April 2024 arXiv papers — page 18

Gerald A. Goldin, David H. Sharp

In 1968, Dashen and Sharp obtained a certain singular Lie algebra of local densities and currents from canonical commutation relations in nonrelativistic quantum field theory. The corresponding Lie group is infinite dimensional: the natural semidirect product of an additive group of scalar functions with a group of diffeomorphisms. Unitary representations of

Rodrigo Tuna, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira

Forecasting methods are affected by data quality issues in two ways: 1. they are hard to predict, and 2. they may affect the model negatively when it is updated with new data. The latter issue is usually addressed by pre-processing the data to remove those issues. An alternative approach has recently been proposed, Corrector LSTM (cLSTM), which is a Read \&

A. F. M. ter Elst, E. M. Ouhabaz

We consider the Dirichlet-to-Neumann operator ${\cal N}$ associated with a general elliptic operator \[ {\cal A} u = - \sum_{k,l=1}^d \partial_k (c_{kl}\, \partial_l u) + \sum_{k=1}^d \Big( c_k\, \partial_k u - \partial_k (b_k\, u) \Big) +c_0\, u \in {\cal D}'(\Omega) \] with possibly complex coefficients. We study three problems: 1) Boundedness on $C^\nu$ a

Qi Zhu, Da Zheng, Xiang Song, Shichang Zhang

Text-rich graphs, which exhibit rich textual information on nodes and edges, are prevalent across a wide range of real-world business applications. Large Language Models (LLMs) have demonstrated remarkable abilities in understanding text, which also introduced the potential for more expressive modeling in text-rich graphs. Despite these capabilities, efficie

Aman Kumar

Error Detection and Correction Codes (ECCs) are often used in digital designs to protect data integrity. Especially in safety-critical systems such as automotive electronics, ECCs are widely used and the verification of such complex logic becomes more critical considering the ISO 26262 safety standards. Exhaustive verification of ECC using formal methods has

Bela Bajnok, Evan Chen

We present the problems and solutions to the 61st Annual International Mathematical Olympiad

Hans Jockers, Maik Sarve, Ida G. Zadeh

It is well-known that families of two-dimensional toroidal conformal field theories possess a dense subset of rational toroidal conformal field theories, which makes such families an interesting testing ground about rationality of conformal field theories in families in general. Rational toroidal conformal field theories possess an extended chiral and anti-c

Yizhou Chi, Jessy Lin, Kevin Lin, Dan Klein

Users often make ambiguous requests that require clarification. We study the problem of asking clarification questions in an information retrieval setting, where systems often face ambiguous search queries and it is challenging to turn the uncertainty in the retrieval model into a natural language question. We present CLARINET, a system that asks informative

Torben S. D. Johansen

In optimal policy problems where treatment effects vary at the individual level, optimally allocating treatments to recipients is complex even when potential outcomes are known. We present an algorithm for multi-arm treatment allocation problems that is guaranteed to find the optimal allocation in strongly polynomial time, and which is able to handle arbitra

Noga Mudrik, Eva Yezerets, Yenho Chen, Christopher Rozell

Identifying latent interactions within complex systems is key to unlocking deeper insights into their operational dynamics, including how their elements affect each other and contribute to the overall system behavior. For instance, in neuroscience, discovering neuron-to-neuron interactions is essential for understanding brain function; in ecology, recognizin

E. Sobolev, M. Volkov, E. Svirplys, J. Thomas

The generation of terawatt (TW) near-single-cycle laser pulses is of high interest for applications including attosecond science. Here we demonstrate a three-stage post-compression scheme in a non-guided geometry using He as the nonlinear medium, resulting in the generation of multi-mJ pulses with a duration of 3.7 fs. Key features of this approach are its s

D. J. Papoular, B. Zumer

We study theoretically two consequences of the mixed classical phase space for three repulsively-interacting bosonic particles in a circular trap. First, we show that the energy levels of the corresponding quantum system are well described by a Berry-Robnik distribution. Second, we identify stationary quantum states whose density is enhanced along the stable

Pin-Jie Lin, Merel Scholman, Muhammed Saeed, Vera Demberg

Nigerian Pidgin is an English-derived contact language and is traditionally an oral language, spoken by approximately 100 million people. No orthographic standard has yet been adopted, and thus the few available Pidgin datasets that exist are characterised by noise in the form of orthographic variations. This contributes to under-performance of models in cri

Andrés Viña

Considering $B$-branes over a complex manifold $X$ as objects of the bounded derived category of coherent sheaves over $X$, we define holomorphic gauge fields on $B$-branes and introduce the Yang-Mills functional for these fields. These definitions extend well-known concepts in the context of vector bundles to the setting of $B$-branes. For a given $B$-brane

Juan A. Sanchez, Vishnu Reddy, Audrey Thirouin, William F. Bottke

The study of small ($<$300 m) near-Earth objects (NEOs) is important because they are more closely related than larger objects to the precursors of meteorites that fall on Earth. Collisions of these bodies with Earth are also more frequent. Although such collisions cannot produce massive extinction events, they can still produce significant local damage. Her

Atharva Naik, Jessica Ruhan Yin, Anusha Kamath, Qianou Ma

An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussion, to potentially better engage students than standard feedback. We present a design and evaluation of a proof-of-concept LLM application to offer students dynamic and contextualiz

Choiti Bandyopadhyay

In a series of previous papers, we initiated a systematic study of semihypergroups and had a thorough discussion on certain analytic and algebraic aspects associated to this class of objects. In particular, we introduced the notion of semihypergroup actions on a general topological space and discussed different continuity, equivalence and natural fixed point

María Alfaro-Contreras, Jorge Calvo-Zaragoza

This paper serves to introduce the Align, Minimize and Diversify (AMD) method, a Source-Free Unsupervised Domain Adaptation approach for Handwritten Text Recognition (HTR). This framework decouples the adaptation process from the source data, thus not only sidestepping the resource-intensive retraining process but also making it possible to leverage the weal

J. A. Mendez-Bermudez, R. Aguilar-Sanchez

Singular-value statistics (SVS) has been recently presented as a random matrix theory tool able to properly characterize non-Hermitian random matrix ensembles [PRX Quantum {\bf 4}, 040312 (2023)]. Here, we perform a numerical study of the SVS of the non-Hermitian adjacency matrices $\mathbf{A}$ of directed random graphs, where $\mathbf{A}$ are members of dil

A. V. Guglielmi, O. D. Zotov

The essence of the cumulative effect of a round-the-world seismic echo is that the echo can serve as a trigger for a second tremors in the epicentral zone of the earthquake that gave rise to the echo. According to the classification of triggers, the round-the-world echo is an endogenous force mechanical additive trigger. The round-the-world echo excited by t

Nilo Pedrazzini

Languages can encode temporal subordination lexically, via subordinating conjunctions, and morphologically, by marking the relation on the predicate. Systematic cross-linguistic variation among the former can be studied using well-established token-based typological approaches to token-aligned parallel corpora. Variation among different morphological means i

Chao Cheng, Fan Li

In cluster-randomized trials (CRTs), there is emerging interest in exploring the causal mechanism in which a cluster-level treatment affects the outcome through an intermediate outcome. The majority of existing causal mediation methods are applicable to independent data and only a few exceptions have considered assessing causal mediation in CRTs, all of whic

Zilong Bai, Ruiji Zhang, Linqing Chen, Qijun Cai

In recent years, large language models(LLMs) have attracted significant attention due to their exceptional performance across a multitude of natural language process tasks, and have been widely applied in various fields. However, the application of large language models in the Intellectual Property (IP) domain is challenging due to the strong need for specia

Panagiotis Nikolaidis, John Baras

In network slicing, the network operator needs to satisfy the service level agreements of multiple slices at the same time and on the same physical infrastructure. To do so with reduced provisioned resources, the operator may consider resource sharing mechanisms. However, each slice then becomes susceptible to traffic surges in other slices which degrades pe

Tengjun Huang

With the rise of Visual and Language Pretraining (VLP), an increasing number of downstream tasks are adopting the paradigm of pretraining followed by fine-tuning. Although this paradigm has demonstrated potential in various multimodal downstream tasks, its implementation in the remote sensing domain encounters some obstacles. Specifically, the tendency for s

Kaiyu Song, Hanjiang Lai

Training-free conditional diffusion models have received great attention in conditional image generation tasks. However, they require a computationally expensive conditional score estimator to let the intermediate results of each step in the reverse process toward the condition, which causes slow conditional generation. In this paper, we propose a novel Fish

Poupak Azad, Cuneyt Gurcan Akcora, Arijit Khan

Blockchain technology has rapidly emerged to mainstream attention, while its publicly accessible, heterogeneous, massive-volume, and temporal data are reminiscent of the complex dynamics encountered during the last decade of big data. Unlike any prior data source, blockchain datasets encompass multiple layers of interactions across real-world entities, e.g.,

Tohida Rehman, Raghubir Bose, Samiran Chattopadhyay, Debarshi Kumar Sanyal

Financial sentiment analysis allows financial institutions like Banks and Insurance Companies to better manage the credit scoring of their customers in a better way. Financial domain uses specialized mechanisms which makes sentiment analysis difficult. In this paper, we propose a pre-trained language model which can help to solve this problem with fewer labe

Mikhail Lomonosov, Vladimir Shiltsev

Mikhail Lomonosov (1711-1765) was the eminent Russian polymath and a towering figure of the European Enlightenment. This English translation of Mikhail Lomonosov seminal work "Oration on the Origin of Light " draws from its original Russian and Latin sources. It is part of a series of English translations of nine most significant scientific treatises, all of

Jie Qiu, Colin Cai, Sahil Bhatia, Niranjan Hasabnis

Tensor processing infrastructures such as deep learning frameworks and specialized hardware accelerators have revolutionized how computationally intensive code from domains such as deep learning and image processing is executed and optimized. These infrastructures provide powerful and expressive abstractions while ensuring high performance. However, to utili

Yudai Suwa, Akira Harada, Masamitsu Mori, Ken'ichiro Nakazato

Neutrinos are pivotal signals in multi-messenger observations of supernovae (SNe). Recent advancements in the analysis method of supernova (SN) neutrinos, especially in quantitative analysis, have significantly broadened scientific possibilities. This study demonstrates the feasibility of estimating distances to SNe using neutrinos. This estimation utilizes

Gabriel Lopes Cardoso, Damián Mayorga Peña, Suresh Nampuri

We study the integrability of two-dimensional theories that are obtained by a dimensional reduction of certain four-dimensional gravitational theories describing the coupling of Maxwell fields and neutral scalar fields to gravity in the presence of a potential for the neutral scalar fields. For a certain solution subspace, we demonstrate partial integrabilit

M. S. Veshchunov

By critically examining the traditional theory of homogeneous nucleation of precipitates in solid solutions, it is revealed that the theory's assertion regarding an increase in the nucleation free energy due to elastic strain associated with the difference in atomic volumes between the two phases is applicable to coherent precipitates, but becomes incorrect

Haoxiao Wang, Bo Peng, Jianhua Zhang, Xu Cheng

Time series classification is one of the most critical and challenging problems in data mining, existing widely in various fields and holding significant research importance. Despite extensive research and notable achievements with successful real-world applications, addressing the challenge of capturing the appropriate receptive field (RF) size from one-dim

Yanbing Bai, Siao Li, Rui-Yang Ju, Zihao Yang

Illegal, unreported, and unregulated (IUU) fishing activities seriously affect various aspects of human life. However, traditional methods for detecting and monitoring IUU fishing activities at sea have limitations. Although synthetic aperture radar (SAR) can complement existing vessel detection systems, extracting useful information from SAR images using tr

David Raveh, Rafael I. Nepomechie

Bethe equations, whose solutions determine exact eigenvalues and eigenstates of corresponding integrable Hamiltonians, are generally hard to solve. We implement a Variational Quantum Eigensolver (VQE) approach to estimating Bethe roots of the spin-1/2 XXZ quantum spin chain, by using Bethe states as trial states, and treating Bethe roots as variational param

Zhili Cheng, Zhitong Wang, Jinyi Hu, Shengding Hu

Despite advancements in Large Language Models (LLMs) and Large Multimodal Models (LMMs), their integration into language-grounded, human-like embodied agents remains incomplete, hindering complex real-life task performance in physical environments. Existing integrations often feature limited open sourcing, challenging collective progress in this field. We in

Shivam Singh Dhama, Konstantinos Spiliopoulos

We study the asymptotic behavior, uniform-in-time, of a non-linear dynamical system under the combined effects of fast periodic sampling with period $\delta$ and small white noise of size $\varepsilon,\thinspace 0<\varepsilon,\delta \ll 1$. The dynamics depend on both the current and recent measurements of the state, and as such it is not Markovian. Our main

Nicolas Burq, Nicolas Camps, Mickaël Latocca, Chenmin Sun

We consider the Wick ordered cubic Schr\"odinger equation (NLS) posed on the two-dimensional sphere, with initial data distributed according to a Gaussian measure. We show that the second Picard iteration does not improve the regularity of the initial data in the scale of the classical Sobolev spaces. This is in sharp contrast with the Wick ordered NLS on th

Calvin Preston, Alexandra Amon, George Efstathiou

Analyses of cosmic shear typically condense weak lensing information over a range of scales to a single cosmological parameter, $S_8$. This paper presents a method to extract more information from Stage-IV cosmic shear measurements by directly reconstructing the matter power spectrum from linear to non-linear scales. We demonstrate that cosmic shear surveys

Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu

Large Language Models (LLMs) have highlighted the necessity of effective unlearning mechanisms to comply with data regulations and ethical AI practices. LLM unlearning aims at removing undesired data influences and associated model capabilities without compromising utility beyond the scope of unlearning. While interest in studying LLM unlearning is growing,

Erik Paemurru

There is a proposition due to Koll\'ar 1997 on computing log canonical thresholds of certain hypersurface germs using weighted blowups, which we extend to weighted blowups with non-negative weights. Using this, we show that the log canonical threshold of a convergent complex power series is at most $1/c$, where $(c, \ldots, c)$ is a point on a facet of its N

Tsukasa Ishibashi, Shunsuke Kano

We continue to study the unbounded $\mathfrak{sl}_3$-laminations [IK22], with a focus on their structures at punctures. A key ingredient is their relation to the root data of $\mathfrak{sl}_3$. After giving a classification of signed $\mathfrak{sl}_3$-webs around a puncture, we describe the tropicalization of the Goncharov--Shen's Weyl group action in detail

Yanbing Bai, Zihao Yang, Jinze Yu, Rui-Yang Ju

With the escalating frequency of floods posing persistent threats to human life and property, satellite remote sensing has emerged as an indispensable tool for monitoring flood hazards. SpaceNet8 offers a unique opportunity to leverage cutting-edge artificial intelligence technologies to assess these hazards. A significant contribution of this research is it

Gabriel Müller, V. J. Martínez-Lahuerta, Ivan Sekulic, Sven Burger

State engineering of quantum objects is a central requirement in most implementations. In the cases where the quantum dynamics can be described by analytical solutions or simple approximation models, optimal state preparation protocols have been theoretically proposed and experimentally realized. For more complex systems, however, such as multi-component qua

Evangelos Georgiadis

The Hayashi-Yoshida (\HY)-estimator exhibits an intrinsic, telescoping property that leads to an often overlooked computational bias, which we denote,formulaic or intrinsic bias. This formulaic bias results in data loss by cancelling out potentially relevant data points, the nonextant data points. This paper attempts to formalize and quantify the data loss a

Thomas Thiemann

In a seminal work, Hawking showed that natural states for free quantum matter fields on classical spacetimes that solve the spherically symmetric vacuum Einstein equations are KMS states of non-vanishing temperature. Although Hawking's calculation does not include backreaction of matter on geometry, it is more than plausible that the corresponding Hawking ra

Daniel Malinsky

We study the data-driven selection of causal graphical models using constraint-based algorithms, which determine the existence or non-existence of edges (causal connections) in a graph based on testing a series of conditional independence hypotheses. In settings where the ultimate scientific goal is to use the selected graph to inform estimation of some caus

Jiangjie Chen, Xintao Wang, Rui Xu, Siyu Yuan

Recent advancements in large language models (LLMs) have significantly boosted the rise of Role-Playing Language Agents (RPLAs), i.e., specialized AI systems designed to simulate assigned personas. By harnessing multiple advanced abilities of LLMs, including in-context learning, instruction following, and social intelligence, RPLAs achieve a remarkable sense

Wajd Afsi, Salem Omri

Let Vect($\mathbb{R}$) be the Lie algebra of smooth vector fields on $\mathbb{R}$ and $\mathbb{F}_{\lambda}$ be the space of $\lambda$-densities on $\mathbb{R}$. Vect($\mathbb{R}$) acts on $\mathbb{F}_{\lambda}$ by Lie derivative. In this paper, we compute the third differential cohomology of the Lie algebra Vect($\mathbb{R}$) with coeffcients in the space $

Thomas Thiemann

For interacting classical field theories such as general relativity exact solutions typically can only be found by imposing physically motivated (Killing) {\it symmetry} assumptions. Such highly symmetric solutions are then often used as {\it backgrounds} in a {\it perturbative} approach to more general non-symmetric solutions. If the theory is in addition a

Nicolas Burq, Nicolas Camps, Chenmin Sun, Nikolay Tzvetkov

We establish the probabilistic well-posedness of the nonlinear Schr\"odinger equation on the $2d$ sphere $\mathbb{S}^{2}$. The initial data are distributed according to Gaussian measures with typical regularity $H^{s}(\mathbb{S}^{2})$, for $s>0$. This level of regularity goes significantly beyond existing deterministic results, in a regime where the flow map

Sharayu Hiwarkhedkar, Saloni Mittal, Vidula Magdum, Omkar Dhekane

For green AI, it is crucial to measure and reduce the carbon footprint emitted during the training of large language models. In NLP, performing pre-training on Transformer models requires significant computational resources. This pre-training involves using a large amount of text data to gain prior knowledge for performing downstream tasks. Thus, it is impor

Antoine Rouxel, Antoine Monmayrant, Stéphane Calvez, Olivier Gauthier-Lafaye

The selective spatial mode excitation of a bi-dimensional grating-coupled micro-cavity called a Cavity Resonator Integrated Grating Filter (CRIGF) is reported using an incident beam shaped to reproduce the theoretical emission profiles of the device in one- and subsequently two-dimensions.In both cases, the selective excitation of modes up to order 10 (per d

Ammar Daskin

A matrix can be converted into a doubly stochastic matrix by using two diagonal matrices. And a doubly stochastic matrix can be written as a sum of permutation matrices. In this paper, we describe a method to write a given generic matrix in terms of quantum gates based on the block encoding. In particular, we first show how to convert a matrix into doubly st

Yi Cheng, Hang Liu, Guoping Pan, Linqi Ye

Traversing 3-D complex environments has always been a significant challenge for legged locomotion. Existing methods typically rely on external sensors such as vision and lidar to preemptively react to obstacles by acquiring environmental information. However, in scenarios like nighttime or dense forests, external sensors often fail to function properly, nece

Renata Ferrero, Thomas Thiemann

In a recent contribution we identified possible points of contact between the asymptotically safe and canonical approach to quantum gravity. The idea is to start from the reduced phase space (often called relational) formulation of canonical quantum gravity which provides a reduced (or physical) Hamiltonian for the true (observable) degrees of freedom. The r

L. Cupertino-Malheiros, T. K. Mandal, F. Thebault, E. Martínez-Pañeda

Combined experiments and computational modelling are used to increase understanding of the suitability of the Single-Edge Notch Tension (SENT) test for assessing hydrogen embrittlement susceptibility. The SENT tests were designed to provide the mode I threshold stress intensity factor ($K_{\text{th}}$) for hydrogen-assisted cracking of a C110 steel in two co

V. Bovdi, D. Leites

We distinguish two classifications of bidifferential operators: between (A) spaces of modular forms and (B) spaces of weighted densities. (A) The invariant under the projective action of $\text{SL}(2;\mathbb{Z})$ binary differential operators between spaces of modular forms of integer or half-integer weight on the 1-dimensional manifold were found by Gordan

David Garzón Ramos, Mauro Birattari

Automatic design is a promising approach to realizing robot swarms. Given a mission to be performed by the swarm, an automatic method produces the required control software for the individual robots. Automatic design has concentrated on missions that a swarm can execute independently, interacting only with a static environment and without the involvement of

Thomas Thiemann

The canonical (CQG) and asymptotically safe (ASQG) approach to quantum gravity share to be both non-perturbative programmes. However, apart from that they seem to differ in several aspects such as: 1. Signature: CQG is Lorentzian while ASQG is mostly Euclidian. 2. Background Independence (BI): CQG is manifesly BI while ASQG is apparently not. 3. Truncations:

Cheng Jiang, Sitian Qian, Huilin Qu

Tabular data stands out as one of the most frequently encountered types in high energy physics. Unlike commonly homogeneous data such as pixelated images, simulating high-dimensional tabular data and accurately capturing their correlations are often quite challenging, even with the most advanced architectures. Based on the findings that tree-based models sur

Alexandra J. Simpson, Jacqueline M. McSweeney, James A. Lerczak, Merrick C. Haller

A combined radar remote sensing and in situ data set is used to track packets of nonlinear internal waves as they propagate and shoal across the inner shelf (40m - 9m). The dataset consists of high space-time resolution (5m, 2min) radar image time series collected over a 10km radial footprint, with over a dozen synchronous and co-located moorings measuring t

Bing Chen, Xun Chen, Xiaohua Li, Zhou-Run Zhu

Based on the holographic model, which incorporates the equation of state (EoS) and baryon number susceptibility for different flavors, we calculate the drag force, jet quenching parameter, and diffusion coefficient of the heavy quark at finite temperature and chemical potential. The holographic results for the diffusion coefficient align with lattice data fo

Saloni Mittal, Vidula Magdum, Omkar Dhekane, Sharayu Hiwarkhedkar

The availability of text or topic classification datasets in the low-resource Marathi language is limited, typically consisting of fewer than 4 target labels, with some achieving nearly perfect accuracy. In this work, we introduce L3Cube-MahaNews, a Marathi text classification corpus that focuses on News headlines and articles. This corpus stands out as the

Benjamin Dequêne

The classical Robinson--Schensted--Knuth correspondence is a bijection from nonnegative integer matrices to pairs of semi-standard Young tableaux. Based on the work of, among others, Burge, Hillman, Grassl, Knuth and Gansner, it is known that a version of this correspondence gives, for any nonzero integer partition $\lambda$, a bijection from arbitrary filli

Zeyu Hu, Yuzhi Xiao, Tao Huang, Xuanrong Huo

Sequential recommendation is one of the important branches of recommender system, aiming to achieve personalized recommended items for the future through the analysis and prediction of users' ordered historical interactive behaviors. However, along with the growth of the user volume and the increasingly rich behavioral information, how to understand and dise

Guanchun Wang, Xiangrong Zhang, Zelin Peng, Tianyang Zhang

Land cover analysis using hyperspectral images (HSI) remains an open problem due to their low spatial resolution and complex spectral information. Recent studies are primarily dedicated to designing Transformer-based architectures for spatial-spectral long-range dependencies modeling, which is computationally expensive with quadratic complexity. Selective st

Navve Wasserman, Noam Rotstein, Roy Ganz, Ron Kimmel

Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual instructions without requiring user-provided input masks remains a challenge. We address this by leveraging the insight that removing objects (Inpaint) is significantly simpler than i

Yanping Zheng, Lu Yi, Zhewei Wei

Graph neural networks (GNNs) have emerged as a powerful tool for effectively mining and learning from graph-structured data, with applications spanning numerous domains. However, most research focuses on static graphs, neglecting the dynamic nature of real-world networks where topologies and attributes evolve over time. By integrating sequence modeling modul

Mohammad Javad Najafirad, Shirantha Welikala

This paper presents a novel dissipativity-based distributed droop-free control approach for the voltage regulation problem in DC microgrids (MGs) comprised of an interconnected set of distributed generators (DGs), loads, and power lines. First, we describe the closed-loop DC MG as a networked system where the sets of DGs and lines (i.e., subsystems) are inte

Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai

Although RDBs store vast amounts of rich, informative data spread across interconnected tables, the progress of predictive machine learning models as applied to such tasks arguably falls well behind advances in other domains such as computer vision or natural language processing. This deficit stems, at least in part, from the lack of established/public RDB b

Víctor Mayoral-Vilches, Juan Manuel Reina-Muñoz, Martiño Crespo-Álvarez, David Mayoral-Vilches

The Robot Operating System (ROS) pubsub model played a pivotal role in developing sophisticated robotic applications. However, the complexities and real-time demands of modern robotics necessitate more efficient communication solutions that are deterministic and isochronous. This article introduces a groundbreaking approach: embedding ROS 2 message-passing i

Serguei Maliar, Bernard Salanie

The positive correlation test for asymmetric information developed by Chiappori and Salanie (2000) has been applied in many insurance markets. Most of the literature focuses on the special case of constant correlation; it also relies on restrictive parametric specifications for the choice of coverage and the occurrence of claims. We relax these restrictions

Sujit Khanna, Shishir Subedi

In recent times Large Language Models have exhibited tremendous capabilities, especially in the areas of mathematics, code generation and general-purpose reasoning. However for specialized domains especially in applications that require parsing and analyzing large chunks of numeric or tabular data even state-of-the-art (SOTA) models struggle. In this paper,

Cuiwei Liu, Youzhi Jiang, Chong Du, Zhaokui Li

Skeleton-based action recognition is vital for comprehending human-centric videos and has applications in diverse domains. One of the challenges of skeleton-based action recognition is dealing with low-quality data, such as skeletons that have missing or inaccurate joints. This paper addresses the issue of enhancing action recognition using low-quality skele

Dmitry Rozplokhas

{\AA}qvist's logics (E, F, F+(CM), and G) are among the best-known systems in the long tradition of preference-based approaches for modeling conditional obligation. While the general semantics of preference models align well with philosophical intuitions, more constructive characterizations are needed to assess computational complexity and facilitate automat

E. Frigerio, G. Rebora, M. Ruelle, H. Souquet-Basiège

Quantum Hall systems are platforms of choice when it comes to study topological properties of condensed matter systems and anyonic exchange statistics. In this work we have developed a tunable radiofrequency edge magnetoplasmonic resonator meant to serve as a versatile platform for future interferometric devices. The resonance frequency of the system is cont

Zicheng Zhang, Haoning Wu, Yingjie Zhou, Chunyi Li

Although large multi-modality models (LMMs) have seen extensive exploration and application in various quality assessment studies, their integration into Point Cloud Quality Assessment (PCQA) remains unexplored. Given LMMs' exceptional performance and robustness in low-level vision and quality assessment tasks, this study aims to investigate the feasibility

Minhao Bai, Kaiyi Pang, Yongfeng Huang

In the rapidly evolving domain of artificial intelligence, safeguarding the intellectual property of Large Language Models (LLMs) is increasingly crucial. Current watermarking techniques against model extraction attacks, which rely on signal insertion in model logits or post-processing of generated text, remain largely heuristic. We propose a novel method fo

Zhiqi Ge, Hongzhe Huang, Mingze Zhou, Juncheng Li

World models are progressively being employed across diverse fields, extending from basic environment simulation to complex scenario construction. However, existing models are mainly trained on domain-specific states and actions, and confined to single-modality state representations. In this paper, We introduce WorldGPT, a generalist world model built upon M

Dingzhe Li, Yixiang Jin, Yuhao Sun, Yong A

The realization of universal robots is an ultimate goal of researchers. However, a key hurdle in achieving this goal lies in the robots' ability to manipulate objects in their unstructured surrounding environments according to different tasks. The learning-based approach is considered an effective way to address generalization. The impressive performance of

Xue Cheng, Meng Wang, Ziyi Xu

The interactions between a large population of high-frequency traders (HFTs) and a large trader (LT) who executes a certain amount of assets at discrete time points are studied. HFTs are faster in the sense that they trade continuously and predict the transactions of LT. A jump process is applied to model the transition of HFTs' attitudes towards inventories

Fares Bougourzi, Fadi Dornaika, Abdelmalik Taleb-Ahmed, Vinh Truong Hoang

Inspired by the success of Transformers in Computer vision, Transformers have been widely investigated for medical imaging segmentation. However, most of Transformer architecture are using the recent transformer architectures as encoder or as parallel encoder with the CNN encoder. In this paper, we introduce a novel hybrid CNN-Transformer segmentation archit

Sreetama Das, Filippo Caruso

The Symmetric group $S_{n}$ manifests itself in large classes of quantum systems as the invariance of certain characteristics of a quantum state with respect to permuting the qubits. The subgroups of $S_{n}$ arise, among many other contexts, to describe label symmetry of classical images with respect to spatial transformations, e.g. reflection or rotation. E

Haoyue Bai, Le Wu, Min Hou, Miaomiao Cai

Multimedia-based recommendation provides personalized item suggestions by learning the content preferences of users. With the proliferation of digital devices and APPs, a huge number of new items are created rapidly over time. How to quickly provide recommendations for new items at the inference time is challenging. What's worse, real-world items exhibit var

Yonghe Zhao, Huiyan Sun

Causal inference methods for observational data are highly regarded due to their wide applicability. While there are already numerous methods available for de-confounding bias, these methods generally assume that covariates consist solely of confounders or make naive assumptions about the covariates. Such assumptions face challenges in both theory and practi

Zijian Ding

Technological advances continue to redefine the dynamics of human-machine interactions, particularly in task execution. This proposal responds to the advancements in Generative AI by outlining a research plan that probes intent-AI interaction across a diverse set of tasks: fixed-scope content curation task, atomic creative tasks, and complex and interdepende

Selime Beyza Özçevik, Abdullah Dertli, Savaş Karaahmetoğlu

The aim of this work is to provide the contributors to journals or Hybrid numbers, akin to spinors, possess a broad range of applications in mathematical physics, geometry, and mathematics. In this study, these two significant topics were collectively addressed, introducing a new perspective to spinors and defining hybrid spinors, from which several basic pr

Ruo-Xun Zhai, Hui Dong

Chemical gradients provide the primordial energy for biological functions by driving the mechanical movement of microscopic engines. Their thermodynamic properties remain elusive, especially concerning the dynamic change in energy demand in biological systems. In this article, we derive a constraint relation between the output power and the conversion effici

Yasuaki Hiraoka, Yusuke Imoto, Shu Kanazawa, Enhao Liu

The stability of persistent homology has led to wide applications of the persistence diagram as a trusted topological descriptor in the presence of noise. However, with the increasing demand for high-dimension and low-sample-size data processing in modern science, it is questionable whether persistence diagrams retain their reliability in the presence of hig

Yu-Qi Lei, Xian-Hui Ge, Surojit Dalui

We compute the Lyapunov exponents for test particles orbiting in unstable circular trajectories around D-dimensional Reissner-Nordstr\"om (RN) black holes, scrutinizing instances of the chaos bound violation. Notably, we discover that an increase in particle angular momentum exacerbates the breach of the chaos bound. Our research centrally investigates the c

Yuanyuan Zhang, Huhu Zhang, Tingzeng Wu, Xing Gao

In this paper, we first introduce a weighted derivation on algebras over an operad $\cal P$, and prove that for the free $\cal P$-algebra, its weighted derivation is determined by the restriction on the generators. As applications, we propose the concept of weighted differential ($q$-tri)dendriform algebras and study some basic properties of them. Then Novik

Yixiao Feng, Zhou Jiang, Yongliang Shi, Yunlong Feng

Accurate localization is an essential technology for the flexible navigation of robots in large-scale environments. Both SLAM-based and map-based localization will increase the computing load due to the increase in map size, which will affect downstream tasks such as robot navigation and services. To this end, we propose a localization system based on Block

Chen Cheng, Xinzhi Yu, Haodong Wen, Jingsong Sun

Recently, the mysterious In-Context Learning (ICL) ability exhibited by Transformer architectures, especially in large language models (LLMs), has sparked significant research interest. However, the resilience of Transformers' in-context learning capabilities in the presence of noisy samples, prevalent in both training corpora and prompt demonstrations, rema

Asif Hamid, Danish Rafiq, Shahkar Ahmad Nahvi, Mohammad Abid Bazaz

Complex systems often show macroscopic coherent behavior due to the interactions of microscopic agents like molecules, cells, or individuals in a population with their environment. However, simulating such systems poses several computational challenges during simulation as the underlying dynamics vary and span wide spatiotemporal scales of interest. To captu

Christopher K. I. Williams

This paper investigates the consequences of encoding a $K$-valued categorical variable incorrectly as $K$ bits via one-hot encoding, when using a Na\"{\i}ve Bayes classifier. This gives rise to a product-of-Bernoullis (PoB) assumption, rather than the correct categorical Na\"{\i}ve Bayes classifier. The differences between the two classifiers are analysed ma

Janarbek Yuanbek, Akbar Islam, Ahmad Abliz, Yusuf Turek

In this paper, we study the effects of postselected von Neumann measurement on the nonclassicality of the Single-Photon-Subtracted-Squeezed-Vacuum-State (SPSSVS). We calculate the squeezing effect, Mandel factor, Wigner function, signal-to-noise ratio (SNR)s and state distance function.We found that postselected von Neumann measurement has positive effects o

Yue-Yan Dong, Ji-Yu Song, Shang-Jie Jin, Jing-Fei Zhang

Multi-band gravitational-wave (GW) standard siren observations are poised to herald a new era in the study of cosmic evolution. These observations offer higher signal-to-noise ratios and improved localizations compared to those achieved with single-band GW detection, which are crucial for the cosmological applications of dark sirens. In this work, we explore

Moritz Thümler, Shesha G. M. Srinivas, Malte Schröder, Marc Timme

We present the finite-size Kuramoto model analytically continued from real to complex variables and analyze its collective dynamics. For strong coupling, synchrony appears through locked states that constitute attractors, as for the real-variable system. However, synchrony persists in the form of \textit{complex locked states} for coupling strengths $K$ belo