May 2023 arXiv papers — page 158

Radek Suchánek

We investigate the landscape of generalized geometries that can be derived from Monge-Amp\`ere structures. Instead of following the approaches of Banos, Roubtsov, Kosmann-Schwarzbach, and others, we take a new path inspired by the results of Hu, Moraru, and Svoboda. We construct a large family of new generalized almost geometries derived from non-degenerate

Gerardo M. Escolano, Antonio M. Peralta, Armando R. Villena

We establish some Lie--Trotter formulae for unital complex Jordan--Banach algebras, showing that for each couple of elements $a,b$ in a unital complex Jordan--Banach algebra $\mathfrak{A}$ the identities $$ \lim_{n\to \infty} \left(e^{\frac{a}{n}}\circ e^{\frac{b}{n}} \right)^{n} = e^{a+b},\ \lim_{n\to \infty} \left(U_{e^{\frac{a}{n}}} \left( e^{\frac{b}{n}}

Jose Alberto Hernandez, Pedro Reviriego

At present (year 2023), approximately 2,500 satellites are currently orbiting the Earth. This number is expected to reach 50,000 satellites (that is, 20 times growth) for the next 10 years, thanks to the recent advances concerning launching satellites at low cost and with high probability of success. In this sense, it is expected that next years the world wi

Chenxiao Liu, Shuai Lu, Weizhu Chen, Daxin Jiang

Code execution is a fundamental aspect of programming language semantics that reflects the exact behavior of the code. However, most pre-trained models for code intelligence ignore the execution trace and only rely on source code and syntactic structures. In this paper, we investigate how well pre-trained models can understand and perform code execution. We

Xiaoxi Guo, Sujoy Sikdar, Lirong Xia, Yongzhi Cao

For the assignment problem where multiple indivisible items are allocated to a group of agents given their ordinal preferences, we design randomized mechanisms that satisfy first-choice maximality (FCM), i.e., maximizing the number of agents assigned their first choices, together with Pareto efficiency (PE). Our mechanisms also provide guarantees of ex-ante

Nikita M. Egorov, Marina V. Sysoeva, Vladimir I. Ponomarenko, Ilya V. Sysoev

Constructing electronic models of neurons has several applications including reproducing dynamics of biological neurons and their networks and neuroprosthetics. In the brain, most neurons themselves are in a non-oscillatory mode, and brain rhythms arise due to their collective dynamics. In this case, very small ensembles of neurons can act as rhythm generato

Samuel Pawel, Rachel Heyard, Charlotte Micheloud, Leonhard Held

In several large-scale replication projects, statistically non-significant results in both the original and the replication study have been interpreted as a "replication success". Here we discuss the logical problems with this approach: Non-significance in both studies does not ensure that the studies provide evidence for the absence of an effect and "replic

Hailu Bikila Yadeta

In this paper, we give a new characterization of the split-complex numbers as a vector space $LC_2= \{xI+yE : x,y \in \mathbb{R},\, E^2=I \}$ of operators, where $I$ is the identity operator and $E$ is the unit shift operator that are operating on the space $\mathbb{P}_2$ of all real-valued $2$-periodic functions. We also characterize the field of the comple

A. M. Badalian

\date{\today} Within the diquark-antidiquark model the masses of the $0^{++}, cc\bar c\bar c$ resonances are calculated, using the expansion of the four-quark wave function in the set of the hyperspherical functions. The interaction is defined via a universal pair-wise potential, which does not contain fitting parameters. The resulting masses $M_4(nS)$ are s

Will Hide

Let $X$ be a finite-area non-compact hyperbolic surface. We study the spectrum of the Laplacian on random covering surfaces of X and on random unitary bundles over X. We show that there is a constant $c > 0$ such that, with probability tending to 1 as $n \to \infty$, a uniformly random degree-$n$ Riemannian covering surface $X_n$ of $X$ has no Laplacian eige

Dongyufu Zhang, Guy Drijkoningen

A field experiment was conducted in Zuidbroek, the Netherlands to compare the performance of a DAS and horizontal-geophone system for shear-wave (SV) reflection surveying. The data were subjected to processing for reflection imaging, including conversion of the geophone data to strain-rate data, to enable such a comparison on migrated-section level. Our find

Leonhard Hennig, Philippe Thomas, Sebastian Möller

Relation extraction (RE) is a fundamental task in information extraction, whose extension to multilingual settings has been hindered by the lack of supervised resources comparable in size to large English datasets such as TACRED (Zhang et al., 2017). To address this gap, we introduce the MultiTACRED dataset, covering 12 typologically diverse languages from 9

Mojtaba Eshghie, Wolfgang Ahrendt, Cyrille Artho, Thomas Troels Hildebrandt

Smart contracts manage blockchain assets and embody business processes. However, mainstream smart contract programming languages such as Solidity lack explicit notions of roles, action dependencies, and time. Instead, these concepts are implemented in program code. This makes it very hard to design and analyze smart contracts. We argue that DCR graphs are a

Gaetano Fiore

We propose a preliminary analytical procedure in 4 steps (based on an improved fully relativistic plane hydrodynamic model) to tailor the initial density of a cold diluted plasma to the laser pulse profile so as to control wave-breaking (WB) of the plasma wave and maximize the acceleration of small bunches of electrons self-injected by the first WB at the de

Hyeok Hwang, JaeKyung Choi, Eunseong Kim

Adaptive tomography has been widely investigated to achieve faster state tomography processing of quantum systems. Infidelity of the nearly pure states in a quantum information process generally scales as O(1/sqrt(N) ), which requires a large number of statistical ensembles in comparison to the infidelity scaling of O(1/N) for mixed states. One previous repo

Matteo Carlesso, Mauro Paternostro

We argue that, in the quest for the translation of fundamental research into actual quantum technologies, two avenues that have - so far - only partly explored should be pursued vigorously. On first entails that the study of energetics at the fundamental quantum level holds the promises for the design of a generation of more energy-efficient quantum devices.

Marwan Mostafa, Davood Babazadeh, Christian Becker

Integrating the gas and district heating with the electrical grid in a multi-energy grid has been shown to provide flexibility and prevent bottlenecks in the operation of electrical distribution grids. This integration assumes a top-down grid planning approach and a perfect knowledge of consumer behaviour. In reality, consumers decides whether to adopt a hea

Dong Huu Quoc Tran, Hoang-Anh Phan, Hieu Dang Van, Tan Van Duong

Autonomous exploration is a new technology in the field of robotics that has found widespread application due to its objective to help robots independently localize, scan maps, and navigate any terrain without human control. Up to present, the sampling-based exploration strategies have been the most effective for aerial and ground vehicles equipped with dept

Moaad Khamlich, Giovanni Stabile, Gianluigi Rozza, László Környei

This article presents an innovative approach for developing an efficient reduced-order model to study the dispersion of urban air pollutants. The need for real-time air quality monitoring has become increasingly important, given the rise in pollutant emissions due to urbanization and its adverse effects on human health. The proposed methodology involves solv

Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin Vechev

Training certifiably robust neural networks remains a notoriously hard problem. On one side, adversarial training optimizes under-approximations of the worst-case loss, which leads to insufficient regularization for certification, while on the other, sound certified training methods optimize loose over-approximations, leading to over-regularization and poor

Anchun Gui, Han Xiao

To fully leverage the advantages of large-scale pre-trained language models (PLMs) on downstream tasks, it has become a ubiquitous adaptation paradigm to fine-tune the entire parameters of PLMs. However, this paradigm poses issues of inefficient updating and resource over-consuming for fine-tuning in data-scarce and resource-limited scenarios, because of the

Grzegorz Chrupała

Human language is firstly spoken and only secondarily written. Text, however, is a very convenient and efficient representation of language, and modern civilization has made it ubiquitous. Thus the field of NLP has overwhelmingly focused on processing written rather than spoken language. Work on spoken language, on the other hand, has been siloed off within

Emma de Oña Wilhelmi, Rubén López-Coto, Yang Su

Evidence of efficient acceleration of cosmic rays in massive young stellar objects has been recently reported. Among these massive protostars, S255 NIRS 3 for which extreme flaring events associated with radio jets have been detected, is one of the best objects to test this hypothesis. We search for gamma-ray emission associated with this object in Fermi-LAT

Antoine Gérardin, Willem E. A. Verplanke, Gen Wang, Zoltan Fodor

In this paper we present a first ab-initio calculation of the $\pi^0$, $\eta$ and $\eta^{\prime}$ transition form factors performed with physical light-quark masses. We provide a complete parametrization of the form factors that includes both single and double-virtual kinematics. Our results are compared with experimental measurements of the form factors in

Vaibhav Shekhar, Punit Sharma

The three-step alternating iteration scheme for finding an iterative solution of a singular (non-singular) linear systems in a faster way was introduced by Nandi {\it et al.} [Numer. Algorithms; 84 (2) (2020) 457-483], recently. The authors then provided its convergence criteria for a class of matrix splitting called proper G-weak regular splittings of type

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We report the first search for $\bar\Lambda$--$\Lambda$ oscillations in the decay $J/\psi \to p K^- \bar{\Lambda} + c.c.$ by analyzing $1.31\times10^9$ $J/\psi$ events accumulated with the BESIII detector at the BEPCII collider. The $J/\psi$ events are produced using $e^+e^-$ collisions at a center of mass energy $\sqrt{s}= 3.097$~GeV. No evidence for hypero

Zeju Li, Linya Cheng, Chunhong Zhang, Xinning Zhu

The field of education has undergone a significant transformation due to the rapid advancements in Artificial Intelligence (AI). Among the various AI technologies, Knowledge Graphs (KGs) using Natural Language Processing (NLP) have emerged as powerful visualization tools for integrating multifaceted information. In the context of university education, the av

Alban Puech, Gorazd Dimitrov, Claudia D'Ambrosio

As the share of variable renewable energy sources increases in the electricity mix, new solutions are needed to build a flexible and reliable grid. Energy arbitrage with battery storage systems supports renewable energy integration into the grid by shifting demand and increasing the overall utilization of power production systems. In this paper, we propose a

Maciej Korpalski, Grzegorz Plebanek

We consider a separable compact line $K$ and its extension $L$ consisting of $K$ and a countable number of isolated points. The main object of study is the existence of a bounded extension operator $E: C(K)\to C(L)$. We show that if such an operator exists then there is one for which $\|E\|$ is an odd natural number. We prove that if the topological weight o

V. Cuciti, R. Cassano, M. Sereno, G. Brunetti

Many galaxy clusters show diffuse cluster-scale emission in the form of radio halos, showing that magnetic fields and relativistic electrons are mixed in with the intra-cluster medium (ICM). There is general agreement that the origin of radio halos is connected to turbulence, generated during cluster mergers. Statistical studies of large samples of galaxy cl

Daniil Musatov, Georgii Potapov

This is the full version of a paper submitted to the Computability in Europe (CiE 2023) conference, with all proofs omitted there. In 2012 P. D. Azar and S. Micali introduced a new model of interactive proofs, called "Rational Interactive Proofs". In this model the prover is neither honest nor malicious, but rational in terms of maximizing his expected rewar

Priyo Shankar Pal, Arnab Pal, Hyunggyu Park, Jae Sung Lee

Resetting is a strategy for boosting the speed of a target-searching process. Since its introduction over a decade ago, most studies have been carried out under the assumption that resetting takes place instantaneously. However, due to its irreversible nature, resetting processes incur a thermodynamic cost, which becomes infinite in case of instantaneous res

Sanghwan Kim, Farhad Nooralahzadeh, Morteza Rohanian, Koji Fujimoto

Recent transformer-based models have made significant strides in generating radiology reports from chest X-ray images. However, a prominent challenge remains: these models often lack prior knowledge, resulting in the generation of synthetic reports that mistakenly reference non-existent prior exams. This discrepancy can be attributed to a knowledge gap betwe

Xuan Son Nguyen, Shuo Yang

Matrix manifolds, such as manifolds of Symmetric Positive Definite (SPD) matrices and Grassmann manifolds, appear in many applications. Recently, by applying the theory of gyrogroups and gyrovector spaces that is a powerful framework for studying hyperbolic geometry, some works have attempted to build principled generalizations of Euclidean neural networks o

Yi Song, Hao Xu, Kai-Kit Wong, Giuseppe Caire

This paper considers the distributed information bottleneck (D-IB) problem for a primitive Gaussian diamond channel with two relays and MIMO Rayleigh fading. The channel state is an independent and identically distributed (i.i.d.) process known at the relays but unknown to the destination. The relays are oblivious, i.e., they are unaware of the codebook and

Xinping Gui, Buyang Li, Jilu Wang

A class of stochastic Besov spaces $B^p L^2(\Omega;\dot H^\alpha(\mathcal{O}))$, $1\le p\le\infty$ and $\alpha\in[-2,2]$, is introduced to characterize the regularity of the noise in the semilinear stochastic heat equation \begin{equation*} {\rm d} u -\Delta u {\rm d} t =f(u) {\rm d} t + {\rm d} W(t) , \end{equation*} under the following conditions for some

Hongqiu Wu, Yongxiang Liu, Hanwen Shi, Hai Zhao

Beyond the success story of adversarial training (AT) in the recent text domain on top of pre-trained language models (PLMs), our empirical study showcases the inconsistent gains from AT on some tasks, e.g. commonsense reasoning, named entity recognition. This paper investigates AT from the perspective of the contextualized language representation outputted

Yi Bin, Mengqun Han, Wenhao Shi, Lei Wang

Existing MWP solvers employ sequence or binary tree to present the solution expression and decode it from given problem description. However, such structures fail to handle the variants that can be derived via mathematical manipulation, e.g., $(a_1+a_2) * a_3$ and $a_1 * a_3+a_2 * a_3$ can both be possible valid solutions for a same problem but formulated as

Zhibo Wang, He Wang, Shuaifan Jin, Wenwen Zhang

Face recognition service providers protect face privacy by extracting compact and discriminative facial features (representations) from images, and storing the facial features for real-time recognition. However, such features can still be exploited to recover the appearance of the original face by building a reconstruction network. Although several privacy-p

Stefano Battilotti, Filippo Cacace, Massimiliano d'Angelo

In this paper we carry out a stability analysis of a distributed consensus algorithm in presence of link failures. The algorithm combines a new broadcast version of a Push-Sum algorithm, specifically designed for handling link failures, with a new recursive consensus filter. The analysis is based on the properties of random Laplacian matrices and random sub-

Batmend Horoldagva, Chunlei Xu

Recently, Gutman defined a new vertex-degree-based graph invariant, named the Sombor index $SO$ of a graph $G$, and is defined by $$SO(G)=\sum_{uv\in E(G)}\sqrt{d_G(u)^2+d_G(v)^2},$$ where $d_G(v)$ is the degree of the vertex $v$ of $G$. In this paper, we obtain the sharp lower and upper bounds on $SO(G)$ of a connected graph, and characterize graphs for whi

Alexandra Ivanova, Denis Antipov, Benjamin Doerr

Evolutionary algorithms are known to be robust to noise in the evaluation of the fitness. In particular, larger offspring population sizes often lead to strong robustness. We analyze to what extent the $(1+(\lambda,\lambda))$ genetic algorithm is robust to noise. This algorithm also works with larger offspring population sizes, but an intermediate selection

Shintaro Akamine

Isometric class of minimal surfaces in the Euclidean 3-space $\mathbb{R}^3$ has the rigidity: if two simply connected minimal surfaces are isometric, then one of them is congruent to a surface in the specific one-parameter family, called the associated family, of the other. On the other hand, the situation for surfaces with Lorentzian metrics is different. I

Rong-Gen Cai, Zong-Kuan Guo, Bin Hu, Chang Liu

The space-based laser interferometers, LISA, Taiji and TianQin, are targeting to observe milliHz gravitational waves (GWs) in the 2030s. The joint observations from multiple space-based detectors yield significant advantages. In this work, we recap the studies and investigations for the joint space-based GW detector networks to highlight: 1) the high precisi

Shuyuan Zhang, Shu Shan, Shizhen Zhao

We study how to reduce the reconfiguration time in hybrid optical-electrical Datacenter Networks (DCNs). With a layer of Optical Circuit Switches (OCSes), hybrid optical-electrical DCNs can reconfigure its logical topologies to better match the on-going traffic patterns, but the reconfiguration time may directly affect the benefits of reconfigurability. The

Fabian Binkert, Judit Szulágyi, Til Birnstiel

The motion of solid particles embedded in gaseous protoplanetary disks is influenced by turbulent fluctuations. Consequently, the dynamics of moderately to weakly coupled solids can be distinctly different from the dynamics of the gas. Additionally, gravitational perturbations from an embedded planet can further impact the dynamics of solids. In this work, w

James Holdeman, Evgeniy Kartaev, John Foss, Marat Ktalkherman

The flow field studied was eight strongly impinging, radially injected jets, into a non-swirling mainstream flow in a cylindrical duct. Our previous paper (Heat Mass Transf. (2020) 56:2285-2302), showed that asymmetry in the solution is very likely to be an indication of the flow unsteadiness. Also, if the flow is asymmetric, even a time dependent flow solve

Zhiyuan Zhang, Deli Chen, Hao Zhou, Fandong Meng

Pre-trained Language Models (PLMs) may be poisonous with backdoors or bias injected by the suspicious attacker during the fine-tuning process. A core challenge of purifying potentially poisonous PLMs is precisely finding poisonous dimensions. To settle this issue, we propose the Fine-purifying approach, which utilizes the diffusion theory to study the dynami

Enrico Reggiani, Renzo Andri, Lukas Cavigelli

Modern DNN workloads increasingly rely on activation functions consisting of computationally complex operations. This poses a challenge to current accelerators optimized for convolutions and matrix-matrix multiplications. This work presents Flex-SFU, a lightweight hardware accelerator for activation functions implementing non-uniform piecewise interpolation

Federico Fallucca, Roberto Pignatelli

In this work we classify all smooth surfaces with geometric genus equal to three and an action of a group G isomorphic to (Z/2)^k such that the quotient is a plane. We find 11 families. We compute the canonical map of all of them, finding in particular a family of surfaces with canonical map of degree 16 that we could not find in the literature. We discuss t

Dominique Désérable, Rolf Hoffmann, Franciszek Seredyński

"Dominos" are special entities consisting of a hard dimer-like kernel surrounded by a soft hull and governed by local interactions. "Soft hull" and "hard kernel" mean that the hulls can overlap while the kernel acts under a repulsive potential. Unlike the dimer problem in statistical physics, which lists the number of all possible configurations for a given

Sai Sathiesh Rajan, Ezekiel Soremekun, Yves Le Traon, Sudipta Chattopadhyay

Ensuring that all classes of objects are detected with equal accuracy is essential in AI systems. For instance, being unable to identify any one class of objects could have fatal consequences in autonomous driving systems. Hence, ensuring the reliability of image recognition systems is crucial. This work addresses how to validate group fairness in image reco

Chengqing Li, Sheng Liu

Joint encryption and compression is an ideal solution for protecting security and privacy of image data in a real scenario, e.g. storing them on an existing cloud-based service like Facebook. Recently, some block-wise encryption-then-compression (ETC) schemes compatible with JPEG were proposed to provide a reasonably high level of security without compromisi

Jeong Hun Yeo, Minsu Kim, Yong Man Ro

Visual Speech Recognition (VSR) is a task to predict a sentence or word from lip movements. Some works have been recently presented which use audio signals to supplement visual information. However, existing methods utilize only limited information such as phoneme-level features and soft labels of Automatic Speech Recognition (ASR) networks. In this paper, w

Min Hun Lee, Yi Jing Choy

Explainable artificial intelligence (AI) techniques are increasingly being explored to provide insights into why AI and machine learning (ML) models provide a certain outcome in various applications. However, there has been limited exploration of explainable AI techniques on time-series data, especially in the healthcare context. In this paper, we describe a

Yilei Shi, Richard Bamler, Yuanyuan Wang, Xiao Xiang Zhu

Multi-baseline interferometric synthetic aperture radar (InSAR) techniques are effective approaches for retrieving the 3-D information of urban areas. In order to obtain a plausible reconstruction, it is necessary to use large-stack interferograms. Hence, these methods are commonly not appropriate for large-scale 3-D urban mapping using TanDEM-X data where o

Miroslav Mitev, Arsenia Chorti, Gerhard Fettweis

The massive deployment of low-end wireless Internet of things (IoT) devices opens the challenge of finding de-centralized and lightweight alternatives for secret key distribution. A possible solution, coming from the physical layer, is the secret key generation (SKG) from channel state information (CSI) during the channel's coherence time. This work acknowle

Kota Kawamoto, Masato Uchida

Assigning labels to instances is crucial for supervised machine learning. In this paper, we proposed a novel annotation method called Q&A labeling, which involves a question generator that asks questions about the labels of the instances to be assigned, and an annotator who answers the questions and assigns the corresponding labels to the instances. We deriv

Jinjie Zhu, Marius E. Yamakou

The study in [Phys. Rev. Lett. 117, 014102 (2016)] discovered a novel type of chimera state known as coherence-resonance chimera (CRC), which combines the effects of coherence resonance (CR) and the spatial property of classical chimeras. In this Letter, we present yet another novel form of chimera, which we refer to as self-induced-stochastic-resonance brea

Gözden Torun, Anastasia Romashkina, Tetsuo Kishi, Yves Bellouard

We report the formation of arbitrary photoconductive patterns made of tellurium (Te) nanocrystals by exposing a tellurite (TeO2-based) glass to femtosecond laser pulses. During this process, Te/TeO2-glass nanocomposite interfaces with photoconductive properties form on the tellurite glass substrate. We show that these laser-written patterns have a highly rep

Paul Barajas

In this paper we establish relations among the module of high-order derivations of the Hasse-Schmidt algebra and the module of high-order derivations of the base ring.

Peng Xia, Di Xu, Ming Hu, Lie Ju

Long-tailed multi-label visual recognition (LTML) task is a highly challenging task due to the label co-occurrence and imbalanced data distribution. In this work, we propose a unified framework for LTML, namely prompt tuning with class-specific embedding loss (LMPT), capturing the semantic feature interactions between categories by combining text and image m

Rizwan Jahangir, Dharm Veer

We characterize Cohen-Macaulay posets of dimension two; they are precisely the shellable and strongly connected posets of dimension two. We also give a combinatorial description of these posets. Using the fact that co-comparability graph of a 2-dimensional poset is a permutation graph, we characterize Cohen-Macaulay permutation graphs.

Jiafeng Zhang, Xuejing Pu

Smart home device detection is a critical aspect of human-computer interaction. However, detecting targets in indoor environments can be challenging due to interference from ambient light and background noise. In this paper, we present a new model called FSA-YOLOv5, which addresses the limitations of traditional convolutional neural networks by introducing t

Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos

In this paper, we propose MPC (Modular Prompted Chatbot), a new approach for creating high-quality conversational agents without the need for fine-tuning. Our method utilizes pre-trained large language models (LLMs) as individual modules for long-term consistency and flexibility, by using techniques such as few-shot prompting, chain-of-thought (CoT), and ext

Teemu Niskanen, Tuomo Sipola, Olli Väänänen

Artificial intelligence is more ubiquitous in multiple domains. Smartphones, social media platforms, search engines, and autonomous vehicles are just a few examples of applications that utilize artificial intelligence technologies to enhance their performance. This study carries out a scoping review of the current state-of-the-art artificial intelligence tec

Makoto Takeuchi, Haruo Saito

A method for analyzing sampling jitter in audio equipment is proposed. The method is based on the time-domain analysis where the time fluctuations of zero-crossing points in recorded sinusoidal waves are employed to characterize jitter. This method enables the separate evaluation of jitter in an audio player from those in audio recorders when the same playba

Yunxin Li, Baotian Hu, Xinyu Chen, Yuxin Ding

Conditional inference on joint textual and visual clues is a multi-modal reasoning task that textual clues provide prior permutation or external knowledge, which are complementary with visual content and pivotal to deducing the correct option. Previous methods utilizing pretrained vision-language models (VLMs) have achieved impressive performances, yet they

Yuexia Luna Lin, Matteo Pezzulla, Pedro M. Reis

The smallest flying insects often have bristled wings resembling feathers or combs. We combined experiments and three-dimensional numerical simulations to investigate the trade-off between wing weight and drag generation. In experiments of bristled strips, a reduced physical model of the bristled wing, we found that the elasto-viscous number indicates when r

A. Skopenkov, O. Styrt

A general position map $f:K\to M$ of a $k$-dimensional simplicial complex to a $2k$-dimensional manifold (for $k=1$, of a graph to a surface) is a $\mathbb Z_2$-embedding if $|f\sigma \cap f\tau|$ is even for any non-adjacent $k$-faces $\sigma,\tau$. We present criteria for $\mathbb Z_2$-embeddability of certain $k$-dimensional complex (for $k=1$, of any gra

Chun Wang, Yang Huang, Yutao Zhou, Huawei Zhang

We construct a catalogue of stellar masses and ages for 696,680 red giant branch (RGB) stars, 180,436 primary red clump (RC) stars, and 120,907 secondary RC stars selected from the LAMOST\,DR8. The RGBs, primary RCs, and secondary RCs are identified with the large frequency spacing ($\Delta \nu$) and period spacing ($\Delta P$), estimated from the LAMOST spe

Mohammad R. Garousi

The least action principle indicates that for the open spacetime manifolds, there are data on the boundary. Recently, it has been proposed that the data for the effective actions at order $\alpha'$ are the values of the massless fields and their first derivatives. These data should be respected by the T-duality transformations at order $\alpha'$. Moreover, t

Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang

Reinforcement learning (RL) is inspired by the way human infants and animals learn from the environment. The setting is somewhat idealized because, in actual tasks, other agents in the environment have their own goals and behave adaptively to the ego agent. To thrive in those environments, the agent needs to influence other agents so their actions become mor

Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi, Massoud Pedram

Transfer learning has become a popular task adaptation method in the era of foundation models. However, many foundation models require large storage and computing resources, which makes off-the-shelf deployment impractical. Post-training compression techniques such as pruning and quantization can help lower deployment costs. Unfortunately, the resulting perf

Giulio Codogni, Víctor González-Alonso, Sara Torelli

In this note we prove that the Torelli, Prym and Spin-Torelli morphisms, as well as covering maps between moduli stacks of projective curves can not be deformed. The proofs use properties of the Fujita decomposition of the Hodge bundle of families of curves.

Jiajun Wei, Hongjian Zhan, Xiao Tu, Yue Lu

Employing a dictionary can efficiently rectify the deviation between the visual prediction and the ground truth in scene text recognition methods. However, the independence of the dictionary on the visual features may lead to incorrect rectification of accurate visual predictions. In this paper, we propose a new dictionary language model leveraging the Scene

Anton A. Peshkov, Elena Jordan, Markus Kromrey, Karan K. Mehta

Photoexcitation of trapped ions by Hermite-Gaussian (HG) modes from guided beam structures is proposed and investigated theoretically. In particular, simple analytical expressions for the Rabi frequencies of induced atomic transitions are derived that depend both on the parameters of HG beams and on the geometry of an experiment. By using these general expre

Junru Lu, Gabriele Pergola, Lin Gui, Yulan He

We propose a simple yet effective strategy to incorporate event knowledge extracted from event trigger annotations via posterior regularization to improve the event reasoning capability of mainstream question-answering (QA) models for event-centric QA. In particular, we define event-related knowledge constraints based on the event trigger annotations in the

Rahul Karmakar, Jaydeb Chakrabarti

Structure formation in non-equilibrium steady state conditions is poorly understood. Non-equilibrium steady state can be achieved in a system by maintaining temperature gradient. A class of cross-linked micro-gel particles, poly-N-isopropylacrylamide (PNIPAM, are reported to increase in size due to adsorption of water as temperature decreases. Here we study

Aoxiang Jiang, Wei Liu, Baojiu Li, Cristian Barrera-Hinojosa

In this study, we explore the potential of utilizing the four Minkowski functionals, which can fully describe the morphological properties of the large-scale structures, as a robust tool for investigating the modified gravity, particularly on non-linear and quasi-linear scales. With the assistance of the N-body simulation, we employ the Minkowski functionals

Asad Mahmood, Thang X. Vu, Symeon Chatzinotas, Björn Ottersten

Unmanned aerial vehicles (UAV) have emerged as a practical solution that provides on-demand services to users in areas where the terrestrial network is non-existent or temporarily unavailable, e.g., due to natural disasters or network congestion. In general, UAVs' user-serving capacity is typically constrained by their limited battery life and the finite com

Guo Lin, Yongfeng Zhang

This study investigates the feasibility of developing an Artificial General Recommender (AGR), facilitated by recent advancements in Large Language Models (LLMs). An AGR comprises both conversationality and universality to engage in natural dialogues and generate recommendations across various domains. We propose ten fundamental principles that an AGR should

Xinmin Qiu, Congying Han, Zicheng Zhang, Bonan Li

Blind face restoration (BFR) is important while challenging. Prior works prefer to exploit GAN-based frameworks to tackle this task due to the balance of quality and efficiency. However, these methods suffer from poor stability and adaptability to long-tail distribution, failing to simultaneously retain source identity and restore detail. We propose DiffBFR

Ross Greer, Akshay Gopalkrishnan, Jacob Landgren, Lulua Rakla

One of the most important tasks for ensuring safe autonomous driving systems is accurately detecting road traffic lights and accurately determining how they impact the driver's actions. In various real-world driving situations, a scene may have numerous traffic lights with varying levels of relevance to the driver, and thus, distinguishing and detecting the

Yongqiang Pan, Yue Sun, Nan Zhou, Xiaolei Yi

Studying the upper critical field ($\mu_0$$H$$_{\rm{c2}}$) and its anisotropy of superconductors is of great importance because it can provide an unusual insight into the pair-breaking mechanism. Since Fe$_{1+y}$Te$_{1-x}$Se$_x$ exhibits the high $\mu_0$$H$$_{\rm{c2}}$ and small anisotropic superconductivity, it has attracted considerable attention. However,

François Dufour, Tomás Prieto-Rumeau

We consider a nonzero-sum N-player Markov game on an abstract measurable state space with compact metric action spaces. The payoff functions are bounded Carath\'eodory functions and the transitions of the system are assumed to have a density function satisfying some continuity conditions. The optimality criterion of the players is given by a total expected p

Yanna Jiang, Baihe Ma, Xu Wang, Ping Yu

The demand for intelligent industries and smart services based on big data is rising rapidly with the increasing digitization and intelligence of the modern world. This survey comprehensively reviews Blockchained Federated Learning (BlockFL) that joins the benefits of both Blockchain and Federated Learning to provide a secure and efficient solution for the d

Xin Liu, Xuhong Guo, Qi Liao

Transport coefficients, such as the diffusion coefficient and shear viscosity, are important material properties that are calculated in computer simulations. In this study, the criterion for the best estimation of viscosity, as an example of transport coefficients, is determined by using the Green-Kubo formula without any artificial models. The related algor

Ruochen Zheng, Siyu Li

We present a method for deadlock-free and collision-free navigation in a multi-robot system with nonholonomic robots. The problem is solved by quadratic programming and is applicable to most wheeled mobile robots with linear kinematic constraints. We introduce masked velocity and Masked Cooperative Collision Avoidance (MCCA) algorithm to encourage a fully de

Izabela Kowalska-Leszczynska, Marzena A. Kubiak, Maciej Bzowski

The Interstellar Neutral Helium (ISN He) is an important source of information on the physical state of the Local Interstellar Medium. Radiation pressure acting on the neutral helium atoms in the heliosphere has always been neglected, its effect has been considered insignificant compared to gravitational force. The most advanced numerical models of ISN He ta

Iridanos Loulas, Grigorios P. Zouros, Evangelos Almpanis, Kosmas L. Tsakmakidis

In this study we investigate the directional scattering of terahertz radiation by dielectric cylinders, focusing on the enhancement of directionality using incident radiation of complex-frequency. We explore the optimization of the second Kerker condition, which corresponds to backward scattering. At first, by carefully tailoring the electric and magnetic po

Hande Dong, Jiayi Lin, Yanlin Wang, Yichong Leng

Pre-trained code models have emerged as the state-of-the-art paradigm for code search tasks. The paradigm involves pre-training the model on search-irrelevant tasks such as masked language modeling, followed by the fine-tuning stage, which focuses on the search-relevant task. The typical fine-tuning method is to employ a dual-encoder architecture to encode s

Wenyuan Yang, Yuguo Yin, Gongxi Zhu, Hanlin Gu

Federated learning (FL) allows multiple parties to cooperatively learn a federated model without sharing private data with each other. The need of protecting such federated models from being plagiarized or misused, therefore, motivates us to propose a provable secure model ownership verification scheme using zero-knowledge proof, named FedZKP. It is shown th

Ross Greer, Samveed Desai, Lulua Rakla, Akshay Gopalkrishnan

It is critical for vehicles to prevent any collisions with pedestrians. Current methods for pedestrian collision prevention focus on integrating visual pedestrian detectors with Automatic Emergency Braking (AEB) systems which can trigger warnings and apply brakes as a pedestrian enters a vehicle's path. Unfortunately, pedestrian-detection-based systems can b

Guangsheng Bao, Zhiyang Teng, Yue Zhang

Document-level machine translation faces the challenge of data sparsity due to its long input length and a small amount of training data, increasing the risk of learning spurious patterns. To address this challenge, we propose a target-side augmentation method, introducing a data augmentation (DA) model to generate many potential translations for each source

Muhammad Kashif, Saif Al-Kuwari

In this paper, we propose a framework to study the combined effect of several factors that contribute to the barren plateau problem in quantum neural networks (QNNs), which is a critical challenge in quantum machine learning (QML). These factors include data encoding, qubit entanglement, and ansatz expressibility. To investigate this joint effect in a real-w

Baihe Ma, Xu Wang, Xiaojie Lin, Yanna Jiang

Location privacy is critical in vehicular networks, where drivers' trajectories and personal information can be exposed, allowing adversaries to launch data and physical attacks that threaten drivers' safety and personal security. This survey reviews comprehensively different localization techniques, including widely used ones like sensing infrastructure-bas

Noor Awad, Ayushi Sharma, Philipp Muller, Janek Thomas

Hyperparameter optimization (HPO) is a powerful technique for automating the tuning of machine learning (ML) models. However, in many real-world applications, accuracy is only one of multiple performance criteria that must be considered. Optimizing these objectives simultaneously on a complex and diverse search space remains a challenging task. In this paper

Junran Wu, Xueyuan Chen, Bowen Shi, Shangzhe Li

In contrastive learning, the choice of ``view'' controls the information that the representation captures and influences the performance of the model. However, leading graph contrastive learning methods generally produce views via random corruption or learning, which could lead to the loss of essential information and alteration of semantic information. An a

Takeshi Kato

Methodologies for evaluating and selecting policies that contribute to the well-being of diverse populations need clarification. To bridge the gap between objective indicators and policies related to well-being, this study shifts from constitutive pluralism based on objective indicators to conceptual pluralism that emphasizes subjective context, develops fro