December 2024 arXiv papers — page 133

Yubo Cui, Zhiheng Li, Jiaqiang Wang, Zheng Fang

Vision-based 3D occupancy prediction has become a popular research task due to its versatility and affordability. Nowadays, conventional methods usually project the image-based vision features to 3D space and learn the geometric information through the attention mechanism, enabling the 3D semantic occupancy prediction. However, these works usually face two m

Chris Scheulen

A measurement of Higgs boson production in association with a top quark pair in the bottom anti-bottom Higgs boson decay channel and leptonic final states is presented. The analysis uses $140\,\mathrm{fb}^{-1}$ of $13\,\mathrm{TeV}$ proton proton collision data collected by the ATLAS detector at the Large Hadron Collider. A particular focus is placed on the

Chiara Amorino, Charlotte Dion-Blanc, Arnaud Gloter, Sarah Lemler

We investigate the nonparametric estimation problem of the density $\pi$, representing the stationary distribution of a two-dimensional system $\left(Z_t\right)_{t \in[0, T]}=\left(X_t, \lambda_t\right)_{t \in[0, T]}$. In this system, $X$ is a Hawkes-diffusion process, and $\lambda$ denotes the stochastic intensity of the Hawkes process driving the jumps of

Shubham Kumar Nigam, Balaramamahanthi Deepak Patnaik, Shivam Mishra, Noel Shallum

The integration of artificial intelligence (AI) in legal judgment prediction (LJP) has the potential to transform the legal landscape, particularly in jurisdictions like India, where a significant backlog of cases burdens the legal system. This paper introduces NyayaAnumana, the largest and most diverse corpus of Indian legal cases compiled for LJP, encompas

Stéphane Vannitsem, Wansuo Duan

The predictability of a coupled system composed by a coupled reduced-order extratropical ocean-atmosphere model forced by a low-order 3-variable tropical recharge-discharge model, is explored with emphasis on the long term forecasting capabilities. Highly idealized ensemble forecasts are produced taking into account the uncertainties in the initial states of

Noura Zenbaa, Khrystyna O. Levchenko, Jaganandha Panda, Kristýna Davídková

We demonstrate a magnonic diode based on a bilayer structure of Yttrium Iron Garnet (YIG) and Cobalt Iron Boron (CoFeB). The bilayer exhibits pronounced non-reciprocal spin-wave propagation, enabled by dipolar coupling and the magnetic properties of the two layers. The YIG layer provides low damping and efficient spin-wave propagation, while the CoFeB layer

Zhentao Tan, Ben Xue, Jian Jia, Junhao Wang

This paper presents the \textbf{S}emantic-a\textbf{W}ar\textbf{E} spatial-t\textbf{E}mporal \textbf{T}okenizer (SweetTok), a novel video tokenizer to overcome the limitations in current video tokenization methods for compacted yet effective discretization. Unlike previous approaches that process flattened local visual patches via direct discretization or ada

Sijia Li, Xin Wang, Yuguang Chen, Tucker Jones

The electron density (${n_{\rm e}}$) of the interstellar medium (ISM) in star-forming galaxies is intimately linked to star formation and ionization condition. Using the high-resolution spectra obtained from the JWST NIRSpec micro shutter assembly (MSA) as part of the GLASS-JWST program, we have assembled the largest sample to date (34 galaxies) with individ

E. D. Dahlberg, I. González-Adalid Pemartín, E. Marinari, V. Martin-Mayor

The study of spin-glass dynamics, long considered the paradigmatic complex system, has reached important milestones. The availability of single crystals has allowed the experimental measurement of spin-glass coherence lengths of almost macroscopic dimensions, while the advent of special-purpose computers enables dynamical simulations that approach experiment

Rubén Mullor, Julio Mulero, Mario Trottini

In this paper we describe a general approach to optimal imperfect maintenance activities of a repairable equipment with independent components. Most of the existing works on optimal imperfect maintenance activities of a repairable equipment with independent components. In addition, it is assumed that all the components of the equipment share the same model a

Shiding Zhu, Wenhui Dong, Jun Song, Yingbo Wang

Recently, there has been growing interest in the capability of multimodal large language models (MLLMs) to process high-resolution images. A common approach currently involves dynamically cropping the original high-resolution image into smaller sub-images, which are then fed into a vision encoder that was pre-trained on lower-resolution images. However, this

Congyi Nai, Xi Chen, Shangshang Yang, Yuan Liang

Accurate weather forecasting is essential for socioeconomic activities. While data-driven forecasting demonstrates superior predictive capabilities over traditional Numerical Weather Prediction (NWP) with reduced computational demands, its deterministic nature and limited advantages over physics-based ensemble predictions restrict operational applications. W

Siyan Dong, Shuzhe Wang, Shaohui Liu, Lulu Cai

Visual localization aims to determine the camera pose of a query image relative to a database of posed images. In recent years, deep neural networks that directly regress camera poses have gained popularity due to their fast inference capabilities. However, existing methods struggle to either generalize well to new scenes or provide accurate camera pose esti

Georgios Akrivis, Stig Larsson

We consider the discretization of a class of nonlinear parabolic equations by discontinuous Galerkin time-stepping methods and establish a priori as well as conditional a posteriori error estimates. Our approach is motivated by the error analysis in [9] for Runge-Kutta methods for nonlinear parabolic equations; in analogy to [9], the proofs are based on maxi

Kaixin Ji, Lin Chen, Li-Ping Yang, Ling-Yan Hung

Following the construction in arXiv:2210.12127, we develop a symmetry-preserving renormalization group (RG) flow for 3D symmetric theories. These theories are expressed as boundary conditions of a symTFT, which in our case is a 3+1D Dijkgraaf-Witten topological theory in the bulk. The boundary is geometrically organized into tetrahedra and represented as a t

Marcin Kościelecki, Piotr Nieżurawski

We present a few charge distributions for which the application of Gauss' law in its integral form, as typically outlined in standard textbooks, results in a contradiction. We identify the root cause of such contradictions and put forward a solution to resolve them.

Yu-Ming Yang, Xiao-Jun Bi, Peng-Fei Yin

Cosmological simulations of fuzzy dark matter (FDM) are computationally expensive, and the resulting halos lack flexibility in parameter adjustments, such as virial mass, density profile, and global velocity. Previous studies have introduced a method for constructing FDM halos with predefined density profiles. In this study, we investigate the initial global

Peter Lowdon, Owe Philipsen

We summarise recent progress towards the non-perturbative determination of thermal spectral functions for pseudo-scalar mesons in QCD by exploiting constraints imposed by micro-causality at finite temperature. For temperatures not much above the vacuum particle mass, continuous contributions from scattering, Landau damping and collective excitations are foun

Ruizhe Yang, Zhongkai Yi, Ying Xu, Dazhi Yang

The growing penetration of renewable energy sources (RESs) in active distribution networks (ADNs) leads to complex and uncertain operation scenarios, resulting in significant deviations and risks for the ADN operation. In this study, a collaborative capacity planning of the distributed energy resources in an ADN is proposed to enhance the RES accommodation c

A. A. Araújo Filho, N. Heidari, Ali Övgün

This paper explores gravitational phenomena associated with a non-commutative black hole. Geodesic equations are derived, and a thin accretion disk is analyzed to model the black hole shadow image, considering an optically thin, radiating, and infalling gas. Retrolensing effects are examined to trace photon emission configurations, while gravitational lensin

Ronaldo B. Assunção, Olímpio H. Miyagaki, Rafaella F. S. Siqueira

In this paper, we consider a fractional p-Laplacian system of equations in the entire space RN with doubly critical singular nonlinearities involving a local critical Sobolev term together with a nonlocal Choquard critical term; the problem also includes a homogeneous singular Hardy term; moreover, all the nonlinearities involve singular critical weights. To

Ke Wang, Qiao Wang, Yue Li, Zhi Guan

As decentralized applications on permissionless blockchains are prevalent, more and more latency-sensitive usage scenarios emerged, where the lower the latency of sending and receiving messages, the better the chance of earning revenue. To reduce latency, we present Pioplat, a feasible, customizable, and low-cost latency reduction framework consisting of mul

Robin Kühlem, Daniel Otten, Daniel Ludwig, Anselm Hudde

Machine learning (ML) will likely play a large role in many processes in the future, also for insurance companies. However, ML models are at risk of being attacked and manipulated. In this work, the robustness of Gradient Boosted Decision Tree (GBDT) models and Deep Neural Networks (DNN) within an insurance context will be evaluated. Therefore, two GBDT mode

Priyal Garg, T. V. S. Sekhar

In this paper, we present a meshless hybrid method combining the Generalized Finite Difference (GFD) and Finite Difference based Radial Basis Function (RBF-FD) approaches to solve non-homogeneous partial differential equations (PDEs) involving both lower and higher order derivatives. The proposed method eliminates the need for mesh generation by leveraging t

Uma Sthanu, Gary Cutter PhD

Background: Multiple Sclerosis (MS), an autoimmune disease affecting millions worldwide, is characterized by its variable course, in which some patients will experience a more benign disease course and others a more active one, with the latter leading to permanent neural damage and disability. Methods: This study uses a Markov Chain model to demonstrate the

Frank A Campo

The characterization of the finite minimal automorphic posets of width three is still an open problem. Niederle has shown that this task can be reduced to the characterization of the nice sections of width three having a non-trivial tower of nice sections as retract. We solve this problem for a sub-class $\mathfrak{N}_2$ of the finite nice sections of width

Cass Alexandru, Vikraman Choudhury, Jurriaan Rot, Niels van der Weide

The paper "Sorting with Bialgebras and Distributive Laws" by Hinze et al. uses the framework of bialgebraic semantics to define sorting algorithms. From distributive laws between functors they construct pairs of sorting algorithms using both folds and unfolds. Pairs of sorting algorithms arising this way include insertion/selection sort and quick/tree sort.

Kuan Li, Cui Qun Chen, Lingyong Zeng, Longfu Li

This study describes the synthesis and characterization of Nb2TiW and Nb2TiMo medium entropy alloys (MEAs). The Nb2TiW and Nb2TiMo MEAs can be successfully synthesized by an arc melting method. Their structures and superconducting properties are investigated by detailed characterization of X ray diffraction (XRD), resistivity, magnetization, and specific hea

Andreas Komninos

This paper discusses the need to move away from an instrumental view of text composition AI assistants under direct control of the user, towards a more agentic approach that is based on a value rationale. Based on an analysis of moral dimensions of AI assistance in computer mediated communication, the paper proposes basic guidelines for designing the agent's

Alexandra Veledina, Matthieu Pélissier

Polarimetric images of accreting black holes encode important information about laws of strong gravity and relativistic motions of matter. Recent advancements in instrumentation enabled such studies in two objects: supermassive black holes M87* and Sagittarius A*. Light coming from these sources is produced by synchrotron mechanism whose polarization is dire

Mónica Canabal-Carbia, Irene Estévez, Emilio González-Arnay, Ivan Montes-Gonzalez

We propose an imaging method to enhance and reveal structures within samples by using a polarization-based filter. This filter removes the isotropic content while amplifying the anisotropic component of depolarization. Whereas isotropic depolarization leads to a complete loss of polarimetric information, the anisotropic one is connected with intrinsic charac

Zirui Shang, Yubo Zhu, Hongxi Li, Shuo Yang

Video summarization aims to eliminate visual redundancy while retaining key parts of video to construct concise and comprehensive synopses. Most existing methods use discriminative models to predict the importance scores of video frames. However, these methods are susceptible to annotation inconsistency caused by the inherent subjectivity of different annota

Alon Levkovitch, Julian Salazar, Soroosh Mariooryad, RJ Skerry-Ryan

We present ZeroBAS, a neural method to synthesize binaural audio from monaural audio recordings and positional information without training on any binaural data. To our knowledge, this is the first published zero-shot neural approach to mono-to-binaural audio synthesis. Specifically, we show that a parameter-free geometric time warping and amplitude scaling

Yangxuan Zhou, Sha Zhao, Jiquan Wang, Haiteng Jiang

Sleep staging is crucial for assessing sleep quality and diagnosing related disorders. Recent deep learning models for automatic sleep staging using polysomnography often suffer from poor generalization to new subjects because they are trained and tested on the same labeled datasets, overlooking individual differences. To tackle this issue, we propose a nove

Maria Vasilyeva, Golo A. Wimmer, Ben S. Southworth

We consider anisotropic heat flow with extreme anisotropy, as arises in magnetized plasmas for fusion applications. Such problems pose significant challenges in both obtaining an accurate approximation as well in the construction of an efficient solver. In both cases, the underlying difficulty is in forming an accurate approximation of temperature fields tha

Quy Thuong Lê, Hoang Long Nguyen

In this paper, we give an explicit formula of the Igusa local zeta function of a Thom-Sebastiani type sum of two separated-variable Newton non-critical polynomials. Data for the description are available on their Newton polyhedra.

Sakil Ahamed, Debanjit Mondal

In this article, we prove that the nonlinear Kawahara equation on the periodic domain \(\mathbb{T}\) (the unit circle in the plane) is globally approximately controllable in \(H^s(\mathbb{T})\) for \(s \in \mathbb{N}\), at any time \(T > 0\), using a two-dimensional control force. The proof is based on the Agrachev-Sarychev approach in geometric control theo

Simon Schneider, Alexander Bakhtin, Xiaozhou Li, Jacopo Soldani

Architecture recovery tools help software engineers obtain an overview of the structure of their software systems during all phases of the software development life cycle. This is especially important for microservice applications because they consist of multiple interacting microservices, which makes it more challenging to oversee the architecture. Various

Bent Ørsted, Jorge A. Vargas

For a semisimple Lie group $G$ satisfying the equal rank condition, the most basic family of unitary irreducible representations is the Discrete Series found by Harish-Chandra. In this paper, we continue our study of the branching laws for Discrete Series when restricted to a subgroup $H$ of the same type by use of integral and differential operators in comb

Maximilian B. Kiss, Ander Biguri, Zakhar Shumaylov, Ferdia Sherry

Computed tomography (CT) is a widely used non-invasive diagnostic method in various fields, and recent advances in deep learning have led to significant progress in CT image reconstruction. However, the lack of large-scale, open-access datasets has hindered the comparison of different types of learned methods. To address this gap, we use the 2DeteCT dataset,

Nickolay S. Martynenko, Grigory I. Rubtsov, Petr S. Satunin, Andrey K. Sharofeev

Extensive air showers (EAS), produced by cosmic rays in the atmosphere, serve as probes of particle interactions, providing access to energies and kinematical regimes beyond the reach of laboratory experiments. Measurements from multiple cosmic-ray detectors indicate a significant, yet unexplained, discrepancy between the observed muon content in EAS and tha

A. Musiał, M. Wasiluk, M. Gawełczyk, J. P. Reithmaier

We demonstrate that optical excitation of InAs quantum dots (QDs) embedded directly in an InP matrix can be mediated via states in a quaternary compound constituting an InP/InGaAlAs bottom distributed Bragg reflector (DBR) and native defects in the InP matrix. It does not only change the carrier relaxation in the structure but could also lead to the imbalanc

Sultan Alrashed

We present SmolTulu-1.7b-Instruct, referenced in this report as SmolTulu-DPO-1130, an instruction-tuned language model that adapts AllenAI's Tulu 3 post-training pipeline to enhance Huggingface's SmolLM2-1.7B base model. Through comprehensive empirical analysis using a 135M parameter model, we demonstrate that the relationship between learning rate and batch

Wenzheng Zhang, Fahira Afzal Maken, Tin Lai, Fabio Ramos

Grasping is essential in robotic manipulation, yet challenging due to object and gripper diversity and real-world complexities. Traditional analytic approaches often have long optimization times, while data-driven methods struggle with unseen objects. This paper formulates the problem as a rigid shape matching between gripper and object, which optimizes with

Mengqi Lei, Haochen Wu, Xinhua Lv, Xin Wang

Medical image segmentation plays an important role in clinical decision making, treatment planning, and disease tracking. However, it still faces two major challenges. On the one hand, there is often a ``soft boundary'' between foreground and background in medical images, with poor illumination and low contrast further reducing the distinguishability of fore

Yushan Han, Hui Zhang, Honglei Zhang, Jing Wang

Current collaborative perception methods often rely on fully annotated datasets, which can be expensive to obtain in practical situations. To reduce annotation costs, some works adopt sparsely supervised learning techniques and generate pseudo labels for the missing instances. However, these methods fail to achieve an optimal confidence threshold that harmon

Hiroki Nishizawa, Keitaro Tanaka, Asuka Hirata, Shugo Yamaguchi

Automatically generating realistic musical performance motion can greatly enhance digital media production, often involving collaboration between professionals and musicians. However, capturing the intricate body, hand, and finger movements required for accurate musical performances is challenging. Existing methods often fall short due to the complex mapping

Mridu Prabal Goswami

We consider an economic environment where a seller wants to sell an indivisible unit of good to a buyer. We show that revenue from any strategy-proof and individually rational mechanism defined on closed intervals of rich single crossing domains considered in \citep{Goswami1}, can be approximated by the revenue from a sequence of strategy-proof and individua

Sinan Du, Guosheng Zhang, Keyao Wang, Yuanrui Wang

Parameter-efficient transfer learning (PETL) has become a promising paradigm for adapting large-scale vision foundation models to downstream tasks. Typical methods primarily leverage the intrinsic low rank property to make decomposition, learning task-specific weights while compressing parameter size. However, such approaches predominantly manipulate within

Xiaobai Ning, Henri Jaffrès, Weisheng Zhao, Aurélien Manchon

The conversion between spin and orbital currents is at the origin of the orbital torque and its Onsager reciprocal, the orbital pumping. Here, we propose a phenomenological model to describe the orbital torque in magnetic bilayers composed of an orbital source (i.e., a light metal such as Ti, Ru, CuOx...) and a spin-orbit coupled magnet (i.e., typically Ni,

Ivan Saetchnikov, Elina Tcherniavskaia, Andreas Ostendorf, Anton Saetchnikov

Accurate measurement of light wavelength is critical for applications in spectroscopy, optical communication, and semiconductor manufacturing, ensuring precision and consistency of sensing, high-speed data transmission and device production. Emerging reconstructive wavemeters synergize physical systems capable for pseudo-random wavelength dependent pattern f

Aaron D. C. Angel, John Rafael M. Antalan, John Loureynz F. Gamurot, Richard P. Tagle

A graph $G$ with $p$ vertices and $q$ edges is said to be edge-graceful if its edges can be labeled from $1$ through $q$, in such a way that the labels induced on the vertices by adding over the labels of incident edges modulo $p$ are distinct. A known result under this topic is Lo's Theorem, which states that if a graph $G$ with $p$ vertices and $q$ edges i

Shuang Liu, Xian Zhong Zheng, Valentino Gonzalez, Xiaohu Yang

The process of galaxy cluster formation likely leaves an imprint on the properties of its individual member galaxies. Understanding this process is essential for uncovering the evolutionary connections between galaxies and cosmic structures. Here we study a sample of ten protoclusters at z~2-3 in different dynamical states that we estimate based on spectrosc

Naoki Matsubara, Rikizo Yano, Kazushige Saigusa, Koshi Takenaka

The appearance of broken time-reversal symmetry (TRS) in superconducting states is an intriguing issue in solid-state physics because of the incompatibility of the spontaneous magnetic field and the Meissner effect. We identify broken TRS in Pd-doped CaAgP (CaAg$_{0.9}$Pd$_{0.1}$P) by tunneling spectroscopy through the magnetic field response of conductance

Timo Vilkas

We consider the following combinatorial two-player game: On the random tree arising from a branching process, each round one player (Breaker) deletes an edge and by that removes the descendant and all its progeny, while the other (Maker) fixates an edge to permanently secure it from deletion. Breaker has won once the tree's root is contained in a finite comp

F. M. Rica, R. Barrena, J. A. Henríquez, G. Vázquez

We present new orbital solutions for 15 binaries, which were astrometrically measured during 2010-2013. We observe the binary systems using the FastCam ``lucky-imaging'' camera, installed at the 1.5-m Carlos S\'anchez Telescope (CST) at the Observatorio del Teide, Tenerife (Spain). We present first orbital solutions for four binaries and revise orbits for ot

Sen Yang, Xiaofeng Li

We establish a high-precision composite model for a piezoelectric fast steering mirror (PFSM) using a Hammerstein structure. A novel asymmetric Bouc-Wen model is proposed to describe the nonlinear rate-independent hysteresis, while a dynamic model is derived to represent the linear rate-dependent component. By analyzing the physical process from the displace

Kangjie Chen, BingQuan Dai, Minghan Qin, Dongbin Zhang

3D semantic field learning is crucial for applications like autonomous navigation, AR/VR, and robotics, where accurate comprehension of 3D scenes from limited viewpoints is essential. Existing methods struggle under sparse view conditions, relying on inefficient per-scene multi-view optimizations, which are impractical for many real-world tasks. To address t

Chen-Xu Han, Zhao-Long Wang, Yi Yan

In the $N=1$ superspace, AdS$_4$ supersymmetry is realized as the non-linear super coordinate transformations. The fermionic coordinates form a faithful non-linear representation of supersymmetry on their own. By introducing an auxiliary scalar coordinate, this representation is reformulated as a 5-dimensional linear representation, i.e., the superspinor rep

Nikolay Banar, Ehsan Lotfi, Walter Daelemans

Zero-shot evaluation of information retrieval (IR) models is often performed using BEIR; a large and heterogeneous benchmark composed of multiple datasets, covering different retrieval tasks across various domains. Although BEIR has become a standard benchmark for the zero-shot setup, its exclusively English content reduces its utility for underrepresented l

Boying Zhou, Chen Shen, Kexuan Tang

This paper proposes a novel method for identifying Th\'evenin equivalent parameters (TEP) in power system, based on the statistical characteristics of the system's stochastic response. The method leverages stochastic fluctuation data under steady-state grid conditions and applies sliding window techniques to compute sensitivity parameters between voltage mag

A. Lumbreras-Calle, J. A. Fernández-Ontiveros, R. Infante-Sainz, M. Akhlaghi

A large, faint nebula was unexpectedly discovered near M31 using narrowband [O III] images. Its apparent size and the lack of a clear counterpart at other wavelengths make it unique and challenging to explain. We aim to determine whether the nebula is extragalactic or located within the Milky Way. This will enable us to constrain its physical properties and

Jisheng Chu, Wenrui Li, Xingtao Wang, Kanglin Ning

The common occurrence of occlusion-induced incompleteness in point clouds has made point cloud completion (PCC) a highly-concerned task in the field of geometric processing. Existing PCC methods typically produce complete point clouds from partial point clouds in a coarse-to-fine paradigm, with the coarse stage generating entire shapes and the fine stage imp

V. A. Antonov, I. R. Khairulin, M. Yu. Emelin, M. M. Popova

It is shown that under optimal conditions, the generation of the 3rd, 5th, 7th, and 9th harmonics of the short-wave, ultraviolet or vacuum ultraviolet, laser field by helium atoms is mainly due to transitions between bound states, and the maximum energy of the harmonics is achieved under conditions of their resonant multiphoton excitation. In this case, the

Mengfan Li, Xuanhua Shi, Chenqi Qiao, Teng Zhang

Knowledge hypergraphs generalize knowledge graphs using hyperedges to connect multiple entities and depict complicated relations. Existing methods either transform hyperedges into an easier-to-handle set of binary relations or view hyperedges as isolated and ignore their adjacencies. Both approaches have information loss and may potentially lead to the creat

Ching-Chun Chang, Isao Echizen

The exchange of messages has always carried with it the timeless challenge of secrecy. From whispers in shadows to the enigmatic notes written in the margins of history, humanity has long sought ways to convey thoughts that remain imperceptible to all but the chosen few. The challenge of subliminal communication has been addressed in various forms of stegano

Teemu Hankala, Miika Hannula, Yasir Mahmood, Arne Meier

We study consistent query answering via different graph representations. First, we introduce solution-conflict hypergraphs in which nodes represent facts and edges represent either conflicts or query solutions. Considering a monotonic query and a set of antimonotonic constraints, we present an explicit algorithm for counting the number of repairs satisfying

Alexej Perevertov

In this work we propose a simple phenomenological model for magnetization curves of stressed samples. The effect of stress is introduced by scaling the arctangent function argument (magnetic field) proportionally to stress. The magnetization curve is modelled by one or two arctangent functions. Despite of its simplicity, the model gives a very good agreement

Rodrigo Martínez-Peña, Juan-Pablo Ortega

Quantum reservoir computing is an emergent field in which quantum dynamical systems are exploited for temporal information processing. In previous work, it was found a feature that makes a quantum reservoir valuable: contractive dynamics of the quantum reservoir channel toward input-dependent fixed points. These results are enhanced in this paper by finding

Jan Krejčí, Oliver Kost, Ondřej Straka, Yuxuan Xia

Multi-object tracking algorithms are deployed in various applications, each with different performance requirements. For example, track switches pose significant challenges for offline scene understanding, as they hinder the accuracy of data interpretation. Conversely, in online surveillance applications, their impact is often minimal. This disparity undersc

Eduard E. Bahingayi, Nemanja Stefan Perović, Le-Nam Tran

Reconfigurable intelligent surfaces (RISs) have huge potential to improve spectral and energy efficiency in future wireless systems at a minimal cost. However, early prototype results indicate that deploying hundreds or thousands of reflective elements is necessary for significant performance gains. Motivated by this, our study focuses on \emph{large-scale }

Aleksandar Janjoš, Miloš S. Kurilić

Topologies $\tau , \sigma \in \mathop{{\mathrm{Top}}}\nolimits _X$ are bijectively related, in notation $\tau \sim \sigma$, if there are continuous bijections $f: (X, \tau )\rightarrow (X, \sigma )$ and $g: (X, \sigma)\rightarrow (X, \tau)$. Defining $[\tau ]_{\cong}=\{ \sigma \in \mathop{{\mathrm{Top}}}\nolimits _X : \sigma \cong \tau\}$ and $[\tau ]_{\sim

Francesco Gucci, Eduardo B. Molinero, Mattia Russo, Pablo San-Jose

Information processing currently reaches speeds as high as 800 GHz. However, the underlying transistor technology is quickly approaching its fundamental limits and further progress requires a disruptive approach. One such path is to manipulate quantum properties of solids, such as the valley degree of freedom, with ultrashort controlled lightwaves. Here we e

Haotong Zhang

We carry out a series of experiments to test large language models' multi-hop reasoning ability from three aspects: selecting and combining external knowledge, dealing with non-sequential reasoning tasks and generalising to data samples with larger numbers of hops. We test the GPT-3.5 model on four reasoning benchmarks with Chain-of-Thought prompting (and it

Xingyu Peng, Junran Wu, Ruomei Liu, Ke Xu

Traditional methods for detecting rumors on social media primarily focus on analyzing textual content, often struggling to capture the complexity of online interactions. Recent research has shifted towards leveraging graph neural networks to model the hierarchical conversation structure that emerges during rumor propagation. However, these methods tend to ov

Bingzhi Shen, Lufan Chang, Siqi Chen, Shuxiang Guo

In medical imaging, precise annotation of lesions or organs is often required. However, 3D volumetric images typically consist of hundreds or thousands of slices, making the annotation process extremely time-consuming and laborious. Recently, the Segment Anything Model (SAM) has drawn widespread attention due to its remarkable zero-shot generalization capabi

Gargi Bakshi, Rushikesh K. Joshi

Dynamic changes in processes necessitate the notion of state equivalence between the old and new workflows. In several cases, the history of the workflow to be migrated provides sufficient context for a meaningful migration. In this paper, we present an algorithm to find the equivalence mapping for states from the old workflow to the new one using a trail-ba

Gergely Szabó, Zsófia Molnár, András Horváth

Temporal forward-tracking has been the dominant approach for multi-object segmentation and tracking (MOTS). However, a novel time-symmetric tracking methodology has recently been introduced for the detection, segmentation, and tracking of budding yeast cells in pre-recorded samples. Although this architecture has demonstrated a unique perspective on stable a

Sowmya Cheripally

This paper presents a new voice conversion model capable of transforming both speaking and singing voices. It addresses key challenges in current systems, such as conveying emotions, managing pronunciation and accent changes, and reproducing non-verbal sounds. One of the model's standout features is its ability to perform accent conversion on hybrid voice sa

Eugenia Celada

We present results from SMEFiT3.0, a global SMEFT fit of Higgs, top quark, and diboson production data from the LHC. Our updated analysis includes recent inclusive and differential measurements from the LHC Run II, together with the exact implementation of electroweak precision observables (EWPOs) from LEP and SLD. We then analyse the impact of HL-LHC measur

Matthias Kohn, Marcel Hoffmann, Ansgar Scherp

Message Passing Neural Networks (MPNNs) have demonstrated remarkable success in node classification on homophilic graphs. It has been shown that they do not solely rely on homophily but on neighborhood distributions of nodes, i.e., consistency of the neighborhood label distribution within the same class. MLP-based models do not use message passing, \eg Graph

Roderic Lakes

Chiral, directionally isotropic gyroid lattices are observed to exhibit nonclassical thermal effects incompatible with an asymmetric ("odd") second rank conductivity tensor but consistent with a third rank tensor property that provides a curl term. The lattices are passive materials so no driving torques are needed to obtain transverse flow. A method for det

Manuel Costanzo, Enzo Rucci, Carlos García-Sánchez, Marcelo Naiouf

The high-performance computing (HPC) landscape is undergoing rapid transformation, with an increasing emphasis on energy-efficient and heterogeneous computing environments. This comprehensive study extends our previous research on SYCL's performance portability by evaluating its effectiveness across a broader spectrum of computing architectures, including CP

Shijian Wang, Linxin Song, Jieyu Zhang, Ryotaro Shimizu

Current multimodal language model (MLM) training approaches overlook the influence of instruction templates. Previous research deals with this problem by leveraging hand-crafted or model-generated templates, failing to investigate the scaling effect of instruction templates on MLM training. In this work, we propose a programmatic instruction template generat

Jiayu Liu, Zhenya Huang, Chaokun Wang, Xunpeng Huang

Owing to the capability of in-context learning, large language models (LLMs) have shown impressive performance across diverse mathematical reasoning benchmarks. However, we find that few-shot demonstrations can sometimes bring negative performance and their effectiveness on LLMs' reasoning abilities remains unreliable. To this end, in this paper, we aim to t

Rangavajjala Sankara Bharadwaj, Jhansi Mallela, Sai Harshitha Aluru, Chiranjeevi Yarra

Automatic syllable stress detection is a crucial component in Computer-Assisted Language Learning (CALL) systems for language learners. Current stress detection models are typically trained on clean speech, which may not be robust in real-world scenarios where background noise is prevalent. To address this, speech enhancement (SE) models, designed to enhance

Tian Ye, Yan-Zhi Wang, Xiang-You Chen, Qing-Hu Chen

Although the superradiant phase transition (SRPT) is prohibited in the paradigmatic quantum Rabi model due to the no-go theorem caused by the $\mathbf{A}^2$ term, we demonstrate two distinct types of SRPTs emerging from the normal phase in the anisotropic quantum Rabi model. A discontinuous phase transition between the two types of superradiant phases also e

Dharmaraj Ramachandran, Aditya Dubey, Subrahmanyam S. G. Mantha, Radhika Vathsan

We introduce an entanglement measure, the Modified Bloch Norm (MBN), for finite-dimensional bipartite mixed states, based on the improved Bloch matrix criteria. MBN is demonstrated to be effective in analyzing the dynamics of bound entanglement--a valuable resource for quantum protocols where free entanglement may not be available. Through examples, we illus

Virgilio Gómez-Rubio, Jesús Lagos, Francisco Palmí-Perales

Finding players with similar profiles is an important problem in sports such as football. Scouting for new players requires a wealth of information about the available players so that similar profiles to that of a target player can be identified. However, information about the position of the players in the field is seldom used. For this reason, a novel appr

Andrii Sokolov, Xutong Wu, Conor Power, Mike Asker

Confining electrons or holes in quantum dots formed in the channel of industry-standard fully depleted silicon-on-insulator CMOS structures is a promising approach to scalable qubit architectures. In this article, we present our results on a calibrated model of a commercial nanostructure using the simulation tool Quantum TCAD, along with our experimental ver

Yining Pang, Chenghan Li

With the proliferation of the Internet and smart devices, IoT technology has seen significant advancements and has become an integral component of smart homes, urban security, smart logistics, and other sectors. IoT facilitates real-time monitoring of critical production indicators, enabling businesses to detect potential quality issues, anticipate equipment

Quoc-Bao Nguyen-Le, Tuan-Hy Le, Anh-Triet Do

In the burgeoning field of medical imaging, precise computation of 3D volume holds a significant importance for subsequent qualitative analysis of 3D reconstructed objects. Combining multivariate calculus, marching cube algorithm, and binary indexed tree data structure, we developed an algorithm for efficient computation of intrinsic volume of any volumetric

Yizhou Dang, Jiahui Zhang, Yuting Liu, Enneng Yang

By generating new yet effective data, data augmentation has become a promising method to mitigate the data sparsity problem in sequential recommendation. Existing works focus on augmenting the original data but rarely explore the issue of imbalanced relevance and diversity for augmented data, leading to semantic drift problems or limited performance improvem

Claudine von Hallern, Ricarda Mißfeldt, Andreas Rößler

For the approximation of solutions for stochastic partial differential equations, numerical methods that obtain a high order of convergence and at the same time involve reasonable computational cost are of particular interest. We therefore propose a new numerical method of exponential stochastic Runge-Kutta type that allows for convergence with a temporal or

I. L. Buchbinder, S. A. Fedoruk, A. P. Isaev, V. A. Krykhtin

The paper is dedicated to the blessed memory of Professor Vladislav Gavrilovich Bagrov, an outstanding Russian scientist in the area of theoretical and mathematical physics. He had a great influence on the formation of the scientific interests dozens of scientists in Tomsk and Russia as a whole. Two of the authors of this paper (I.L.B and V.A.K) are to one d

Thomas Krieguer, Yanko Todorov

We present a microscopic quantum theory for nonlinear optical phenomena in semiconductor quantum well heterostructures operating in the regime of ultra-strong light matter coupling regime. This work extends the Power-Zienau-Wooley (PZW) formulation of quantum electrodynamics to account for nonlinear interactions based on a fully fermionic approach, without r

Samad Noeiaghdam

This study investigates the existence and uniqueness of solutions to Volterra integral equations with discontinuous kernels in both linear and nonlinear cases. The problem is two-dimensional, and the collocation method is employed to analyze the equations. The research aims to provide a comprehensive understanding of the solution properties of these integral

Ruihuai Liang, Bo Yang, Pengyu Chen, Xuelin Cao

Optimization is crucial for MEC networks to function efficiently and reliably, most of which are NP-hard and lack efficient approximation algorithms. This leads to a paucity of optimal solution, constraining the effectiveness of conventional deep learning approaches. Most existing learning-based methods necessitate extensive optimal data and fail to exploit

Simone Blumer

This paper examines (restricted) Koszul Lie algebras, a class of positively graded Lie algebras with a quadratic presentation and specific cohomological properties. The study employs HNN-extensions as a key tool for decomposing and analysing these algebras. Building on a previous work on Koszul Lie algebras ("Kurosh theorem for certain Koszul Lie algebras",

Kawsar Haghshenas, Mona Hashemi

Deep Learning Training (DLT) is a growing workload in shared GPU/CPU clusters due to its high computational cost and increasing number of jobs. This contributes to significant energy consumption in GPU clusters, further exacerbated by GPU under-utilization, as shown in production cluster logs. Addressing this challenge requires workload scheduling and resour