equations have expanded the architecture of graph neural networks (GNNs). Due to the connection between graph diffusion and message passing, diffusion-based models have been widely studied. However, diffusion naturally drives the system towards an equilibrium state, leading to issues like over-smoothing. T

Federico Campanini, Carmelo Antonio Finocchiaro

Let $A$ be the fiber product $R\times_TB$, where $B\to T$ is a surjective ring homomorphism with regular kernel and $R\subseteq T$ is a ring extension where $T$ is an overring of $R$. In this paper we provide a characterization of when $A$ has distinguished Pr\"ufer-like properties and new constructions of Pr\"ufer rings with zero-divisors. Furthermore we gi

Jonas El Gammal, Sven Günther, Emil Brinch Holm, Andreas Nygaard

Recently, cosmology has seen a surge in alternative models that purport to solve the discrepancy between the values of the Hubble constant $H_0$ as measured by cosmological microwave background anisotropies and local supernovae, respectively. In particular, many of the most successful approaches have involved varying fundamental constants, such as an alterna

Jiani Fan, Minrui Xu, Jiale Guo, Lwin Khin Shar

The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through onboard infotainment applications. Decentralized data sharing can improve security, privacy, reliability, and facilitate infotainment data sharing in IoVs. However, decentralized d

Yuta Nasuda

In this thesis, we study a quantization condition in relation to the solvability of Schr\"{o}dinger equations. This quantization condition is called the SWKB (supersymmetric Wentzel-Kramers-Brillouin) quantization condition and has been known in the context of supersymmetric quantum mechanics for decades. The main contents of this thesis are recapitulated as

Robert Godwin-Jones

Generative AI offers significant opportunities for language learning. Tools like ChatGPT can provide informal second language practice through chats in written or voice forms, with the learner specifying through prompts conversational parameters such as proficiency level, language register, and discussion topics. AI can be instructed to give corrective feedb

Abed Alhakim Freihat, Hadi Khalilia, Gábor Bella, Fausto Giunchiglia

High-quality WordNets are crucial for achieving high-quality results in NLP applications that rely on such resources. However, the wordnets of most languages suffer from serious issues of correctness and completeness with respect to the words and word meanings they define, such as incorrect lemmas, missing glosses and example sentences, or an inadequate, Wes

Nathaniel Josephs, Elizabeth Upton

In team sports, traditional ranking statistics do not allow for the simultaneous evaluation of both individuals and combinations of players. Metrics for individual player rankings often fail to include the interaction effects between groups of players, while methods for assessing full lineups cannot be used to identify the value of lower-order combinations o

Chao Pang, Xingxing Weng, Jiang Wu, Jiayu Li

This paper develops a Versatile and Honest vision language Model (VHM) for remote sensing image analysis. VHM is built on a large-scale remote sensing image-text dataset with rich-content captions (VersaD), and an honest instruction dataset comprising both factual and deceptive questions (HnstD). Unlike prevailing remote sensing image-text datasets, in which

Yimeng Min, Carla P. Gomes

We study the generalization capability of Unsupervised Learning in solving the Travelling Salesman Problem (TSP). We use a Graph Neural Network (GNN) trained with a surrogate loss function to generate an embedding for each node. We use these embeddings to construct a heat map that indicates the likelihood of each edge being part of the optimal route. We then

Astorg Matthieu, Bianchi Fabrizio

We prove that horn maps associated to quadratic semi-parabolic fixed points of H\'enon maps, first introduced by Bedford, Smillie, and Ueda, satisfy a weak form of the Ahlfors island property. As a consequence, two natural definitions of their Julia set (the non-normality locus of the family of iterates and the closure of the set of the repelling periodic po

Tomohiro Kikuta, Sachio Komori, Keiichiro Imura, Tomoyasu Taniyama

In a ferromagnet/superconductor/ferromagnet (F/S/F) superconducting spin-valve (SSV), a change of the magnetization alignment of the two F layers modulates the critical temperature (Tc) of the S layer. The Tc-switching (the SSV effect) is based on the interplay between superconductivity and magnetism. Fast and large resistive switching associated with the Tc

Baptiste Coquinot, Lydéric Bocquet, Nikita Kavokine

Hydraulic energy is a key component of the global energy mix, yet there exists no practical way of harvesting it at small scales, from flows at low Reynolds number. This has triggered the search for alternative hydroelectric conversion methodologies, leading to unconventional proposals based on droplet triboelectricity, water evaporation, osmotic energy or f

Yazheng Yang, Yuqi Wang, Yaxuan Li, Sankalok Sen

In the domain of data science, the predictive tasks of classification, regression, and imputation of missing values are commonly encountered challenges associated with tabular data. This research endeavors to apply Large Language Models (LLMs) towards addressing these predictive tasks. Despite their proficiency in comprehending natural language, LLMs fall sh

Frederik Stouten

Consider the rectangular triangle with sides with length 1 and 1, then the oblique side has length square root of 2. Now construct on top of the oblique side, a new rectangular triangle with the oblique side as rectangle side and a second rectangle side of length 1. Continue this process indefinitely, what you get is called "the spiral of Theodorus". Now the

Hubert Woszczek, Aleksei Chechkin, Agnieszka Wylomanska

The scaled Brownian motion (SBM) is regarded as one of the paradigmatic random processes, featuring the anomalous diffusion property characterized by the diffusion exponent. It is a Gaussian, self-similar process with independent increments, which has found applications across various fields, from turbulence and stochastic hydrology to biophysics. In our pap

Yu-Hong Dai, Jiani Wang, Liwei Zhang

This paper presents a stochastic approximation proximal subgradient (SAPS) method for stochastic convex-concave minimax optimization. By accessing unbiased and variance bounded approximate subgradients, we show that this algorithm exhibits ${\rm O}(N^{-1/2})$ expected convergence rate of the minimax optimality measure if the parameters in the algorithm are p

Junhao Xu, Longdi Xian, Zening Liu, Mingliang Chen

Artificial Intelligence Generated Content (AIGC) technology development has facilitated the creation of rumors with misinformation, impacting societal, economic, and political ecosystems, challenging democracy. Current rumor detection efforts fall short by merely labeling potentially misinformation (classification task), inadequately addressing the issue, an

V. Pastukhov

Thermodynamically stable low-temperature phases of the Bose-Fermi mixtures composed of bosons and spinless fermions close to four dimensions are considered. In the regime, where the only boson-fermion two-body interaction is present and tuned to unitary limit, the properties of a system solely depend on the mass and number ratios of constituent atoms. In add

Radan Ganchev

The widespread use of automated voice assistants along with other recent technological developments have increased the demand for applications that process audio signals and human voice in particular. Voice recognition tasks are typically performed using artificial intelligence and machine learning models. Even though end-to-end models exist, properly pre-pr

CMS Collaboration

A measurement of the production cross section of a Higgs boson with transverse momentum greater than 250 GeV is presented where the Higgs boson decays to a pair of $\tau$ leptons. It is based on proton-proton collision data collected by the CMS experiment at the CERN LHC at a center-of-mass energy of 13 TeV. The data sample corresponds to an integrated lumin

Parth Patel, Milena Radenkovic

Space Communication poses challenges such as severe delays, hard-to-predict routes and communication disruptions. The Delay Tolerant Network architecture, having been specifically designed keeping such scenarios in mind, is suitable to address some challenges. The traditional DTN routing protocols fall short of delivering optimal performance, due to the inhe

Kaiyi Chi, Qianqian Yang, Yuanchao Shu, Zhaohui Yang

While existing studies have highlighted the advantages of deep learning (DL)-based joint source-channel coding (JSCC) schemes in enhancing transmission efficiency, they often overlook the crucial aspect of resource management during the deployment phase. In this paper, we propose an approach to minimize the transmission latency in an uplink JSCC-based system

Maryam Abdolali, Giovanni Barbarino, Nicolas Gillis

Simplex-structured matrix factorization (SSMF) is a generalization of nonnegative matrix factorization, a fundamental interpretable data analysis model, and has applications in hyperspectral unmixing and topic modeling. To obtain identifiable solutions, a standard approach is to find minimum-volume solutions. By taking advantage of the duality/polarity conce

Yingxue Fu

Existing discourse corpora are annotated based on different frameworks, which show significant dissimilarities in definitions of arguments and relations and structural constraints. Despite surface differences, these frameworks share basic understandings of discourse relations. The relationship between these frameworks has been an open research question, espe

Victor Silva dos Santos, Erwan Gloaguen, Shiva Tirdad

Geological maps are an extremely valuable source of information for the Earth sciences. They provide insights into mineral exploration, vulnerability to natural hazards, and many other applications. These maps are created using numerical or conceptual models that use geological observations to extrapolate data. Geostatistical techniques have traditionally be

Shuo Liu, Kaining Ying, Hao Zhang, Yue Yang

This paper presents ConvBench, a novel multi-turn conversation evaluation benchmark tailored for Large Vision-Language Models (LVLMs). Unlike existing benchmarks that assess individual capabilities in single-turn dialogues, ConvBench adopts a three-level multimodal capability hierarchy, mimicking human cognitive processes by stacking up perception, reasoning

Luozhou Wang, Ziyang Mai, Guibao Shen, Yixun Liang

In this work, we present a novel approach for motion customization in video generation, addressing the widespread gap in the exploration of motion representation within video generative models. Recognizing the unique challenges posed by the spatiotemporal nature of video, our method introduces Motion Embeddings, a set of explicit, temporally coherent embeddi

Xuehan Hu, Grigoris Paouris

We study the small ball probability of an order-$\ell$ simple random tensor $X=X^{(1)}\otimes\cdots\otimes X^{(\ell)}$ where $X^{(i)}, 1\leq i\leq\ell$ are independent random vectors in $\mathbb{R}^n$ that are log-concave or have independent coordinates with bounded densities. We show that the probability that the projection of $X$ onto an $m$-dimensional su

Jun Hu, Zhan-Long Wang

This study investigates the crystallization and self-assembly phenomena of polyacrylamide (PAM) solutions during evaporation. While traditional thin-film fabrication methods such as spin coating and drop casting are commonly used, this study utilizes a simple evaporation approach to gain insights into the self-assembly processes of PAM solutions. We examined

Leonardo Neumann, Antonio Guimarães, Diego F. Aranha, Edson Borin

The widespread application of machine learning algorithms is a matter of increasing concern for the data privacy research community, and many have sought to develop privacy-preserving techniques for it. Among existing approaches, the homomorphic evaluation of ML algorithms stands out by performing operations directly over encrypted data, enabling strong guar

Kiran Sharma

Research stands as a pivotal factor in propelling the progress of any nation forward. However, if tainted by misconduct, it poses a significant threat to the nation's development. This study aims to scrutinize various cases of deliberate scientific misconduct by Indian researchers. A comprehensive analysis was conducted on 3,244 retracted publications source

Jagannath Das, Sarbajaya Kundu, Aman Kumar, Vikram Tripathi

The honeycomb Kitaev model describes a $Z_2$ spin liquid with topological order and fractionalized excitations consisting of gapped $\pi$-fluxes and free Majorana fermions. Competing interactions, even when not very strong, are known to destabilize the Kitaev spin liquid. Magnetic fields are a convenient parameter for tuning between different phases of the K

Yue Wang, Zhi Tian, FXin Fan, Zhipeng Cai

The rapid growth of Internet of Things (IoT) has led to the widespread deployment of smart IoT devices at wireless edge for collaborative machine learning tasks, ushering in a new era of edge learning. With a huge number of hardware-constrained IoT devices operating in resource-limited wireless networks, edge learning encounters substantial challenges, inclu

I. I. Bulygin, M. A. Shchurov, A. G. Rudnitskiy

Finding a suitable very long baseline (VLBI) interferometer geometry is a key task in planning observations, especially imaging sessions. The main characteristic of the quality of VLBI imaging data is the (u, v)-coverage. In the case when one or more radio telescopes are located in space, this task becomes more complex. This paper presents a method for recov

Pengzhi Li, Baijuan Li, Zhiheng Li

Recently, the development of large-scale models has paved the way for various interdisciplinary research, including architecture. By using generative AI, we present a novel workflow that utilizes AI models to generate conceptual floorplans and 3D models from simple sketches, enabling rapid ideation and controlled generation of architectural renderings based

Louigi Addario Berry, Simon Briend, Luc Devroye, Serte Donderwinkel

We study a random recursive tree model featuring complete redirection called the random friend tree and introduced by Saram\"aki and Kaski. Vertices are attached in a sequential manner one by one by selecting an existing target vertex and connecting to one of its neighbours (or friends), chosen uniformly at random. This model has interesting emergent propert

Tuan Nguyen, Corinne Fredouille, Alain Ghio, Mathieu Balaguer

Automatic speech quality assessment has raised more attention as an alternative or support to traditional perceptual clinical evaluation. However, most research so far only gains good results on simple tasks such as binary classification, largely due to data scarcity. To deal with this challenge, current works tend to segment patients' audio files into many

Shuangjian Li, Tao Zhu, Furong Duan, Liming Chen

Wearable sensor-based human activity recognition (HAR) is a critical research domain in activity perception. However, achieving high efficiency and long sequence recognition remains a challenge. Despite the extensive investigation of temporal deep learning models, such as CNNs, RNNs, and transformers, their extensive parameters often pose significant computa

Urša Zrimšek, Erik Štrumbelj

A critical literature review and comprehensive simulation study is used to show that (a) non-parametric bootstrap is a viable alternative to commonly taught and used methods in basic estimation tasks (mean, variance, quartiles, correlation) and (b), contrary to recommendations in most related work, double bootstrap performs better than BCa. Quantifying uncer

M. Azaiez, A. Doubova, S. Ervedoza, F. Jelassi

We analyze an optimization problem of the conductivity in a composite material arising in a heat conduction energy storage problem. The model is described by the heat equation that specifies the heat exchange between two types of materials with different conductive properties with Dirichlet-Neumann boundary conditions on the external part of the domain, and

Po-Heng Chen, Sijia Cheng, Wei-Lin Chen, Yen-Ting Lin

The evaluation of large language models (LLMs) has drawn substantial attention in the field recently. This work focuses on evaluating LLMs in a Chinese context, specifically, for Traditional Chinese which has been largely underrepresented in existing benchmarks. We present TMLU, a holistic evaluation suit tailored for assessing the advanced knowledge and rea

B. Carry, J. Peloton, R. Le Montagner, M. Mahlke

Large surveys provide numerous non-targeted observations of small bodies (SSOs). The upcoming LSST of the Rubin observatory will be the largest source of SSO photometry in the next decade. With non-coordinated epochs of observation, colors, and therefore taxonomy and composition, can only be computed by comparing absolute magnitudes obtained in each filter b

Georges Dloussky

Let $S$ be a minimal compact complex surface with Betti numbers $b_1(S)=1$ and $b_2(S)\ge 1$ i.e. a compact surface in class VII$_0^+$. We show that if there exists a twisted logarithmic 1-form $\tau\in H^0(S,\Omega^1(\log D)\otimes \mathcal L_\lambda)$, where $D$ is a non zero divisor and $\mathcal L\in H^1(S,\mathbb C^\star)$, then $S$ is a Kato surface. I

K. Evers, M. Farisco, R. Chatila, B. D. Earp

The pursuit of artificial consciousness requires conceptual clarity to navigate its theoretical and empirical challenges. This paper introduces a composite, multilevel, and multidimensional model of consciousness as a heuristic framework to guide research in this field. Consciousness is treated as a complex phenomenon, with distinct constituents and dimensio

Goro Akagi, Florian Salin

The present paper is concerned with the Cauchy-Dirichlet problem for fractional (and non-fractional) nonlinear diffusion equations posed in bounded domains. Main results consist of well-posedness in an energy class with no sign restriction and convergence of such (possibly sign-changing) energy solutions to asymptotic profiles after a proper rescaling. They

Mark Popinchalk

A Total Solar Eclipse (TSE) is a shocking and sublime experience. In just a week hundreds of millions of Homo Sapiens will attempt to see the 2024 eclipse as it stretches across the North American continent. However, while Homo Sapiens may be uniquely positioned to understand and predict eclipses, they are not the only species capable of observing them. The

Marie-Christin Heißenbüttel, Pierre-Maurice Piel, Julian Klein, Thorsten Deilmann

The optical properties of the layered magnet CrSBr are dominated by intralayer excitons: the antiferromagnetic order between the layers makes layer-to-layer charge hopping, and therefore interlayer excitons, spin-forbidden. An external magnetic field, however, continuously drives the magnetic order towards layer-to-layer ferromagnetic, which opens spin-allow

Qiang Guo, Rubo Zhang, Di Zhao

Aiming at the metro video surveillance system has not been able to effectively solve the metro crowd density estimation problem, a Metro Crowd density estimation Network (called MCNet) is proposed to automatically classify crowd density level of passengers. Firstly, an Integrating Multi-scale Attention (IMA) module is proposed to enhance the ability of the p

Kiran Garimella, Abhilash Datta

The relationship between television shows and social media has become increasingly intertwined in recent years. Social media platforms, particularly Twitter, have emerged as significant sources of public opinion and discourse on topics discussed in television shows. In India, news debates leverage the popularity of social media to promote hashtags and engage

Revathy B S, Victor Mukherjee, Uma Divakaran

We construct a quantum critical Otto engine that is powered by finite temperature baths. We show that the work output of the engine shows universal power law behavior that depends on the critical exponents of the working medium, as well as on the temperature of the cold bath. Furthermore, higher temperatures of the cold bath allows the engine to approach the

Yeow Meng Chee, Tuvi Etzion, Han Mao Kiah, Hui Zhang

Recovery sets for vectors and subspaces are important in the construction of distributed storage system codes. These concepts are also interesting in their own right. In this paper, we consider the following very basic recovery question: what is the maximum number of possible pairwise disjoint recovery sets for each recovered element? The recovered elements

Dung Le

It will be established that the mean oscillation of bounded weak solutions to strongly coupled parabolic systems is small in small balls. If the systems are regular elliptic then their bounded weak solutions are H\"older continuous. Further assumptions on the systems will even prove that these solutions exist globally. Weak solutions to degenerate systems of

Chuan Huang, Jia Wei, Rui Li

Multi-modal brain images from MRI scans are widely used in clinical diagnosis to provide complementary information from different modalities. However, obtaining fully paired multi-modal images in practice is challenging due to various factors, such as time, cost, and artifacts, resulting in modality-missing brain images. To address this problem, unsupervised

Marco Araujo

Rather than simply offering suggestions, this guideline for the methodology chapter in computer science dissertations provides thorough insights on how to develop a strong research methodology within the area of computer science. The method is structured into several parts starting with an overview of research strategies which include experiments, surveys, i

Kiran Garimella, Simon Chauchard

In recent years, reports and anecdotal evidence pointing at the role of WhatsApp in a variety of events, ranging from elections to collective violence, have emerged. While academic research should examine the validity of these claims, obtaining WhatsApp data for research is notably challenging, contrasting with the relative abundance of data from platforms l

Avraham Aizenbud, Raf Cluckers, Michel Raibaut, Tamara Servi

We introduce a notion of distributions on $\mathbb{R}^n$, called distributions of C$^{{\mathrm{exp}}}$-class, based on wavelet transforms of distributions and the theory from Cluckers, Comte, Miller, Rolin, Servi (2018) about C$^{{\mathrm{exp}}}$-class functions. We prove that the framework of C$^{{\mathrm{exp}}}$-class distributions is closed under natural

Krister M. Swenson

In 1937, biologists Sturtevant and Tan posed a computational question: transform a chromosome represented by a permutation of genes, into a second permutation, using a minimum-length sequence of reversals, each inverting the order of a contiguous subset of elements. Solutions to this problem, applied to Drosophila chromosomes, were computed by hand. The firs

Kfir Blum, Mehrdad Mirbabayi

We show that quantum fluctuations of an expanding phase transition bubble give rise to gravitational wave (GW) emission, even when considering a single bubble, without bubble collisions or plasma effects. The ratio of GW energy to the total bubble energy reservoir increases with time as $\propto t$. If the bubble expands for long enough before percolation de

Duzhen Zhang, Qingyu Wang, Tielin Zhang, Bo Xu

The success of Deep Reinforcement Learning (DRL) is largely attributed to utilizing Artificial Neural Networks (ANNs) as function approximators. Recent advances in neuroscience have unveiled that the human brain achieves efficient reward-based learning, at least by integrating spiking neurons with spatial-temporal dynamics and network topologies with biologi

Pierandrea Vergallo, Evgeny V. Ferapontov

We investigate Hamiltonian aspects of the integro-differential kinetic equation for dense soliton gas which results as a thermodynamic limit of the Whitham equations. Under a delta-functional ansatz, the kinetic equation reduces to a non-diagonalisable system of hydrodynamic type whose matrix consists of several $2\times 2$ Jordan blocks. We demonstrate that

Nicolas Troquard

In resource contribution games, a class of non-cooperative games, the players want to obtain a bundle of resources and are endowed with bags of bundles of resources that they can make available into a common for all to enjoy. Available resources can then be used towards their private goals. A player is potentially satisfied with a profile of contributed reso

Stephanie M. LaMassa, Alessandro Peca, C. Megan Urry, Eilat Glikman

We present the third catalog release of the wide-area (31.3 deg$^2$) Stripe 82 X-ray survey. This catalog combines previously published X-ray source properties with multiwavelength counterparts and photometric redshifts, presents 343 new spectroscopic redshifts, and provides black hole masses for 1297 Type 1 Active Galactic Nuclei (AGN). With spectroscopic r

Ke Wu, Kaizhao Zhang, Zhiwei Zhang, Shanshuai Yuan

Online dense mapping of urban scenes forms a fundamental cornerstone for scene understanding and navigation of autonomous vehicles. Recent advancements in mapping methods are mainly based on NeRF, whose rendering speed is too slow to meet online requirements. 3D Gaussian Splatting (3DGS), with its rendering speed hundreds of times faster than NeRF, holds gre

Silvia García-Méndez, Milagros Fernández-Gavilanes, Jonathan Juncal-Martínez, Francisco J. González-Castaño

Short texts are omnipresent in real-time news, social network commentaries, etc. Traditional text representation methods have been successfully applied to self-contained documents of medium size. However, information in short texts is often insufficient, due, for example, to the use of mnemonics, which makes them hard to classify. Therefore, the particularit

Zehao Wen, Rabih Younes

In our rapidly evolving digital sphere, the ability to discern media bias becomes crucial as it can shape public sentiment and influence pivotal decisions. The advent of large language models (LLMs), such as ChatGPT, noted for their broad utility in various natural language processing (NLP) tasks, invites exploration of their efficacy in media bias detection

Francois Meyer, Jan Buys

Multilingual modelling can improve machine translation for low-resource languages, partly through shared subword representations. This paper studies the role of subword segmentation in cross-lingual transfer. We systematically compare the efficacy of several subword methods in promoting synergy and preventing interference across different linguistic typologi

Hei Yi Mak, Flint Xiaofeng Fan, Luca A. Lanzendörfer, Cheston Tan

In this study, we delve into Federated Reinforcement Learning (FedRL) in the context of value-based agents operating across diverse Markov Decision Processes (MDPs). Existing FedRL methods typically aggregate agents' learning by averaging the value functions across them to improve their performance. However, this aggregation strategy is suboptimal in heterog

C. A. Downing, M. S. Ukhtary

The challenge of storing energy efficiently and sustainably is highly prominent within modern scientific investigations. Due to the ongoing trend of miniaturization, the design of expressly quantum storage devices is itself a crucial task within current quantum technological research. Here we provide a transparent analytic model of a two-component quantum ba

Paras Naik

Thanks to the large cross-section for the production of strange and charm mesons at the Large Hadron Collider, LHCb has recently performed several new explorations of rare transitions that are highly suppressed or forbidden by the Standard Model: mostly flavour changing neutral current decays, but also lepton flavour violating decays. Physics beyond the Stan

Jaehoon Ko, Kyusun Cho, Joungbin Lee, Heeji Yoon

Recent methods for audio-driven talking head synthesis often optimize neural radiance fields (NeRF) on a monocular talking portrait video, leveraging its capability to render high-fidelity and 3D-consistent novel-view frames. However, they often struggle to reconstruct complete face geometry due to the absence of comprehensive 3D information in the input mon

Wolfgang Hoegele

The goal of this paper is to demonstrate the general modeling and practical simulation of random equations with mixture model parameter random variables. Random equations, understood as stationary (non-dynamical) equations with parameters as random variables, have a long history and a broad range of applications. The specific novelty of this explorative stud

Jiani Fan, Minrui Xu, Ziyao Liu, Huanyi Ye

Artificial Intelligence-Generated Content (AIGC) refers to the paradigm of automated content generation utilizing AI models. Mobile AIGC services in the Internet of Vehicles (IoV) network have numerous advantages over traditional cloud-based AIGC services, including enhanced network efficiency, better reconfigurability, and stronger data security and privacy

Xiangfei Qiu, Jilin Hu, Lekui Zhou, Xingjian Wu

Time series are generated in diverse domains such as economic, traffic, health, and energy, where forecasting of future values has numerous important applications. Not surprisingly, many forecasting methods are being proposed. To ensure progress, it is essential to be able to study and compare such methods empirically in a comprehensive and reliable manner.

Yvet Renkema, Nico Brinkel, Tarek Alskaif

This paper studies the use of conformal prediction (CP), an emerging probabilistic forecasting method, for day-ahead photovoltaic power predictions to enhance participation in electricity markets. First, machine learning models are used to construct point predictions. Thereafter, several variants of CP are implemented to quantify the uncertainty of those pre

M. A. Reyes, C. Dalfó, M. A. Fiol, A. Messegué

The $k$-token graph $F_k(G)$ of a graph $G$ is the graph whose vertices are the $k$-subsets of vertices from $G$, two of which being adjacent whenever their symmetric difference is a pair of adjacent vertices in $G$. In this paper, we propose a general method to find the spectrum and eigenspaces of the $k$-token graph $F_k(C_n)$ of a cycle $C_n$. The method

Nihar Ranjan Sahoo, Pranamya Prashant Kulkarni, Narjis Asad, Arif Ahmad

The pervasive influence of social biases in language data has sparked the need for benchmark datasets that capture and evaluate these biases in Large Language Models (LLMs). Existing efforts predominantly focus on English language and the Western context, leaving a void for a reliable dataset that encapsulates India's unique socio-cultural nuances. To bridge

Vishnu Rajagopal

We study the Unruh effect in doubly special relativity (DSR) framework by generalising the Doppler-shift method to DSR. For both the scalar and Dirac particles, we observe a deviation in the power spectrum of Unruh radiation from the standard Bose-Einstein and Fermi-Dirac distributions, respectively, due to the presence of the frame independent length scale

Nilesh Kumar Sahu, Manjeet Yadav, Mudita Chaturvedi, Snehil Gupta

Mental health disorders affect a significant portion of the global population, with diagnoses primarily conducted through Mental State Examinations (MSEs). MSEs serve as structured assessments to evaluate behavioral and cognitive functioning across various domains, aiding mental health professionals in diagnosis and treatment monitoring. However, in developi

Stephen M. Wilkins, Sophie L. Newman, Will J. Roper

In recent years the James Webb Space Telescope has enabled the frontier of observational galaxy formation to push to ever higher redshift, deep within cosmic dawn. However, what is high-redshift, and when was cosmic dawn? While widely used, these terms (as well as many other confusing terms) are not consistently defined in the literature; this both hampers e

D. Sidious, S. Arcari, N. Barbieri, L. Bazzanini

The cosmic microwave background (CMB) radiation offers a unique avenue for exploring the early Universe's dynamics and evolution. In this paper, we delve into the fascinating realm of slow-roll inflation, contextualizing the primordial acoustic perturbations as the resonant echoes akin to the iconic sound of Chewbacca from the Star Wars universe. By extrapol

Sidi Wu, Yizi Chen, Samuel Mermet, Lorenz Hurni

Most image-to-image translation models postulate that a unique correspondence exists between the semantic classes of the source and target domains. However, this assumption does not always hold in real-world scenarios due to divergent distributions, different class sets, and asymmetrical information representation. As conventional GANs attempt to generate im

Francisco de Arriba-Pérez, Silvia García-Méndez, José A. Regueiro-Janeiro, Francisco J. González-Castaño

Micro-blogging sources such as the Twitter social network provide valuable real-time data for market prediction models. Investors' opinions in this network follow the fluctuations of the stock markets and often include educated speculations on market opportunities that may have impact on the actions of other investors. In view of this, we propose a novel sys

Zehui Zhu, Imad L. Al-Qadi

Resurfacing a moderately deteriorated Portland cement concrete (PCC) pavement with asphalt concrete (AC) layers is considered an efficient rehabilitation practice. However, reflective cracks may develop shortly after resurfacing because of discontinuities (e.g. joints and cracks) in existing PCC pavement. In this paper, a new accelerated full-scale testing a

Timothy Y. Chow

Ivan Niven's succinct proof that pi is irrational is easy to verify, but it begins with a magical formula that appears to come out of nowhere, and whose origin remains mysterious even after one goes through the proof. The goal of this expository paper is to describe a thought process by which a mathematician might come up with the proof from scratch, without

Miguel Vaquero, David Martín de Diego, Jorge Cortés

This paper presents a general method to construct Poisson integrators, i.e., integrators that preserve the underlying Poisson geometry. We assume the Poisson manifold is integrable, meaning there is a known local symplectic groupoid for which the Poisson manifold serves as the set of units. Our constructions build upon the correspondence between Poisson diff

Johan Klarbring, Aron Walsh

Solid-state sodium batteries require effective electrolytes that conduct at room temperature. The Na$_3$SbS$_4$ (Pn = P, Sb; Ch = S, Se) family have been studied for their high Na ion conductivity. The population of Na vacancies, which mediate ion diffusion in these materials, can be enhanced through aliovalent doping on the pnictogen site. To probe the micr

Nikita Trukhanov, Ilya Soloveychik

The demand for inference on extremely large scale LLMs has seen enormous growth in the recent months. It made evident the colossal shortage of dedicated hardware capable of efficient and fast processing of the involved compute and memory movement. The problem is aggravated by the exploding raise in the lengths of the sequences being processed, since those re

Silvia García-Méndez, Francisco de Arriba-Pérez, Francisco J. González-Castaño, José A. Regueiro-Janeiro

Current language processing technologies allow the creation of conversational chatbot platforms. Even though artificial intelligence is still too immature to support satisfactory user experience in many mass market domains, conversational interfaces have found their way into ad hoc applications such as call centres and online shopping assistants. However, th