February 2024 arXiv papers — page 6

Chen Zhang, Xiao Liu, Jiuheng Lin, Yansong Feng

Existing large language models struggle to support numerous low-resource languages, particularly the extremely low-resource ones, for which there is minimal training data available for effective parameter updating. We thus investigate whether LLMs can learn a new language on the fly solely through prompting. To study this question, we collect a research suit

William Hunt, Toby Godfrey, Mohammad D. Soorati

With the increasing prevalence and diversity of robots interacting in the real world, there is need for flexible, on-the-fly planning and cooperation. Large Language Models are starting to be explored in a multimodal setup for communication, coordination, and planning in robotics. Existing approaches generally use a single agent building a plan, or have mult

Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao

Planning for both immediate and long-term benefits becomes increasingly important in recommendation. Existing methods apply Reinforcement Learning (RL) to learn planning capacity by maximizing cumulative reward for long-term recommendation. However, the scarcity of recommendation data presents challenges such as instability and susceptibility to overfitting

B. Petrović, A. Bader, J. Nauschütz, T. Sato

We present a comparison between interband cascade lasers (ICLs) with a 6-stage active region emitting at 5 $\mu$m with AlSb/InAs superlattice claddings and with bulk Al_0.85 Ga_0.15 As_0.07 Sb_0.93 claddings. Utilizing bulk AlGaAsSb claddings with their lower refractive index compared to the more commonly used AlSb/InAs superlattice claddings, the mode-confi

Federica Dragoni, Qing Liu, Ye Zhang

We show that the square of Carnot-Carath\'eodory distance from the origin, in step 2 Carnot groups, enjoys the horizontal semiconcavity (h-semiconcavity) everywhere in the group including the origin. We first give a proof in the case of ideal Carnot groups, based on the simple group structure as well as estimates for the Euclidean semiconcavity. Our proof of

Javad Aliakbari, Johan Östman, Alexandre Graell i Amat

We address the challenge of federated learning on graph-structured data distributed across multiple clients. Specifically, we focus on the prevalent scenario of interconnected subgraphs, where interconnections between different clients play a critical role. We present a novel framework for this scenario, named FedStruct, that harnesses deep structural depend

Mattia Stival, Lorenzo Schiavon, Stefano Campostrini

In several countries, including Italy, a prominent approach to population health surveillance involves conducting repeated cross-sectional surveys at short intervals of time. These surveys gather information on the health status of individual respondents, including details on their behaviours, risk factors, and relevant socio-demographic information. While t

Hongxin Li, Zeyu Wang, Xu Yang, Yuran Yang

Image-goal navigation is a challenging task that requires an agent to navigate to a goal indicated by an image in unfamiliar environments. Existing methods utilizing diverse scene memories suffer from inefficient exploration since they use all historical observations for decision-making without considering the goal-relevant fraction. To address this limitati

Gao Yu, Qiu Xuchong, Ye Zihan

Message hiding, a technique that conceals secret message bits within a cover image, aims to achieve an optimal balance among message capacity, recovery accuracy, and imperceptibility. While convolutional neural networks have notably improved message capacity and imperceptibility, achieving high recovery accuracy remains challenging. This challenge arises bec

Jianbin Zheng, Minghui Hu, Zhongyi Fan, Chaoyue Wang

Latent Consistency Model (LCM) extends the Consistency Model to the latent space and leverages the guided consistency distillation technique to achieve impressive performance in accelerating text-to-image synthesis. However, we observed that LCM struggles to generate images with both clarity and detailed intricacy. Consequently, we introduce Trajectory Consi

Maurizio Carbone, Vincent J. Peterhans, Alexander S. Ecker, Michael Wilczek

Small-scale turbulence can be comprehensively described in terms of velocity gradients, which makes them an appealing starting point for low-dimensional modeling. Typical models consist of stochastic equations based on closures for non-local pressure and viscous contributions. The fidelity of the resulting models depends on the accuracy of the underlying mod

Ramón Nartallo-Kaluarachchi, Malbor Asllani, Gustavo Deco, Morten L. Kringelbach

The structure of a complex network plays a crucial role in determining its dynamical properties. In this work, we show that the the degree to which a network is directed and hierarchically organised is closely associated with the degree to which its dynamics break detailed balance and produce entropy. We consider a range of dynamical processes and show how d

Filippo Riva, Elisabetta Rocca

In this paper we consider two diffuse interface models for tumor growth coupling a Cahn-Hilliard type equation for the tumor phase parameter to a reaction-diffusion type equation for the nutrient. The models are distinguished by the presence of two different coupling source terms. For such problems, we address the question of the limit, as the diffuse interf

Shangda Wu, Xu Tan, Zili Wang, Rui Wang

Traditional deep learning often overlooks bytes, the basic units of the digital world, where all forms of information and operations are encoded and manipulated in binary format. Inspired by the success of next token prediction in natural language processing, we introduce bGPT, a model with next byte prediction to simulate the digital world. bGPT matches spe

Luca Baracco, Olga Bernardi, Alessandra Nardi

The aim of the present paper is to establish a Bialy-Mironov type rigidity for centrally symmetric symplectic billiards. For a centrally symmetric $C^2$ strongly-convex domain $D$ with boundary $\partial D$, assume that the symplectic billiard map has a (simple) continuous invariant curve $\delta \subset \mathcal{P}$ of rotation number $1/4$ (winding once ar

J. M. Aldaz, H. Render

Let $P$ be a fixed homogeneous polynomial. We present a sharp condition on $P$ guaranteeing the existence of asymptotically larger bounds in Bombieri's inequality, so for every homogeneous polynomial $q_m$ of degree $m$ we have \begin{equation*} \left\Vert P q_{m}\right\Vert _{a}\geq C_{P} m^{l\left( P\right) /2}\left\Vert q_{m}\right\Vert _{a}, \end{equatio

E. García-Sánchez, D. H. Leung, M. A. Taylor, P. Tradacete

We study the free Banach lattice $FBL^{(p,\infty)}[E]$ with upper $p$-estimates generated by a Banach space $E$. Using a classical result of Pisier on factorization through $L^{p,\infty}(\mu)$ together with a finite dimensional reduction, it is shown that the spaces $\ell^{p,\infty}(n)$ witness the universal property of $FBL^{(p,\infty)}[E]$ isomorphically.

Lior Tenenbaum

Periodic approximations of quasicrystals are a powerful tool in analyzing spectra of Schr\"odinger operators arising from quasicrystals, given the known theory for periodic crystals. Namely, we seek periodic operators whose spectra approximate the spectrum of the limiting operator (of the quasicrystal). This naturally leads to study the convergence of the un

Hao Cheng, Erjia Xiao, Jindong Gu, Le Yang

Large Vision-Language Models (LVLMs) rely on vision encoders and Large Language Models (LLMs) to exhibit remarkable capabilities on various multi-modal tasks in the joint space of vision and language. However, typographic attacks, which disrupt Vision-Language Models (VLMs) such as Contrastive Language-Image Pretraining (CLIP), have also been expected to be

Jianqi Sheng, Dongkai Zhang, Lixiang Chen

There are two powerful arguments against the possibility of extending quantum mechanics, the violation of Bell inequalities and the Kochen-Specker theorem, but the connection between the two remains confused. Following the distinctive strategy proposed by Cabello [Phys. Rev. Lett. 127, 070401 (2021)], Bell inequalities can be violated by state-independent co

George Khujadze, David Gogichaishvili, George Chagelishvili

A novel turbulence control strategy for wall-bounded shear flow is proposed by Chagelishvili et al, 2014. The essence of this strategy involves continuously imposition of specially designed seed velocity perturbations with spanwise asymmetry near the flow wall. The configuration of this imposed velocity field, enhanced due to the shear flow non-normality, br

Peng-Ling Wu, Kit Ian Kou, Hongmin Cai, Zhaoyuan Yu

The low-rank quaternion matrix approximation has been successfully applied in many applications involving signal processing and color image processing. However, the cost of quaternion models for generating low-rank quaternion matrix approximation is sometimes considerable due to the computation of the quaternion singular value decomposition (QSVD), which lim

Taketo Tsujimoto, Yuki Yonemoto, Hiroki Shibata, Takuya Mieno

Two strings of the same length are said to Cartesian-tree match (CT-match) if their Cartesian-trees are isomorphic [Park et al., TCS 2020]. Cartesian-tree matching is a natural model that allows for capturing similarities of numerical sequences. Oizumi et al. [CPM 2022] showed that subsequence pattern matching under CT-matching model (CT-MSeq) can be solved

Chenghao Li, Lei Qi, Xin Geng

In industrial anomaly detection, model efficiency and mobile-friendliness become the primary concerns in real-world applications. Simultaneously, the impressive generalization capabilities of Segment Anything (SAM) have garnered broad academic attention, making it an ideal choice for localizing unseen anomalies and diverse real-world patterns. In this paper,

Xueying Jiang, Sheng Jin, Lewei Lu, Xiaoqin Zhang

Monocular 3D detection (M3D) aims for precise 3D object localization from a single-view image which usually involves labor-intensive annotation of 3D detection boxes. Weakly supervised M3D has recently been studied to obviate the 3D annotation process by leveraging many existing 2D annotations, but it often requires extra training data such as LiDAR point cl

Zhihang Liu, Chao Zheng

Quantum (Poincar\'e) recurrence theorem are known for closed quantum (classical) systems. Can recurrence happen in open systems? We provide the recurrence theorem for open quantum systems via non-Hermitian (NH) description. We find that PT symmetry and pseudo-Hermitian symmetry protect recurrence for NH open quantum systems and the recurrence fails with the

Pavlos Rath-Manakidis, Frederik Strothmann, Tobias Glasmachers, Laurenz Wiskott

Interpretation and visualization of the behavior of detection transformers tends to highlight the locations in the image that the model attends to, but it provides limited insight into the \emph{semantics} that the model is focusing on. This paper introduces an extension to detection transformers that constructs prototypical local features and uses them in o

Mikhail Cherkasskii, Ritwik Mondal, Levente Rózsa

Inertial effects in spin dynamics emerge on picosecond time scales, giving rise to nutational excitations at THz frequencies. Here, we describe a general framework for investigating the precessional and nutational excitations in any type of spin structure within linear spin-wave theory. We consider the particular cases of planar and conical spin spirals in d

Juan V. O. Pêgas, André G. S. Landulfo, George E. A. Matsas, Daniel A. T. Vanzella

We discuss the information loss issue for completely evaporating black holes in the context of a globally hyperbolic spacetime that maintains unchanged the entire semiclassical picture except for the "last evaporation breath," which pertains to full quantum gravity. Even though observers outside the black hole cannot access information that enters the horizo

Debasis Das, Xuanyao Fong

Spiking Neural Networks (SNNs) have emerged as a promising paradigm, offering event-driven and energy-efficient computation. In recent studies, various devices tailored for SNN synapses and neurons have been proposed, leveraging the unique characteristics of emerging non-volatile memory (eNVM) technologies. While substantial progress has been made in explori

Anton Alekseev, Florian Naef, Muze Ren

Drinfeld defined the Knizhinik--Zamolodchikov (KZ) associator $\Phi_{\rm KZ}$ by considering the regularized holonomy of the KZ connection along the {\em droit chemin} $[0,1]$. The KZ associator is a group-like element of the free associative algebra with two generators, and it satisfies the pentagon equation. In this paper, we consider paths on $\mathbb{C}\

Hao Shen, Rongchan Zhu, Xiangchan Zhu

This article revisits the problem of global well-posedness for the generalized parabolic Anderson model on $\mathbb{R}^+\times \mathbb{T}^2$ within the framework of paracontrolled calculus \cite{GIP15}. The model is given by the equation: \begin{equation*} (\partial_t-\Delta) u=F(u)\eta \end{equation*} where $\eta\in C^{-1-\kappa}$ with $1/6>\kappa>0$, and $

Masato Takahashi, Sei Ban, Weiyuan Li, Atsuhiko Ochi

A novel type of resistive plate chamber, based on diamond-like carbon (DLC) electrodes is under development for background identification in the MEG II experiment. The DLC-RPC is required to have a radiation hardness to mass irradiation since it is planned to be placed in a high-intensity and low-momentum muon beam. In this study, the aging test using a high

Liudmila Zavolokina, Kilian Sprenkamp, Zoya Katashinskaya, Daniel Gordon Jones

In today's digital age, characterized by rapid news consumption and increasing vulnerability to propaganda, fostering citizens' critical thinking is crucial for stable democracies. This paper introduces the design of ClarifAI, a novel automated propaganda detection tool designed to nudge readers towards more critical news consumption by activating the analyt

Sanjin Benić, Adrian Dumitru, Abhiram Kaushik, Leszek Motyka

Exclusive $C=+1$ scalar, axial-vector, and tensor quarkonium production in high-energy electron-proton scattering requires a $C$-odd $t$-channel exchange of a photon or a three gluon ladder. We derive the expressions for the corresponding amplitudes. The relative phase of the photon vs. three gluon exchange amplitudes is determined by the sign of the light-f

Stephanie Brandl, Oliver Eberle, Tiago Ribeiro, Anders Søgaard

Rationales in the form of manually annotated input spans usually serve as ground truth when evaluating explainability methods in NLP. They are, however, time-consuming and often biased by the annotation process. In this paper, we debate whether human gaze, in the form of webcam-based eye-tracking recordings, poses a valid alternative when evaluating importan

Jiansong Li, Yun Ling, Jiaxin Geng, Heping Wang

Given a sequence of Marcinkiewicz-Zygmund inequalities in $L_2$ on a compact space, Gr\"ochenig in \cite{G} discussed weighted least squares approximation and least squares quadrature. Inspired by this work, for all $1\le p\le\infty$, we develop weighted least $\ell_p$ approximation induced by a sequence of Marcinkiewicz-Zygmund inequalities in $L_p$ on a co

Xing-Xing Dong, Shu-Min Zhao, Jia-Peng Huo, Tong-Tong Wang

Charged lepton flavor violation (CLFV) represents a clear new physics (NP) signal beyond the standard model (SM). In this work, we investigate CLFV processes $l_j^-\rightarrow l_i^- \gamma$ utilizing mass insertion approximation(MIA) in the minimal supersymmetric extension of the SM with local B-L gauge symmetry (B-LSSM). The MIA method can provide a set of

Roja Hosseinzadeh, Tatjana Petek

Let $\mathcal{X}$ be a real or complex Banach space with $ \dim \mathcal{X}\geq 3$. We give a complete description of surjective mappings on $\mathcal{B(X)}$ that preserve the ascent of Jordan triple product of operators or, preserve the descent of Jordan triple product of operators.

Yue Liu, Wen He, Bingze Wu, Fengyuan Xuan

Second harmonic generation (SHG) in van der Waals (vdWs) materials has garnered significant attention due to its potential for integrated nonlinear optical and optoelectronic applications. Stacking faults in vdWs materials, a typical kind of planar defect, can introduce a new degree of freedom to modulate the crystal symmetry and resultant SHG response, howe

Angelo Caregnato-Neto, Luciano Cavalcante Siebert, Arkady Zgonnikov, Marcos Ricardo Omena de Albuquerque Maximo

One of the key issues in human-robot collaboration is the development of computational models that allow robots to predict and adapt to human behavior. Much progress has been achieved in developing such models, as well as control techniques that address the autonomy problems of motion planning and decision-making in robotics. However, the integration of comp

Markus Fulmek

In recent preprints, Cigler considered certain Hankel determinants of convoluted Catalan numbers and conjectured identities for these determinants. In this note, we shall give a bijective proof of Cigler's Conjecture by interpreting determinants as generating functions of nonintersecting lattice paths: this proof employs the reflection principle, the Lindstr

K. Mukherjee, T. Arnone Cardinale, S. M. Reimann

A repulsively interacting Bose-Einstein condensate on a ring is well known to show persistent currents. For attractive interactions, however, a bound state may form that renders the rotation classical. Here we show that in a multiply-connected confinement, the strong in-plane attraction of an {\it anti-dipolar }condensate can form stacks of ring-shaped dropl

Sen Lin, Huiyuan Li, Zhiguo Yang

In this paper, we present Gauss's law-preserving spectral methods and their efficient solution algorithms for curl-curl source and eigenvalue problems in two and three dimensions arising from Maxwell's equations. Arbitrary order $H(curl)$-conforming spectral basis functions in two and three dimensions are firstly proposed using compact combination of Legendr

Dingyang Wang, Francesco Fioranelli, Alexander Yarovoy

In this paper, the problem of formulating effective processing pipelines for indoor human tracking is investigated, with the usage of a Multiple Input Multiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radar. Specifically, two processing pipelines starting with detections on the Range-Azimuth (RA) maps and the Range-Doppler (RD) maps are formu

Rahul Gupta, Pardeep Kumar, Rina Kanamoto, M. Bhattacharya

Atomic superfluids formed using Bose-Einstein condensates (BECs) in a ring trap are currently being investigated in the context of superfluid hydrodynamics, quantum sensing and matter-wave interferometry. The characterization of the rotational properties of such superfluids is important, but can presently only be performed by using optical absorption imaging

Dingqiang Ye, Chao Fan, Jingzhe Ma, Xiaoming Liu

Gait recognition stands as one of the most pivotal remote identification technologies and progressively expands across research and industry communities. However, existing gait recognition methods heavily rely on task-specific upstream driven by supervised learning to provide explicit gait representations like silhouette sequences, which inevitably introduce

Marco Crialesi-Esposito, Guido Boffetta, Luca Brandt, Sergio Chibbaro

The formation of small droplets and bubbles in turbulent flows is a crucial process in geophysics and engineering, whose underlying physical mechanism remains a puzzle. In this letter, we address this problem by means of high-resolution numerical simulations, comparing a realistic multiphase configuration with a numerical experiment in which we attenuate the

Shamima Naznin, Dr. Manishankar Mondal

Coding is an integral aspect of programming. A programmer can automatically complete a code fragment after writing a few tokens, and the process of automatic completion is known as code completion. Several research studies on code completion have previously been conducted for method body completion and method parameter completion. However, this fundamental s

Alexander Black, Jing Shi, Yifei Fan, Tu Bui

We present VIXEN - a technique that succinctly summarizes in text the visual differences between a pair of images in order to highlight any content manipulation present. Our proposed network linearly maps image features in a pairwise manner, constructing a soft prompt for a pretrained large language model. We address the challenge of low volume of training d

Alberto Cavallo

We study in details how and when the radical $\sqrt[3]{a+b\sqrt p}$ with rational numbers $a,b$ and $p$ positive can be simplified, providing a complete answer to the problem; furthermore, a program that computes the result is also made available. The solution highlights an interesting connection with the cubic formula.

Qidan Zhu, Jing Li, Fei Yuan, Quan Gan

Changes in facial expression, head movement, body movement and gesture movement are remarkable cues in sign language recognition, and most of the current continuous sign language recognition(CSLR) research methods mainly focus on static images in video sequences at the frame-level feature extraction stage, while ignoring the dynamic changes in the images. In

M. Sumetsky

The behavior of electromagnetic waves in a medium modulated in time and space, largely investigated decades ago, has recently attracted renewed interest. Here, we solve an intriguing problem of this research: can light with an initial frequency $\omega_0$ be amplified in a realistic photonic circuit solely pumped by a traveling wave with a much lower frequen

Jiamin Luo, Jianing Zhao, Jingjing Wang, Guodong Zhou

Weakly-supervised Phrase Grounding (WPG) is an emerging task of inferring the fine-grained phrase-region matching, while merely leveraging the coarse-grained sentence-image pairs for training. However, existing studies on WPG largely ignore the implicit phrase-region matching relations, which are crucial for evaluating the capability of models in understandi

A. Pop, M. Petrovici

Based on the existing experimental data for A-A collisions starting from the AGS energies up to the LHC ones, various systematics related to strange hadrons and anti-hadrons are presented. The ratio between the average transverse momentum and the square root of the total particle multiplicity per unit rapidity and unit transverse overlap area decreases with

Takashi Imoto, Yuki Susa, Ryoji Miyazaki, Yuichiro Matsuzaki

Quantum computation is a promising emerging technology, and by utilizing the principles of quantum mechanics, it is expected to achieve faster computations than classical computers for specific problems. There are two distinct architectures for quantum computation: gate-based quantum computers and quantum annealing. In gate-based quantum computation, we impl

Tobias Dornheim, Tilo Döppner, Panagiotis Tolias, Maximilian Böhme

The study of matter at extreme densities and temperatures has emerged as a highly active frontier at the interface of plasma physics, material science and quantum chemistry with direct relevance for planetary modeling and inertial confinement fusion. A particular feature of such warm dense matter is the complex interplay of strong Coulomb interactions, quant

Mark Oosterloo, Inga Kamp, Wim van Westrenen

The abundances of volatile CHNOS have a profound effect on the interior structure and evolution of a planet. Therefore, it is key to investigate the behavior of the abundances of these elements in the solid phase in the earliest stages of planet formation. However, the processes in planet-forming disks that shape these abundances are highly coupled and nonlo

Wenxue Cui, Xingtao Wang, Xiaopeng Fan, Shaohui Liu

Existing image compressed sensing (CS) coding frameworks usually solve an inverse problem based on measurement coding and optimization-based image reconstruction, which still exist the following two challenges: 1) The widely used random sampling matrix, such as the Gaussian Random Matrix (GRM), usually leads to low measurement coding efficiency. 2) The optim

Jinhao Li, Changlong Wang, Yanru Zhang, Hao Wang

The battery energy storage system (BESS) has immense potential for enhancing grid reliability and security through its participation in the electricity market. BESS often seeks various revenue streams by taking part in multiple markets to unlock its full potential, but effective algorithms for joint-market participation under price uncertainties are insuffic

Sanjay M. Joshi

Confidence interval of mean is often used when quoting statistics. The same rigor is often missing when quoting percentiles and tolerance or percentile intervals. This article derives the expression for confidence in percentiles of a sample population. Confidence intervals of median is compared to those of mean for a few sample distributions. The concept of

Hao Feng, Wendi Wang, Shaokai Liu, Jiajun Deng

In this work, we present DeepEraser, an effective deep network for generic text removal. DeepEraser utilizes a recurrent architecture that erases the text in an image via iterative operations. Our idea comes from the process of erasing pencil script, where the text area designated for removal is subject to continuous monitoring and the text is attenuated pro

Mohammad Khalid Imam Rahmani

Various decision support systems are available that implement Data Mining and Data Warehousing techniques for diving into the sea of data for getting useful patterns of knowledge (pearls). Classification, regression, clustering, and many other algorithms are used to enhance the precision and accuracy of the decision process. So, there is scope for increasing

Andreea-Maria Oncescu, João F. Henriques, Andrew Zisserman, Samuel Albanie

Video databases from the internet are a valuable source of text-audio retrieval datasets. However, given that sound and vision streams represent different "views" of the data, treating visual descriptions as audio descriptions is far from optimal. Even if audio class labels are present, they commonly are not very detailed, making them unsuited for text-audio

Domenique Zipperling, Simeon Allmendinger, Lukas Struppek, Niklas Kühl

In the landscape of generative artificial intelligence, diffusion-based models present challenges for socio-technical systems in data requirements and privacy. Traditional approaches like federated learning distribute the learning process but strain individual clients, especially with constrained resources (e.g., edge devices). In response to these challenge

Hubert Kalf

The hitherto unknown author of a citation by Goethe in his History of Colours is identified as J. E. Montucla and the context of Montucla's quotation is discussed.

Hongbang Yuan, Pengfei Cao, Zhuoran Jin, Yubo Chen

Large Language Models (LLMs) have shown impressive capabilities but still suffer from the issue of hallucinations. A significant type of this issue is the false premise hallucination, which we define as the phenomenon when LLMs generate hallucinated text when confronted with false premise questions. In this paper, we perform a comprehensive analysis of the f

Matteo Gambella, Fabrizio Pittorino, Manuel Roveri

Neural Architecture Search (NAS) paves the way for the automatic definition of Neural Network (NN) architectures, attracting increasing research attention and offering solutions in various scenarios. This study introduces a novel NAS solution, called Flat Neural Architecture Search (FlatNAS), which explores the interplay between a novel figure of merit based

Jianyu Guan, Zongming Yin, Tianyi Zhang, Leihui Chen

In recent years, the recommendation content on e-commerce platforms has become increasingly rich -- a single user feed may contain multiple entities, such as selling products, short videos, and content posts. To deal with the multi-entity recommendation problem, an intuitive solution is to adopt the shared-network-based architecture for joint training. The i

Benedikt Schosser, Pedro Riba Mello, Miguel Quartin, Bjoern Malte Schaefer

Tensions between cosmological parameters derived through different channels can be a genuine signature of new physics that $\Lambda$CDM as the standard model is not able to reproduce, in particular in the missing consistency between parameter estimates from measurements the early and late Universe. Or, they could be caused by yet to be understood systematics

Corentin Coupry, Paul Richard, David Bigaud, Sylvain Noblecourt

In the Architecture, Engineering and Construction (AEC) sector, data extracted from building information modelling (BIM) can be used to create a digital twin (DT). The algorithms of a BIM-based DT can facilitate the retrieval of information, which can then be used to improve building operation and maintenance procedures. However, with the increased complexit

Kotomi Taniguchi, Jaime E Pineda, Paola Caselli, Tomomi Shimoikura

Streamers bring gas from outer regions to protostellar systems and could change the chemical composition around protostars and protoplanetary disks. We have carried out mapping observations of carbon-chain species (HC$_3$N, HC$_5$N, CCH, and CCS) in the 3mm and 7mm bands toward the streamer flowing to the Class 0 young stellar object (YSO) Per-emb-2 with the

Roman Cherniha, Vasyl' Davydovych

We consider the classical Holling-Tanner model extended on 1D space by introducing the diffusion term. Making a reasonable simplification, the diffusive Holling-Tanner system is studied by means of symmetry based methods. Lie and Q-conditional (nonclassical) symmetries are identified. The symmetries obtained are applied for finding a wide range of exact solu

Alexander Shabalin, Viacheslav Meshchaninov, Egor Chimbulatov, Vladislav Lapikov

This paper presents the Text Encoding Diffusion Model (TEncDM), a novel approach to diffusion modeling that operates in the space of pre-trained language model encodings. In contrast to traditionally used embeddings, encodings integrate contextual information. In our approach, we also employ a transformer-based decoder, specifically designed to incorporate c

Jonathon Riddell, Curt von Keyserlingk, Tomaž Prosen, Bruno Bertini

Having spectral correlations that, over small enough energy scales, are described by random matrix theory is regarded as the most general defining feature of quantum chaotic systems as it applies in the many-body setting and away from any semiclassical limit. Although this property is extremely difficult to prove analytically for generic many-body systems, a

Yanlin Zhou, Kai Tan, Xinyu Shen, Zheng He

Proteins are essential for life, and their structure determines their function. The protein secondary structure is formed by the folding of the protein primary structure, and the protein tertiary structure is formed by the bending and folding of the secondary structure. Therefore, the study of protein secondary structure is very helpful to the overall unders

Miriam Schwarze, Gerhard Hilgers, Hans Rabus

Previously reported nanodosimetric measurements of therapeutic-energy carbon ions penetrating simulated tissue have produced results that are incompatible with the predicted mean energy of the carbon ions in the nanodosimeter and previous experiments with lower energy monoenergetic beams. The purpose of this study is to explore the origin of these discrepanc

Céline Van Landeghem, Luca Berti, Vincent Chabannes, Christophe Prud'Homme

We studied numerically the dynamics of colliding rigid bodies in a Newtonian fluid. The finite element method is used to solve the fluid-body interaction and the fluid motion is described in the Arbitrary-Lagrangian-Eulerian framework. To model the interactions between bodies, we consider a repulsive collision-avoidance model, defined by R. Glowinski. The ma

Charles Bertucci, Pierre Louis Lions

We adapt the classical theory of local well-posedness of evolution problems to cases in which the nonlinearity can be accurately quantified by two different norms. For ordinary differential equations, we consider $\dot{x} = f(x,x)$ for a function $f: V\times E \to E$ where $E$ is a Banach space and $V \hookrightarrow E$ a normed vector space. This structure

Christos Koutlis, Symeon Papadopoulos

The recently developed and publicly available synthetic image generation methods and services make it possible to create extremely realistic imagery on demand, raising great risks for the integrity and safety of online information. State-of-the-art Synthetic Image Detection (SID) research has led to strong evidence on the advantages of feature extraction fro

Zitian Li, Wang Chi Cheung

Motivated by the cost heterogeneity in experimentation across different alternatives, we study the Best Arm Identification with Resource Constraints (BAIwRC) problem. The agent aims to identify the best arm under resource constraints, where resources are consumed for each arm pull. We make two novel contributions. We design and analyze the Successive Halving

Yinfeng Zhu

A word $w$ is called a reaching word of a subset $S$ of states in a deterministic finite automaton (DFA) if $S$ is the image of $Q$ under the action of $w$. A DFA is called completely reachable if every non-empty subset of the state set has a reaching word. A conjecture states that in every $n$-state completely reachable DFA, for every $k$-element subset of

Jader Martins Camboim de Sá, Marcos Da Silveira, Cédric Pruski

Live languages continuously evolve to integrate the cultural change of human societies. This evolution manifests through neologisms (new words) or \textbf{semantic changes} of words (new meaning to existing words). Understanding the meaning of words is vital for interpreting texts coming from different cultures (regionalism or slang), domains (e.g., technica

Konstantinos Dimopoulos

We briefly discuss cosmic inflation, which is the dominant paradigm for the generation of the large scale structure in the Universe and also for arranging for the initial conditions of the hot Big Bang. We then present quintessential inflation, which also accounts of the observed dark energy. We discuss how quintessential inflation can be successfully modell

Yiju Guo, Ganqu Cui, Lifan Yuan, Ning Ding

Alignment in artificial intelligence pursues the consistency between model responses and human preferences as well as values. In practice, the multifaceted nature of human preferences inadvertently introduces what is known as the "alignment tax" -a compromise where enhancements in alignment within one objective (e.g.,harmlessness) can diminish performance in

Pablo Cubillos, Julián López-Gómez, Andrea Tellini

In this paper we consider a superlinear one-dimensional elliptic boundary value problem that generalizes the one studied by Moore and Nehari in [43]. Specifically, we deal with piecewise-constant weight functions in front of the nonlinearity with an arbitrary number $\kappa\geq 1$ of vanishing regions. We study, from an analytic and numerical point of view,

Jianfeng Chen, Jize Xiong, Yixu Wang, Qi Xin

With the application of hematopoietic stem cell transplantation and new drugs, the progression-free survival rate and overall survival rate of multiple myeloma have been greatly improved, but it is still considered as a kind of disease that cannot be completely cured. Many patients have disease recurrence after complete remission, which is rooted in the pres

Gurpreet Singh, Jeewan C. Pandey

Using long-term X-ray observations, we present the short-term and long-term X-ray variability analysis of the ultra-fast rotating active star AB Dor. Flaring events are common in X-ray observations of AB Dor and occupy a substantial portion of the total observation time, averaging around 57$\pm$23\%. The flare-free X-ray light curves show rotational modulati

Gensheng Pei, Tao Chen, Xiruo Jiang, Huafeng Liu

Recently, the advancement of self-supervised learning techniques, like masked autoencoders (MAE), has greatly influenced visual representation learning for images and videos. Nevertheless, it is worth noting that the predominant approaches in existing masked image / video modeling rely excessively on resource-intensive vision transformers (ViTs) as the featu

Maria Elena Griseta, Janusz Wysoczański

We consider the $C^*$-algebra generated by finitely many annihilation operators acting on the weakly monotone Fock space, and we call it weakly monotone $C^*$-algebra. We give an abstract representation for this algebra, showing that it is isomorphic to a suitable quotient of a Cuntz-Krieger $C^*$-algebra $\mathcal{O}_A$ corresponding to a suitable matrix $A

Geraldo F. Oliveira, Ataberk Olgun, Abdullah Giray Yağlıkçı, F. Nisa Bostancı

Processing-using-DRAM (PUD) is a processing-in-memory (PIM) approach that uses a DRAM array's massive internal parallelism to execute very-wide data-parallel operations, in a single-instruction multiple-data (SIMD) fashion. However, DRAM rows' large and rigid granularity limit the effectiveness and applicability of PUD in three ways. First, since application

Shakib Daryanoosh, Geoff J. Pryde, Howard M. Wiseman, Sergei Slussarenko

Interferometric phase estimation is an essential tool for precise measurements of quantities such as displacement, velocity and material properties. The lower bound on measurement uncertainty achievable with classical resources is set by the shot-noise limit (SNL) that scales asymptotically as $1/\sqrt{N}$, where $N$ is the number of resources used. The expe

Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu

Multi-objective optimization problems can be found in many real-world applications, where the objectives often conflict each other and cannot be optimized by a single solution. In the past few decades, numerous methods have been proposed to find Pareto solutions that represent optimal trade-offs among the objectives for a given problem. However, these existi

Markus Linckelmann

We show that the sets of $d$-dimensional Latin hypercubes over a non-empty set $X$, with $d$ running over the positive integers, determine an operad which is isomorphic to a sub-operad of the endomorphism operad of $X$. We generalise this to categories with finite products, and then further to internal versions for certain Cartesian closed monoidal categorie

Gennaro Nolano, Moritz Blum, Basil Ell, Philipp Cimiano

In recent years, large language models have achieved state-of-the-art performance across various NLP tasks. However, investigations have shown that these models tend to rely on shortcut features, leading to inaccurate predictions and causing the models to be unreliable at generalization to out-of-distribution (OOD) samples. For instance, in the context of re

D. V. Dobrycheva, M. Yu. Vasylenko, I. V. Kulyk, Ya. V. Pavlenko

This study introduces an approach to detecting exocomet transits in the dataset of the Transiting Exoplanet Survey Satellite (TESS), specifically within its Sector 1. Given the limited number of exocomet transits detected in the observed light curves, creating a sufficient training sample for the machine learning method was challenging. We developed a unique

Binghui Xiao

This paper is aim to extend Kenneth R. Berg's findings on the maximal entropy theorem and the ergodicity of measure convolution to the case of surjective homomorphisms. We further explores dynamical systems under surjective homomorphism in detail, especially the variation of entropy. Let $G_{1} $ and $G_{2} $ be compact metrizable groups, and suppose that $G

Akila Pemasiri, Zi Huang, Fraser Williams, Ethan Goan

This paper addresses a critical preliminary step in radar signal processing: detecting the presence of a radar signal and robustly estimating its bandwidth. Existing methods which are largely statistical feature-based approaches face challenges in electronic warfare (EW) settings where prior information about signals is lacking. While alternate deep learning

Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Guo Qin

Deep models have demonstrated remarkable performance in time series forecasting. However, due to the partially-observed nature of real-world applications, solely focusing on the target of interest, so-called endogenous variables, is usually insufficient to guarantee accurate forecasting. Notably, a system is often recorded into multiple variables, where the

Yueqiao Jin, Vanessa Echeverria, Lixiang Yan, Linxuan Zhao

Multimodal Learning Analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across various learnin