April 2024 arXiv papers — page 147

Tatsuo Iguchi, Masahiro Takayama

Motivated by an analysis on the well-posedness of the initial boundary value problem for the motion of an inextensible hanging string, we first consider an initial boundary value problem for one-dimensional degenerate hyperbolic systems with a localized term and show its well-posedness in weighted Sobolev spaces. We then consider the linearized system for th

Yutao Ouyang, Jinhan Li, Yunfei Li, Zhongyu Li

We present a large language model (LLM) based system to empower quadrupedal robots with problem-solving abilities for long-horizon tasks beyond short-term motions. Long-horizon tasks for quadrupeds are challenging since they require both a high-level understanding of the semantics of the problem for task planning and a broad range of locomotion and manipulat

Valerio Biscione, Milton L. Montero, Marin Dujmovic, Gaurav Malhotra

Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision. In almost all cases these benchmarks are observational in the sense they are composed of behavioural and brain responses to naturalistic images that have not been manipulated to test hypotheses regarding how DNNs or humans perceive and identi

Jia-Xi Feng, Fengge Zhang, Xian Gao

We study the scalar induced gravitational waves (SIGWs) from a chiral scalar-tensor theory of gravity. The parity-violating (PV) Lagrangian contains the Chern-Simons (CS) term and PV scalar-tensor terms, which are built of the quadratic Riemann tensor term and first-order derivatives of a scalar field. We consider SIGWs in two cases, in which the semi-analyt

Chenpeng Yu, Xing Fang, Hui Liu

The immune checkpoint inhibitors have demonstrated promising clinical efficacy across various tumor types, yet the percentage of patients who benefit from them remains low. The bindings between tumor antigens and HLA-I/TCR molecules determine the antigen presentation and T-cell activation, thereby playing an important role in the immunotherapy response. In t

Alessandro Nagar, Rossella Gamba, Piero Rettegno, Veronica Fantini

We present an updated version of the TEOBResumS-Dali effective-one-body (EOB) waveform model for spin aligned binaries on non-circularized orbits. Recently computed 4PN (nonspinning) terms are incorporated in the waveform and radiation reaction. The model is informed by a restricted sample ($\sim60$) of spin-aligned, quasi-circular, Numerical Relativity (NR)

Ismail Soudi, Abhijit Majumder

Various azimuthal anisotropies ($v_1, v_2, v_3, v_4$), at high transverse momentum (high-$p_T$), are shown to arise from the asymmetric scattering of transverse polarized quarks and gluons, arising from unpolarized nucleons (the Boer-Mulders' effect) and resulting in unpolarized hadrons (the Collins effect). Combined with the asymmetric scattering of partons

Kento Kawaharazuka, Shogo Makino, Masaya Kawamura, Ayaka Fujii

Tendon-driven musculoskeletal humanoids have many benefits in terms of the flexible spine, multiple degrees of freedom, and variable stiffness. At the same time, because of its body complexity, there are problems in controllability. First, due to the large difference between the actual robot and its geometric model, it cannot move as intended and large inter

Haitian Zhang, Chang Xu, Xinya Wang, Bingde Liu

Object detection is critical in autonomous driving, and it is more practical yet challenging to localize objects of unknown categories: an endeavour known as Class-Agnostic Object Detection (CAOD). Existing studies on CAOD predominantly rely on ordinary cameras, but these frame-based sensors usually have high latency and limited dynamic range, leading to saf

Yue Wang, Xin Wang, Shijie Sun, Fengquan Wu

The HI 21cm global signal from the Cosmic Dawn and the Epoch of Reionization (EoR) offers critical insights into the evolution of our Universe. Yet, its detection presents significant challenges due to its extremely low signal-to-contamination ratio and complex instrumental systematics. In this paper, we examine the effects of the ionosphere and antenna beam

Tobias M. Schmidt, François Bouchy

Achieving a truly accurate wavelength calibration of high-dispersion echelle spectrographs is a challenging task but crucially needed for certain science cases, e.g. to test for a possible variation of the fine-structure constant in quasar spectra. One of the spectrographs best suited for this mission is VLT/ESPRESSO. Nevertheless, previous studies have iden

Max Menssen, Martina Dammann, Firas Fneish, David Ellenberger

In pre-clinical and medical quality control, it is of interest to assess the stability of the process under monitoring or to validate a current observation using historical control data. Classically, this is done by the application of historical control limits (HCL) graphically displayed in control charts. In many applications, HCL are applied to count data,

Syrielle Montariol, Matej Martinc, Andraž Pelicon, Senja Pollak

For assessing various performance indicators of companies, the focus is shifting from strictly financial (quantitative) publicly disclosed information to qualitative (textual) information. This textual data can provide valuable weak signals, for example through stylistic features, which can complement the quantitative data on financial performance or on Envi

Xiahan Chen, Mingjian Chen, Sanli Tang, Yi Niu

3D object detection based on roadside cameras is an additional way for autonomous driving to alleviate the challenges of occlusion and short perception range from vehicle cameras. Previous methods for roadside 3D object detection mainly focus on modeling the depth or height of objects, neglecting the stationary of cameras and the characteristic of inter-fram

Z. Prudil, R. Smolec, A. Kunder, A. J Koch-Hansen

We present a new set of tools to derive systemic velocities for single-mode RR~Lyrae stars from visual and near-infrared spectra. We derived scaling relations and line-of-sight velocity templates using both APOGEE and {\it Gaia} spectroscopic products combined with photometric $G$-band amplitudes. We provide a means to estimate systemic velocities for the RR

Stella Civelli, Marco Secondini, Pantea Nadimi Goki, Luca Potì

We propose a coherent transceiver architecture able to transmit information and enhance the security of the optical network by identifying other optical systems and subsystems. Simulations show that identification is obtained with sufficient reliability in standard operating conditions.

Shreepranav Varma Enugandla, Xin Fang, Ghislain Fourier, Christian Steinert

Cerulli Irelli and Lanini have shown that PBW degenerations of flag varieties in type A and C are actually Schubert varieties of higher rank. We introduce Dynkin cones to parameterise specific abelianisations of classical Lie algebras. Within this framework, we generalise their result to all degenerations of flag varieties defined by degree vectors originati

Anupam Das, Damiano Mazza, Lê Thành Dũng Nguyên, Noam Zeilberger

We sketch a tentative proof of P-completeness for the $\beta$-convertibility problem on untyped planar (a.k.a. ordered or non-commutative) $\lambda$-terms.

Arim Song

We show that supersymmetric(SUSY) W-algebra of generic level can be realized as an intersection of the kernels of the screening operators. Applying this result to principal SUSY W-algebras, we get their free field realization inside the SUSY Heisenberg vertex algebras. Furthermore, the screening operators for principal SUSY W-algebras allow us to present the

Ping Wang, Lishun Wang, Xin Yuan

Video snapshot compressive imaging (SCI) aims to capture a sequence of video frames with only a single shot of a 2D detector, whose backbones rest in optical modulation patterns (also known as masks) and a computational reconstruction algorithm. Advanced deep learning algorithms and mature hardware are putting video SCI into practical applications. Yet, ther

Seungbeom Chin

Recent attention has turned to exploring quantum information within larger Hilbert spaces by utilizing qudits, which offer increased information capacity and potential for robust quantum communications. While the efficient generation of multipartite qudit entanglement is crucial for studying quantum correlations in high-dimensional Hilbert spaces, the increa

Jie Liu, Tao Feng, Yan Jiang, Peizheng Wang

We consider a scenario where a seller possesses a dataset $D$ and trains it into models of varying accuracies for sale in the market. Due to the reproducibility of data, the dataset can be reused to train models with different accuracies, and the training cost is independent of the sales volume. These two characteristics lead to fundamental differences betwe

Rahul Vaze

The problem of online scheduling of multi-server jobs is considered, where there are a total of $K$ servers, and each job requires concurrent service from multiple servers for it to be processed. Each job on its arrival reveals its processing time, the number of servers from which it needs concurrent service and an online algorithm has to make scheduling dec

Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini

Algorithmic Recourse aims to provide actionable explanations, or recourse plans, to overturn potentially unfavourable decisions taken by automated machine learning models. In this paper, we propose an interaction paradigm based on a guided interaction pattern aimed at both eliciting the users' preferences and heading them toward effective recourse interventi

Yermek Aldabergenov, Ignatios Antoniadis, Auttakit Chatrabhuti, Hiroshi Isono

We extend a recently proposed framework, dubbed inflation by supersymmetry breaking, to hybrid inflation by introducing a waterfall field that allows to decouple the supersymmetry breaking scale in the observable sector from the inflation scale, while keeping intact the inflation sector and its successful predictions: naturally small slow-roll parameters, sm

Jiaxiu Jiang, Yabo Zhang, Kailai Feng, Xiaohe Wu

Customized text-to-image generation, which synthesizes images based on user-specified concepts, has made significant progress in handling individual concepts. However, when extended to multiple concepts, existing methods often struggle with properly integrating different models and avoiding the unintended blending of characteristics from distinct concepts. I

Peilong Wang, Jingyuan Chen

Solar eclipses, as rare astronomical events, often evoke a profound sense of wonder and awe within the human spirit. However, for ordinary people, the extremely short preparation time, a few hours of notice from friends or social media, and the lack of observation equipment often hinder safe and effective eclipse viewing. Some individuals directly observe th

Laiyuan Gao, Horst Martini, Deyan Zhang

A nonlocal curvature flow is introduced to evolve locally convex curves in the plane. It is proved that this flow with any initial locally convex curve has a global solution, keeping the local convexity and the elastic energy of the evolving curve, and that, as the time goes to infinity, the curve converges to a smooth, locally convex curve of constant $k$-o

Sidney T. da Silva, Enrique C. Gabrick, Paulo R. Protachevicz, Kelly C. Iarosz

Dengue is a viral vector-borne infectious disease that affects many countries worldwide, infecting around 390 million people per year. The main outbreaks occur in subtropical and tropical countries. We study here the influence of climate on dengue in Natal (2016-2019), Brazil, Iquitos (2001-2012), Peru, and Barranquilla (2011-2016), Colombia. For the analysi

Mikołaj Bojańczyk, Lê Thành Dũng Nguyên, Rafał Stefański

Orbit-finite sets are a generalisation of finite sets, and as such support many operations allowed for finite sets, such as pairing, quotienting, or taking subsets. However, they do not support function spaces, i.e. if X and Y are orbit-finite sets, then the space of finitely supported functions from X to Y is not orbit-finite. In this paper we propose two s

Yihe Fan, Yuxin Cao, Ziyu Zhao, Ziyao Liu

Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities that increasingly influence various aspects of our daily lives, constantly defining the new boundary of Artificial General Intelligence (AGI). Image modalities, enriched with profound semantic information and a more continuous mathematical nature compared to other modalities, greatl

Johann Cigler

This note presents some results about Hankel determinants of backwards shifted Catalan-like numbers and related sequences.

Kai Junge, Josie Hughes

The impressive capabilities of humans to robustly perform manipulation relies on compliant interactions, enabled through the structure and materials spatially distributed in our hands. We propose by mimicking this distributed compliance in an anthropomorphic robotic hand, the open-loop manipulation robustness increases and observe the emergence of human-like

Placido Mursia, Francesco Devoti, Marco Rossanese, Vincenzo Sciancalepore

This paper presents a theoretical and mathematical framework for the design of a conformal reconfigurable intelligent surface (RIS) that adapts to non-planar geometries, which is a critical advancement for the deployment of RIS on non-planar and irregular surfaces as envisioned in smart radio environments. Previous research focused mainly on the optimization

Shan Shen, Zhiqiang Liu, Wenjian Yu

Designing the power delivery network (PDN) in very large-scale integrated (VLSI) circuits is increasingly important, especially for nowadays low-power integrated circuit (IC) design. In order to ensure that the designed PDN enables a low level of voltage drop and noise which is required for the success of IC design, accurate analysis of PDN is largely demand

Yani Zhang, Helmut Bölcskei

We develop a theory characterizing the fundamental capability of deep neural networks to learn, from evolution traces, the logical rules governing the behavior of cellular automata (CA). This is accomplished by first establishing a novel connection between CA and Lukasiewicz propositional logic. While binary CA have been known for decades to essentially perf

Judy X Yang, Jun Zhou, Jing Wang, Hui Tian

Band selection in hyperspectral imaging (HSI) is critical for optimising data processing and enhancing analytical accuracy. Traditional approaches have predominantly concentrated on analysing spectral and pixel characteristics within individual bands independently. These approaches overlook the potential benefits of integrating multiple data sources, such as

Teng Ma, Yue Xiao, Xia Lei, Ming Xiao

With the evolution of integrated sensing and communication (ISAC) technology, a growing number of devices go beyond conventional communication functions with sensing abilities. Therefore, future networks are divinable to encounter new privacy concerns on sensing, such as the exposure of position information to unintended receivers. In contrast to traditional

Junseo Park, Beomseok Ko, Hyeryung Jang

Recent advancements in text-to-image models, such as Stable Diffusion, have showcased their ability to create visual images from natural language prompts. However, existing methods like DreamBooth struggle with capturing arbitrary art styles due to the abstract and multifaceted nature of stylistic attributes. We introduce Single-StyleForge, a novel approach

Ibrahim Aliyu, Awwal Arigi, Seungmin Oh, Tai-Won Um

This paper addresses the problem of minimizing latency with partial computation offloading within Industrial Internet-of-Things (IoT) systems in in-network computing (COIN)-assisted Multiaccess Edge Computing (C-MEC) via ultra-reliable and low latency communications (URLLC) links. We propose a digital twin (DT) scheme for a multiuser scenario, allowing colla

Haoyuan Zhong, Changhua Bao, Tianyun Lin, Fei Wang

Revealing the fine electronic structure is critical for understanding the underlying physics of low-dimensional materials. Angle-resolved photoemission spectroscopy (ARPES) is a powerful experimental technique for mapping out the experimental electronic structure. By reducing the photon energy (e.g. to 6 eV) using laser sources, a greatly improved momentum r

Zhengde Zhang, Yiyu Zhang, Haodong Yao, Jianwen Luo

Large Language Models (LLMs) are undergoing a period of rapid updates and changes, with state-of-the-art (SOTA) model frequently being replaced. When applying LLMs to a specific scientific field, it's challenging to acquire unique domain knowledge while keeping the model itself advanced. To address this challenge, a sophisticated large language model system

Tianyu Chen, Yiming Zhang, Guoxin Yu, Dapeng Zhang

In this paper, we extend financial sentiment analysis~(FSA) to event-level since events usually serve as the subject of the sentiment in financial text. Though extracting events from the financial text may be conducive to accurate sentiment predictions, it has specialized challenges due to the lengthy and discontinuity of events in a financial text. To this

Fernando Blesa, Juan D. Bernal, Jesus M. Seoane, Miguel AF Sanjuan

In this paper, we study different types of phase space structures which appear in the context of relativistic chaotic scattering. By using the relativistic version of the H\'{e}non-Heiles Hamiltonian, we numerically study the topology of different kind of exit basins and compare it with the case of low velocities in which the Newtonian version of the system

Xu Wu, XianXu Hou, Zhihui Lai, Jie Zhou

Low-light image enhancement (LLIE) aims to improve low-illumination images. However, existing methods face two challenges: (1) uncertainty in restoration from diverse brightness degradations; (2) loss of texture and color information caused by noise suppression and light enhancement. In this paper, we propose a novel enhancement approach, CodeEnhance, by lev

Zekun Lu, Feng Chen, M. D. Ding, Can Wang

What physical mechanisms heat the outer solar or stellar atmosphere to million-Kelvin temperatures is a fundamental but long-standing open question. In particular, the solar corona in active region cores contains an even hotter component reaching ten million Kelvin, manifesting as persistent coronal loops in extreme ultraviolet and soft X-ray images, which i

Yadi Wei, Jiaxin Wang, Fang-Wei Fu

Association schemes play an important role in algebraic combinatorics and have important applications in coding theory, graph theory and design theory. The methods to construct association schemes by using bent functions have been extensively studied. Recently, in [13], {\"O}zbudak and Pelen constructed infinite families of symmetric association schemes of c

Yigeng Zhang, Fabio A. González, Thamar Solorio

Reading comprehension continues to be a crucial research focus in the NLP community. Recent advances in Machine Reading Comprehension (MRC) have mostly centered on literal comprehension, referring to the surface-level understanding of content. In this work, we focus on the next level - interpretive comprehension, with a particular emphasis on inferring the t

Yusuf Umut Ciftci, Darren Chiu, Zeyuan Feng, Gaurav S. Sukhatme

Behavior cloning (BC) is a widely-used approach in imitation learning, where a robot learns a control policy by observing an expert supervisor. However, the learned policy can make errors and might lead to safety violations, which limits their utility in safety-critical robotics applications. While prior works have tried improving a BC policy via additional

Jiehua Mai, Enhui Shi, Kesong Yan, Fanping Zeng

We study the existence of fixed points for continuous maps $f$ from an $n$-ball $X$ in $\mathbb R^n$ to $\mathbb R^n$ with $n\geq 1$. We show that $f$ has a fixed point if, for some absolute retract $Y\subset\partial X$, $f(Y)\subset X$ and $\partial X-Y$ is an $(f, X)$-blockading set. For $n\geq 2$, let $D$ be an $n$-ball in $X$ and $Y$ be an $(n-1)$-ball i

Akash nag Oruganti, Ivan Derkach, Radim Filip, Vladyslav C. Usenko

We address the role of noisy squeezing in security and performance of continuous-variable (CV) quantum key distribution (QKD) protocols. Squeezing has long been recognized for its numerous advantages in CV QKD, such as enhanced robustness against channel noise and loss, and improved secret key rates. However, the noise of the squeezed states, that unavoidabl

Shanshan Luo, Yixuan Yu, Chunchen Liu, Feng Xie

To evaluate a single cause of a binary effect, Dawid et al. (2014) defined the probability of causation, while Pearl (2015) defined the probabilities of necessity and sufficiency. For assessing the multiple correlated causes of a binary effect, Lu et al. (2023) defined the posterior causal effects based on post-treatment variables. In many scenarios, outcome

Murtadha Ahmed, Qun Chen

Aspect Category Detection (ACD) aims to identify implicit and explicit aspects in a given review sentence. The state-of-the-art approaches for ACD use Deep Neural Networks (DNNs) to address the problem as a multi-label classification task. However, learning category-specific representations heavily rely on the amount of labeled examples, which may not readil

Yung Won Cho, Nik Ruskuc

The monogenic free inverse semigroup $FI_1$ is not finitely presented as a semigroup due to the classic result by Schein (1975). We extend this result and prove that a finitely generated subsemigroup of $FI_1$ is finitely presented if and only if it contains only finitely many idempotents. As a consequence, we derive that an inverse subsemigroup of $FI_1$ is

Tejpalsingh Siledar, Rupasai Rangaraju, Sankara Sri Raghava Ravindra Muddu, Suman Banerjee

In e-commerce, opinion summarization is the process of summarizing the consensus opinions found in product reviews. However, the potential of additional sources such as product description and question-answers (QA) has been considered less often. Moreover, the absence of any supervised training data makes this task challenging. To address this, we propose a

Yulin Li, Chunxin Zheng, Kai Chen, Yusen Xie

In this work, we propose a trajectory optimization approach for robot navigation in cluttered 3D environments. We represent the robot's geometry as a semialgebraic set defined by polynomial inequalities such that robots with general shapes can be suitably characterized. To address the robot navigation task in obstacle-dense environments, we exploit the free

Amin Aminifar, Baichuan Huang, Azra Abtahi, Amir Aminifar

The human brain performs tasks with an outstanding energy efficiency, i.e., with approximately 20 Watts. The state-of-the-art Artificial/Deep Neural Networks (ANN/DNN), on the other hand, have recently been shown to consume massive amounts of energy. The training of these ANNs/DNNs is done almost exclusively based on the back-propagation algorithm, which is

Manita Pote

According to the classical definition, propaganda is the management of collective attitudes by manipulation of significant symbols. However this definition has changed to computational propaganda, the way manipulation takes place in digital medium. Computational propaganda is the use of algorithms, automation and human curation to purposefully distribute mis

Dan Yang, Jindan Xu, Wei Xu, Bin Sheng

This paper investigates the integration of a reconfigurable intelligent surface (RIS) into a secure multiuser massive multiple-input multiple-output (MIMO) system in the presence of transceiver hardware impairments (HWI), imperfect channel state information (CSI), and spatially correlated channels. We first introduce a linear minimum-mean-square error estima

Giang Nguyen, Mohammad Reza Taesiri, Sunnie S. Y. Kim, Anh Nguyen

Via thousands of papers in Explainable AI (XAI), attention maps \cite{vaswani2017attention} and feature importance maps \cite{bansal2020sam} have been established as a common means for finding how important each input feature is to an AI's decisions. It is an interesting, unexplored question whether allowing users to edit the feature importance at test time

Filippus S. Roux

Heralding, which is often used for preparing quantum optical states, is studied to determine the effects of the spatiotemporal properties of the process. Incorporating all the spatiotemporal degrees of freedom, we follow a Wigner functional approach to consider cases where these states are prepared to have Wigner functionals with negative regions, being suit

Y. Wang, A. Gao, Y. Gong, Y. Zeng

Recently, a surge of 3D style transfer methods has been proposed that leverage the scene reconstruction power of a pre-trained neural radiance field (NeRF). To successfully stylize a scene this way, one must first reconstruct a photo-realistic radiance field from collected images of the scene. However, when only sparse input views are available, pre-trained

Dillon Z. Chen, Sylvie Thiébaux

Heuristic search is a powerful approach for solving planning problems and numeric planning is no exception. In this paper, we boost the performance of heuristic search for numeric planning with various powerful techniques orthogonal to improving heuristic informedness: numeric novelty heuristics, the Manhattan distance heuristic, and exploring the use of mul

Weifeng Lin, Monika Kluzek, Nir kampf, Yifeng Cao

Healthy articular cartilage has excellent lubricating properties, with friction coefficients reaching extremely low values at physiological pressures. Such high-performing lubricating layer in joints is attributed to the surface hydration arising from the interplay between multiple hydrophilic biopolymers (such as hyaluronic acid, proteoglycans, and lubricin

Franco Flandoli, Ruojun Huang

We consider an abstract non-inertial model of aggregation under the influence of a Gaussian white noise with prescribed space-covariance, and prove a formula for the mean collision rate $R$, per unit of time and volume. Specializing the abstract theory to a non-inertial model obtained by an inertial one, with physical constants, in the limit of infinitesimal

Yirui Xiong

Let $X$ be the total space of canonical bundle of $\pp$, we study an invariant subspace of stability conditions on $X$ under an autoequivalence of $D^b(X)$. We describe the complete set of stable objects with respect to the invariant stability conditions and characterize the space of invariant stability conditions.

Xiaofan Li, Zhizhong Zhang, Xin Tan, Chengwei Chen

The vision-language model has brought great improvement to few-shot industrial anomaly detection, which usually needs to design of hundreds of prompts through prompt engineering. For automated scenarios, we first use conventional prompt learning with many-class paradigm as the baseline to automatically learn prompts but found that it can not work well in one

Ariel Neufeld, Julian Sester

In this article we present a general framework for non-concave robust stochastic control problems under model uncertainty in a discrete time finite horizon setting. Our framework allows to consider a variety of different path-dependent ambiguity sets of probability measures comprising, as a natural example, the ambiguity set defined via Wasserstein-balls aro

Narayana Darapaneni, Ashish K, Ullas M S, Anwesh Reddy Paduri

The battery management system plays a vital role in ensuring the safety and dependability of electric and hybrid vehicles. It is responsible for various functions, including state evaluation, monitoring, charge control, and cell balancing, all integrated within the BMS. Nonetheless, due to the uncertainties surrounding battery performance, implementing these

Mingzhe Yang, Hiromi Arai, Naomi Yamashita, Yukino Baba

Teaching unbiased decision-making is crucial for addressing biased decision-making in daily life. Although both raising awareness of personal biases and providing guidance on unbiased decision-making are essential, the latter topics remains under-researched. In this study, we developed and evaluated an AI system aimed at educating individuals on making unbia

Prabhanjan Ananth, Aditya Gulati, Yao-Ting Lin

Common random string model is a popular model in classical cryptography with many constructions proposed in this model. We study a quantum analogue of this model called the common Haar state model, which was also studied in an independent work by Chen, Coladangelo and Sattath (arXiv 2024). In this model, every party in the cryptographic system receives many

Zhengxing Lian, Rongzhong Xiao

In the paper, we search for monochromatic infinite additive structures involving polynomials over $\mathbb{N}$. It is proved that for any $r\in \mathbb{N}$, any two distinct natural numbers $a,b$, and any $2$-coloring of $\mathbb{N}$, there exist two sets $B,C\subset \mathbb{N}$ with $|B|=r$ and $|C|=\infty$ such that there exists some color containing $B+aC

Said Daoudagh, Eda Marchetti, Oum-El-Kheir Aktouf

The recent events affecting global society continuously highlight the need to change the development lifecycle of complex systems by promoting human-centered solutions that increase awareness and ensure critical properties such as security, safety, trust, transparency, and privacy. This fast abstract introduces the Holistic Human-Centered Development Lifecyc

Chuwei Luo, Yufan Shen, Zhaoqing Zhu, Qi Zheng

Recently, leveraging large language models (LLMs) or multimodal large language models (MLLMs) for document understanding has been proven very promising. However, previous works that employ LLMs/MLLMs for document understanding have not fully explored and utilized the document layout information, which is vital for precise document understanding. In this pape

Melinda Hodkiewicz, Caitlin Woods, Matt Selway, Markus Stumptner

In this paper we present a publicly-available maintenance ontology (Iof-maint). Iof-maint is a modular ontology aligned with the Industrial Ontology Foundry Core (IOF Core) and contains 20 classes and 2 relations. It provides a set of maintenance-specific terms used in a wide variety of practical data-driven use cases. Iof-maint supports OWL DL reasoning, is

Yimin Tang, Sven Koenig, Jiaoyang Li

Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, plays a critical role in many applications. Sometimes, assigning a target to each agent also presents a challenge. The Combined Target-Assignment and Path-Finding (TAPF) problem, a variant of MAPF, requires one to simultaneously assign targets to agents and plan collisio

Lizaveta Ihnatsyeva, Kaushik Mohanta, Antti V. Vähäkangas

We prove that a pointwise fractional Hardy inequality implies a fractional Hardy inequality, defined via a Gagliardo-type seminorm. The proof consists of two main parts. The first one is to characterize the pointwise fractional Hardy inequality in terms of a fractional capacity density condition. The second part is to show the deep open-endedness or self-imp

Shibo Hao, Yi Gu, Haotian Luo, Tianyang Liu

Generating accurate step-by-step reasoning is essential for Large Language Models (LLMs) to address complex problems and enhance robustness and interpretability. Despite the flux of research on developing advanced reasoning approaches, systematically analyzing the diverse LLMs and reasoning strategies in generating reasoning chains remains a significant chal

Dingxi Zhang, Yu-Jie Yuan, Zhuoxun Chen, Fang-Lue Zhang

As XR technology continues to advance rapidly, 3D generation and editing are increasingly crucial. Among these, stylization plays a key role in enhancing the appearance of 3D models. By utilizing stylization, users can achieve consistent artistic effects in 3D editing using a single reference style image, making it a user-friendly editing method. However, re

Naveen Karunanayake, Ravin Gunawardena, Suranga Seneviratne, Sanjay Chawla

Deep neural networks (DNNs) deployed in real-world applications can encounter out-of-distribution (OOD) data and adversarial examples. These represent distinct forms of distributional shifts that can significantly impact DNNs' reliability and robustness. Traditionally, research has addressed OOD detection and adversarial robustness as separate challenges. Th

Gregorio Robles, Christoph Treude, Jesus M. Gonzalez-Barahona, Raula Gaikovina Kula

At the current pace of technological advancements, Generative AI models, including both Large Language Models and Large Multi-modal Models, are becoming integral to the developer workspace. However, challenges emerge due to the 'black box' nature of many of these models, where the processes behind their outputs are not transparent. This position paper advoca

Jaewoo Jeong, Daehee Park, Kuk-Jin Yoon

Human pose forecasting garners attention for its diverse applications. However, challenges in modeling the multi-modal nature of human motion and intricate interactions among agents persist, particularly with longer timescales and more agents. In this paper, we propose an interaction-aware trajectory-conditioned long-term multi-agent human pose forecasting m

Zekuan Yu, Haiwang Zhong, Guangchun Ruan, Xinfei Yan

Modern network-constrained unit commitment (NCUC) bears a heavy computational burden due to the ever-growing model scale. This situation becomes more challenging when detailed operational characteristics, complicated constraints, and multiple objectives are considered. We propose a novel simplification method to determine the flexible temporal resolution for

Hiroto Akaike

The \textit{slope} of a fibered $3$-folds $f:X \to B$ is a relative numerical invariant defined by $\lambda(f) := K_{f}^{3}/\mathrm{deg}(f_{\ast}\omega_{f})$, where $K_{f}$ is the relative canonical divisor and $\omega_{f}$ is the relative dualizing sheaf. Establishing slope inequalities is a fundamental problem in the geography of fibered spaces. In this pa

Swati Jindal, Mohit Yadav, Roberto Manduchi

Gaze is an essential prompt for analyzing human behavior and attention. Recently, there has been an increasing interest in determining gaze direction from facial videos. However, video gaze estimation faces significant challenges, such as understanding the dynamic evolution of gaze in video sequences, dealing with static backgrounds, and adapting to variatio

Nizar Riane, Claire David

In this work, we give a generalized formulation of the Black-Scholes model. The novelty resides in considering the Black-Scholes model to be valid on 'average', but such that the pointwise option price dynamics depends on a measure representing the investors' 'uncertainty'. We make use of the theory of non-symmetric Dirichlet forms and the abstract theory of

Gionnieve Lim, Simon T. Perrault

There is increasing interest in the adoption of LLMs in HCI research. However, LLMs may often be regarded as a panacea because of their powerful capabilities with an accompanying oversight on whether they are suitable for their intended tasks. We contend that LLMs should be adopted in a critical manner following rigorous evaluation. Accordingly, we present t

Yingtao Tian

Chinese, Japanese, and Korean (CJK), with a vast number of native speakers, have profound influence on society and culture. The typesetting of CJK languages carries a wide range of requirements due to the complexity of their scripts and unique literary traditions. A critical aspect of this typesetting process is that CJK fonts need to provide a set of consis

E. J. García-Claro

An easily computable dimension (or ECD) group code in the group algebra $\mathbb{F}_{q}G$ is an ideal of dimension less than or equal to $p=char(\mathbb{F}_{q})$ that is generated by an idempotent. This paper introduces an easily computable indecomposable dimension (or ECID) group algebra as a finite group algebra for which all group codes generated by primi

Jingxin Wang, Renxiang Guan, Kainan Gao, Zihao Li

Hyperspectral image (HSI) clustering is a challenging task due to its high complexity. Despite subspace clustering shows impressive performance for HSI, traditional methods tend to ignore the global-local interaction in HSI data. In this study, we proposed a multi-level graph subspace contrastive learning (MLGSC) for HSI clustering. The model is divided into

Selman Akbulut

Remarks relating the various notions of corks.

George Leotescu, Daniel Voinea, Alin-Ionut Popa

The transformer is a powerful data modelling framework responsible for remarkable performance on a wide range of tasks. However, they are limited in terms of scalability as it is suboptimal and inefficient to process long-sequence data. To this purpose we introduce BLRP (Bidirectional Long-Range Parser), a novel and versatile attention mechanism designed to

Philippe Goulet Coulombe, Karin Klieber, Christophe Barrette, Maximilian Goebel

Timely monetary policy decision-making requires timely core inflation measures. We create a new core inflation series that is explicitly designed to succeed at that goal. Precisely, we introduce the Assemblage Regression, a generalized nonnegative ridge regression problem that optimizes the price index's subcomponent weights such that the aggregate is maxima

Lingnan Shen, Di Xiao, Ting Cao

Defects in hexagonal boron nitride (hBN), a two-dimensional van der Waals material, have raised wide range interest for its potential in various quantum applications. Due to hBN's 2D nature, spin center in hBN can be engineered in close proximity to target material, providing advantages over their 3D counterparts, such as nitrogen-vacancy (NV) center in diam

Nan Zhou, Jiaxin Chen, Di Huang

Recent progress has shown great potential of visual prompt tuning (VPT) when adapting pre-trained vision transformers to various downstream tasks. However, most existing solutions independently optimize prompts at each layer, thereby neglecting the usage of task-relevant information encoded in prompt tokens across layers. Additionally, existing prompt struct

Changan Chen, Kumar Ashutosh, Rohit Girdhar, David Harwath

We propose a novel self-supervised embedding to learn how actions sound from narrated in-the-wild egocentric videos. Whereas existing methods rely on curated data with known audio-visual correspondence, our multimodal contrastive-consensus coding (MC3) embedding reinforces the associations between audio, language, and vision when all modality pairs agree, wh

Babak Poorebrahim Gilkalaye, Shubhabrata Mukherjee, Reza Derakhshani

Generative AI has revolutionized modern machine learning by providing unprecedented realism, diversity, and efficiency in data generation. This technology holds immense potential for biometrics, including for securing sensitive and personally identifiable information. Given the irrevocability of biometric samples and mounting privacy concerns, biometric temp

Kohei Hattori, Hikaru Watanabe, Junta Iguchi, Takuya Nomoto

We develop an efficient real-time simulation method for the spin-charge coupled system in the velocity gauge. This method enables us to compute the real-time simulation for the two-dimensional system with the complex spin texture. We focus on the effect of the collective excitation of the localized spins on the electronic transport properties of the non-triv

Mannan Saeed Muhammad, Estrella Montero

Autonomous navigation capabilities play a critical role in service robots operating in environments where human interactions are pivotal, due to the dynamic and unpredictable nature of these environments. However, the variability in human behavior presents a substantial challenge for robots in predicting and anticipating movements, particularly in crowded sc

Lekbir Afraites, Julius Fergy Tiongson Rabago

This study revisits the problem of identifying the unknown interior Robin boundary of a connected domain using Cauchy data from the exterior region of a harmonic function. It investigates two shape optimization reformulations employing least-squares boundary-data-tracking cost functionals. Firstly, it rigorously addresses the existence of optimal shape solut