March 2024 arXiv papers — page 48

Lin Zhao, Tianchen Zhao, Zinan Lin, Xuefei Ning

In recent years, there has been significant progress in the development of text-to-image generative models. Evaluating the quality of the generative models is one essential step in the development process. Unfortunately, the evaluation process could consume a significant amount of computational resources, making the required periodic evaluation of model perf

Yunjia Xi, Weiwen Liu, Jianghao Lin, Chuhan Wu

The rise of large language models (LLMs) has opened new opportunities in Recommender Systems (RSs) by enhancing user behavior modeling and content understanding. However, current approaches that integrate LLMs into RSs solely utilize either LLM or conventional recommender model (CRM) to generate final recommendations, without considering which data segments

Shafiuddin Rehan Ahmed, George Arthur Baker, Evi Judge, Michael Regan

Event Coreference Resolution (ECR) as a pairwise mention classification task is expensive both for automated systems and manual annotations. The task's quadratic difficulty is exacerbated when using Large Language Models (LLMs), making prompt engineering for ECR prohibitively costly. In this work, we propose a graphical representation of events, X-AMR, ancho

Seokhyun Chung, Raed Al Kontar

Building a predictive model that rapidly adapts to real-time condition monitoring (CM) signals is critical for engineering systems/units. Unfortunately, many current methods suffer from a trade-off between representation power and agility in online settings. For instance, parametric methods that assume an underlying functional form for CM signals facilitate

Hao Ai, Lin Wang

360 depth estimation has recently received great attention for 3D reconstruction owing to its omnidirectional field of view (FoV). Recent approaches are predominantly focused on cross-projection fusion with geometry-based re-projection: they fuse 360 images with equirectangular projection (ERP) and another projection type, e.g., cubemap projection to estimat

Yuan You, Shuang-Nan Zhang, Zhaosheng Li, Mingyu Ge

MAXI J1816-195 is an accreting millisecond X-ray pulsar (AMXP) discovered in 2022. According to the Insight-HXMT data, the pulsations of this source extend all the way to over 100 keV, and its pulse profiles change from a single peak in low-energy range to double peaks in high-energy range. In this work, we simulate its energy spectra and pulse profiles with

Yinke Dong, Haifeng Yuan, Hongkun Liu, Wei Jing

Accurate motion prediction of pedestrians, cyclists, and other surrounding vehicles (all called agents) is very important for autonomous driving. Most existing works capture map information through an one-stage interaction with map by vector-based attention, to provide map constraints for social interaction and multi-modal differentiation. However, these met

Fujun Hou

By relaxing the dominating set in three ways (e.g., from "each member beats every non-member" to "each member beats or ties every non-member, with an additional requirement that at least one member beat every non-member"), we propose a new social welfare function, which satisfies a number of desirable properties including Condorcet winner principle, Condorce

Chanho Park, H. Vincent Poor, Namyoon Lee

Distributed learning is commonly used for accelerating model training by harnessing the computational capabilities of multiple-edge devices. However, in practical applications, the communication delay emerges as a bottleneck due to the substantial information exchange required between workers and a central parameter server. SignSGD with majority voting (sign

Jiyuan Yang, Yuanzi Li, Jingyu Zhao, Hanbing Wang

Sequential Recommenders have been widely applied in various online services, aiming to model users' dynamic interests from their sequential interactions. With users increasingly engaging with online platforms, vast amounts of lifelong user behavioral sequences have been generated. However, existing sequential recommender models often struggle to handle such

Weiming Zhang, Yexin Liu, Xu Zheng, Lin Wang

This paper tackles a novel yet challenging problem: how to transfer knowledge from the emerging Segment Anything Model (SAM) -- which reveals impressive zero-shot instance segmentation capacity -- to learn a compact panoramic semantic segmentation model, i.e., student, without requiring any labeled data. This poses considerable challenges due to SAM's inabil

Yiyang Mei

Since its introduction in 2022, Generative AI has significantly impacted the art world, from winning state art fairs to creating complex videos from simple prompts. Amid this renaissance, a pivotal issue emerges: should users of Generative AI be recognized as authors eligible for copyright protection? The Copyright Office, in its March 2023 Guidance, argues

Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky

Robust reinforcement learning agents using high-dimensional observations must be able to identify relevant state features amidst many exogeneous distractors. A representation that captures controllability identifies these state elements by determining what affects agent control. While methods such as inverse dynamics and mutual information capture controllab

Quan Zhang, Xiaoyu Liu, Wei Li, Hanting Chen

In image restoration (IR), leveraging semantic priors from segmentation models has been a common approach to improve performance. The recent segment anything model (SAM) has emerged as a powerful tool for extracting advanced semantic priors to enhance IR tasks. However, the computational cost of SAM is prohibitive for IR, compared to existing smaller IR mode

Xiangyi Meng, Nicolò Lo Piparo, Kae Nemoto, István A. Kovács

Building large-scale quantum communication networks has its unique challenges. Here, we demonstrate that a network-wide synergistic usage of quantum memories distributed in a quantum communication network offers a fundamental advantage. We first map the problem of quantum communication with local usage of memories into a classical continuum percolation model

Sunan Sun, Nadia Figueroa

Linear Parameter Varying Dynamical Systems (LPV-DS) encode trajectories into an autonomous first-order DS that enables reactive responses to perturbations, while ensuring globally asymptotic stability at the target. However, the current LPV-DS framework is established on Euclidean data only and has not been applicable to broader robotic applications requirin

Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam Fowl

Modern neural networks are often trained on massive datasets that are web scraped with minimal human inspection. As a result of this insecure curation pipeline, an adversary can poison or backdoor the resulting model by uploading malicious data to the internet and waiting for a victim to scrape and train on it. Existing approaches for creating poisons and ba

Tomoya Tachinami, Yuuiti Sendouda

We study the structure of static spherical stars composed of non-relativistic matter in linear massive gravity with or without the Fierz-Pauli (FP) tuning. Adopting a polytropic equation of state, we construct master differential equations for the stellar profile function, which is fourth order in the FP theory or sixth order in generic non-FP theories, wher

Yihao Qin, Shangwen Wang, Yiling Lou, Jinhao Dong

Fault Localization (FL) is an essential step during the debugging process. With the strong capabilities of code comprehension, the recent Large Language Models (LLMs) have demonstrated promising performance in diagnosing bugs in the code. Nevertheless, due to LLMs' limited performance in handling long contexts, existing LLM-based fault localization remains o

Ziheng Deng, Hua Chen, Yongzheng Zhou, Haibo Hu

Four-dimensional cone-beam computed tomography (4D CBCT) provides respiration-resolved images and can be used for image-guided radiation therapy. However, the ability to reveal respiratory motion comes at the cost of image artifacts. As raw projection data are sorted into multiple respiratory phases, the cone-beam projections become much sparser and the reco

Talia Fernós

We revisit the topic of probability measures on CAT(0) cube complexes and prove that an amenable group acting on a CAT(0) cube complex, regardless of dimension, necessarily preserves an interval in the Roller compactification. In the finite dimensional case, we prove that there must be an orbit of cardinality $2^N$, where $N$ is bounded by the dimension. Thi

Eugene Stephane Mananga

The Floquet-Magnus and Fer expansion schemes were introduced in solid-state nuclear magnetic resonance (NMR) in 2011 and 2006, respectively. Key features of the Floquet magnus expansion are its ability to account for the calculations developed in a finite-dimensional Hilbert space instead of an infinite-dimensional space within the Floquet theory as well as

Xiaoyan Kui, Haonan Yan, Qinsong Li, Liming Chen

Graph neural networks have achieved remarkable success in learning graph representations, especially graph Transformer, which has recently shown superior performance on various graph mining tasks. However, graph Transformer generally treats nodes as tokens, which results in quadratic complexity regarding the number of nodes during self-attention computation.

Antonios-Alexandros Robotis

We study varieties $\mathcal{A}_n$ arising as equivariant compactifications of the space of $n$ points in $\mathbb{C}$ up to overall translation. We define $\mathcal{A}_n$ and examine its basic geometric properties before constructing an isomorphism to an augmented wonderful variety. We show that $\mathcal{A}_n$ is in a canonical way a resolution of the spac

Kasidit Muenprasitivej, Jesse Jiang, Abdulaziz Shamsah, Samuel Coogan

We study the problem of bipedal robot navigation in complex environments with uncertain and rough terrain. In particular, we consider a scenario in which the robot is expected to reach a desired goal location by traversing an environment with uncertain terrain elevation. Such terrain uncertainties induce not only untraversable regions but also robot motion p

Shuai Wang, Li-Hua Shao

Dislocation is a very important one-dimensional defect in ferroelectrics. This work introduces an easy and flexible model of implementing the edge dislocation by introducing eigenstrain at the interface, and it could be easily extended to incorporate the surface stress to refine the analysis of ferroelectric thin films. The influence of dislocations on the f

Kyla H. Levin, Nicolas van Kempen, Emery D. Berger, Stephen N. Freund

Debugging is a critical but challenging task for programmers. This paper proposes ChatDBG, an AI-powered debugging assistant. ChatDBG integrates large language models (LLMs) to significantly enhance the capabilities and user-friendliness of conventional debuggers. ChatDBG lets programmers engage in a collaborative dialogue with the debugger, allowing them to

Zeyu Hao, Yuan Fang, Xianghao Yu, Jie Xu

This paper investigates the energy-efficient hybrid beamforming design for a multi-functional integrated sensing, communications, and powering (ISCAP) system. In this system, a base station (BS) with a hybrid analog-digital (HAD) architecture sends unified wireless signals to communicate with multiple information receivers (IRs), sense multiple point targets

Danyal Ahmad, Marco Donatelli, Mariarosa Mazza, Stefano Serra-Capizzano

In the past decades, a remarkable amount of research has been carried out regarding fast solvers for large linear systems resulting from various discretizations of fractional differential equations (FDEs). In the current work, we focus on multigrid methods for a Riesz-space FDE whose theoretical convergence analysis of such multigrids is currently limited to

Yang Wang, Zhibin Gao, Xiaoying Wang, Jinping Sun

Noble gas atoms such as Kr and Xe are byproducts of nuclear fission in nuclear plants. How to trap and confine these volatile even radioactive gases is particularly challenging. Recent studies have shown that they can be trapped in nanocages of ultrathin silica. Here, we exhibit with self-consistent phonon theory and four-phonon (4ph) scattering where the ad

Dongwei Gan, Ming Chang, Juan Chen

Medical image segmentation (MIS) aims to finely segment various organs. It requires grasping global information from both parts and the entire image for better segmenting, and clinically there are often certain requirements for segmentation efficiency. Convolutional neural networks (CNNs) have made considerable achievements in MIS. However, they are difficul

Juho Leppänen

We adapt Stein's method to obtain Berry--Esseen type error bounds in the multivariate central limit theorem for non-stationary processes generated by time-dependent compositions of uniformly expanding dynamical systems. In a particular case of random dynamical systems with a strongly mixing base transformation, we derive an error estimate of order $O(N^{-1/2

Wojciech Młotkowski, Nobuaki Obata

We derive a general formula for the quadratic embedding constant of a graph join $\bar{K}_m+G$, where $\bar{K}_m$ is the empty graph on $m\ge1$ vertices and $G$ is an arbitrary graph. Applying our formula to a fan graph $K_1+P_n$, where $K_1=\bar{K}_1$ is the singleton graph and $P_n$ is the path on $n\ge1$ vertices, we show that $\mathrm{QEC}(K_1+P_n)=-\til

Minaoar Hossain Tanzil, Junaed Younus Khan, Gias Uddin

We conducted a survey of 135 software engineering (SE) practitioners to understand how they use Generative AI-based chatbots like ChatGPT for SE tasks. We find that they want to use ChatGPT for SE tasks like software library selection but often worry about the truthfulness of ChatGPT responses. We developed a suite of techniques and a tool called CID (ChatGP

Jamal El Qars, Benachir Boukhris, Ahmed Tirbiyine, Abdelaziz Labrag

Quantum steering refers to the apparent possibility of exploiting nonseparable quantum correlations to remotely influence the quantum state of an observer via local measurements. Different from entanglement and Bell nonlocality, quantum steering exhibits an inherent asymmetric property, which makes it relevant for many asymmetric quantum information processi

Joosung Lee, Jinhong Kim

In information retrieval, facet identification of a user query is an important task. If a search service can recognize the facets of a user's query, it has the potential to offer users a much broader range of search results. Previous studies can enhance facet prediction by leveraging retrieved documents and related queries obtained through a search engine. H

Ahmad Ali Khan, Raviraj Adve

Improving throughput for cell-edge users through coordinated resource allocation has been a long-standing driver of research in wireless cellular networks. While a variety of wireless resource management problems focus on sum utility, max-min utility and proportional fair utility, these formulations do not explicitly cater to cell-edge users and can, in fact

Ahmad Ali Khan, Raviraj Adve

Part I of this two-part paper focused on the formulation of percentile problems, complexity analysis, and development of power control algorithms via the quadratic fractional transform (QFT) and logarithmic fractional transform (LFT) for sum-least-qth-percentile (SLqP) rate maximization problems. In this second part, we first tackle the significantly more ch

Thomas Moran, Susanne Pumpluen

Let $F$ be a field of characteristic not 2 or 3. The first Tits construction is a well-known tripling process to construct separable cubic Jordan algebras, especially Albert algebras. We generalize the first Tits construction by choosing the scalar employed in the tripling process outside of the base field. This yields a new family of nonassociative unital a

Avik Pal, Flemming Holtorf, Axel Larsson, Torkel Loman

Efficiently solving nonlinear equations underpins numerous scientific and engineering disciplines, yet scaling these solutions for challenging system models remains a challenge. This paper presents NonlinearSolve.jl -- a suite of high-performance open-source nonlinear equation solvers implemented natively in the Julia programming language. NonlinearSolve.jl

Judah Van Zandt, Erik Petigura

We present \texttt{ethraid}, an open source Python package designed to measure the mass ($m_c$) and separation ($a$) of a bound companion from measurements covering a fraction of the orbital period. \texttt{ethraid} constrains $m_c$ and $a$ by jointly modeling radial velocity (RV), astrometric, and/or direct imaging data in a Bayesian framework. Partial orbi

Chon-Fai Kam, Zhong-Tang Wu

Entanglement, a puzzle since Einstein's time, has become increasingly crucial with the rise of quantum computation. But what exactly is it? Historically , entanglement can be precisely defined, but only negatively. In this article, we explore four interconnected definitions of entangled states.

Madhumitha Sakthi, Louis Kerofsky, Varun Ravi Kumar, Senthil Yogamani

Autonomous driving systems require extensive data collection schemes to cover the diverse scenarios needed for building a robust and safe system. The data volumes are in the order of Exabytes and have to be stored for a long period of time (i.e., more than 10 years of the vehicle's life cycle). Lossless compression doesn't provide sufficient compression rati

Nikolai Krivulin

We consider a discrete best approximation problem formulated in the framework of tropical algebra, which deals with the theory and applications of algebraic systems with idempotent operations. Given a set of samples of input and output of an unknown function, the problem is to construct a generalized tropical Puiseux polynomial that best approximates the fun

John C. Duchi, Suyash Gupta, Kuanhao Jiang, Pragya Sur

We address the challenge of constructing valid confidence intervals and sets in problems of prediction across multiple environments. We investigate two types of coverage suitable for these problems, extending the jackknife and split-conformal methods to show how to obtain distribution-free coverage in such non-traditional, potentially hierarchical data-gener

Yasamin Medghalchi, Niloufar Zakariaei, Arman Rahmim, Ilker Hacihaliloglu

The effectiveness of Deep Neural Networks (DNNs) heavily relies on the abundance and accuracy of available training data. However, collecting and annotating data on a large scale is often both costly and time-intensive, particularly in medical cases where practitioners are already occupied with their duties. Moreover, ensuring that the model remains robust a

Qin Tian, Wenjun Wang, Chen Zhao, Minglai Shao

Traditional machine learning methods heavily rely on the independent and identically distribution assumption, which imposes limitations when the test distribution deviates from the training distribution. To address this crucial issue, out-of-distribution (OOD) generalization, which aims to achieve satisfactory generalization performance when faced with unkno

T. L. Campante, H. Kjeldsen, Y. Li, M. N. Lund

Fuelled by space photometry, asteroseismology is vastly benefitting the study of cool main-sequence stars, which exhibit convection-driven solar-like oscillations. Even so, the tiny oscillation amplitudes in K dwarfs continue to pose a challenge to space-based asteroseismology. A viable alternative is offered by the lower stellar noise over the oscillation t

Kaike Ping, Anisha Kumar, Xiaohan Ding, Eugenia Rho

Current research mainly explores the attributes and impact of online counterspeech, leaving a gap in understanding of who engages in online counterspeech or what motivates or deters users from participating. To investigate this, we surveyed 458 English-speaking U.S. participants, analyzing key motivations and barriers underlying online counterspeech engageme

Henning U. Voss, Douglas J. Ballon

It is shown on the examples of Moore and Gosper curves that two spatially shifted or twisted, pre-asymptotic space-filling curves can produce large-scale superstructures akin to moiré patterns. To study physical phenomena emerging from these patterns, a geometrical coupling coefficient based on the Neumann integral is introduced. It is found that moiré patte

I. Yu. Rybak, C. J. A. P. Martins, Patrick Peter, E. P. S. Shellard

We continue our studies of the evolution and cosmological consequences of current-carrying cosmic string networks, described by a charge-velocity-dependent one scale (CVOS) model. We present a detailed calculation of the effects of these networks on the cosmic microwave background (CMB), in the context of this model, and specifically discuss how such current

Hanzhi Yin, Gang Cheng, Christian J. Steinmetz, Ruibin Yuan

We describe a novel approach for developing realistic digital models of dynamic range compressors for digital audio production by analyzing their analog prototypes. While realistic digital dynamic compressors are potentially useful for many applications, the design process is challenging because the compressors operate nonlinearly over long time scales. Our

Vladimir Yu. Protasov, Rinat Kamalov

We address the problem of the best uniform approximation by linear combinations of a finite system of functions. If the system is Chebyshev and the problem is unconstrained, then the classical Remez algorithm provides a fast and precise solution. For non-Chebyshev systems, this problem may offer a great resistance. The same happens to approximations under li

Matthew Scott, Asimina Mertzani, Ciske Smit, Stefan Sarkadi

Self-organising multi-agent systems regulate their components' behaviour voluntarily, according to a set of socially-constructed, mutually-agreed, and mutable social arrangements. In some systems, these arrangements may be applied with a frequency, at a scale and within implicit cost constraints such that performance becomes a pressing issue. This paper intr

Joydeep Chowdhury, Subhajit Dutta, Marc G. Genton

Asymptotic methods for hypothesis testing in high-dimensional data usually require the dimension of the observations to increase to infinity, often with an additional condition on its rate of increase compared to the sample size. On the other hand, multivariate asymptotic methods are valid for fixed dimension only, and their practical implementations in hypo

Andrew Walter, Shimeng Wu, Andy M. Tyrrell, Liam McDaid

Artificial Neural Networks (ANNs) are one of the most widely employed forms of bio-inspired computation. However the current trend is for ANNs to be structurally homogeneous. Furthermore, this structural homogeneity requires the application of complex training and learning tools that produce application specific ANNs, susceptible to pitfalls such as overfitt

Valentina Kiritchenko, Michael Tsfasman, Serge Vladuts, Ilya Zakharevich

Quadratic residue patterns modulo a prime are studied since 19th century. In the first part we extend existing results on the number of consecutive $\ell$-tuples of quadratic residues, studying corresponding algebraic curves and their jacobians, which happen to be products of jacobians of hyperelliptic curves. In the second part we state the last unpublished

Makoto Katori, Pierre Lazag, Tomoyuki Shirai

We define the accumulated spectrogram associated to a locally trace class orthogonal projection operator and to a bounded set using the polar decomposition of its restriction on that set and prove a convergence theorem for accumulated spectrograms along an exhaustion in the case when the corresponding determinantal point process is hyperuniform. We prove tha

Trung Chau, Selvi Kara, Kyle Wang

In this paper, we prove that the path ideals of both paths and cycles have minimal cellular resolutions. Specifically, these minimal free resolutions coincide with the Barile-Macchia resolutions for paths, and their generalized counterparts for cycles. Furthermore, we identify edge ideals of cycles as a class of ideals that lack a minimal Barile-Macchia reso

Carla Farsi, Frederic Latremoliere, Judith Packer

We address the natural question: as noncommutative solenoids are inductive limits of quantum tori, do the standard spectral triples on quantum tori converge to some spectral triple on noncommutative solenoid for the spectral propinquity? We answer this question by showing that, using appropriate bounded perturbation of the spectral triples on quantum tori, s

Igor Spiridonov

Let $\phi \in {\rm Mod}(\Sigma)$ be an arbitrary element of the mapping class group of a closed orientable surface $\Sigma$ of genus at least $2$. For any characteristic cover $\widetilde{\Sigma} \to \Sigma$ one can consider the linear subspace ${\rm H}_1^{f.o.}(\widetilde{\Sigma}, \mathbb{Q})^\phi \subseteq {\rm H}_1(\widetilde{\Sigma}, \mathbb{Q})$ consist

Nahid Binandeh Dehaghani, A. Pedro Aguiar, Rafal Wisniewski

We propose an optimal control strategy to generate maximally entangled states in bipartite quantum systems. Leveraging the Pontryagin Principle, we derive time-dependent control fields that maximize the entanglement measure, specifically concurrence, within minimal time while adhering to input constraints. Our formulation addresses the Liouville-von Neumann

Toshihiro Nishimura, Yosuke Suzuki, Tokuo Tsuj, Tetsuyou Watanabe

This study proposes a novel robotic gripper with variable grasping configurations for grasping various objects. The fingers of the developed gripper incorporate multiple different surfaces. The gripper possesses the function of altering the finger surfaces facing a target object by rotating the fingers in its longitudinal direction. In the proposed design eq

Noga Alon

We observe that several vertex Tur\'an type problems for the hypercube that received a considerable amount of attention in the combinatorial community are equivalent to questions about erasure list-decodable codes. Analyzing a recent construction of Ellis, Ivan and Leader, and determining the Tur\'an density of certain hypergraph augemntations we obtain impr

Cedric Perauer, Laurenz Adrian Heidrich, Haifan Zhang, Matthias Nießner

Recently, progress in acquisition equipment such as LiDAR sensors has enabled sensing increasingly spacious outdoor 3D environments. Making sense of such 3D acquisitions requires fine-grained scene understanding, such as constructing instance-based 3D scene segmentations. Commonly, a neural network is trained for this task; however, this requires access to a

Jelena Diakonikolas, Cristóbal Guzmán

We initiate the study of nonsmooth optimization problems under bounded local subgradient variation, which postulates bounded difference between (sub)gradients in small local regions around points, in either average or maximum sense. The resulting class of objective functions encapsulates the classes of objective functions traditionally studied in optimizatio

Thorsten Heidersdorf, George Tyriard

Two different types of Deligne categories have been defined to interpolate the finite dimensional complex representations of the hyperoctahedral group. The first one, initially defined by Knop and then further studied by Likeng and Savage, uses a categorical analogue of the permutation representation as a tensor generator. The second one, due to Flake and Ma

M. A. Hosain, J. -M. Le Floch, J. Krupka, M. E. Tobar

The impurity paramagnetic ion, $Cu^{2+}$ substitutes $Al$ in the $SrLaAlO_4$ single crystal lattice, this results in a $CuO_6$ elongated octahedron, the resulting measured g-factors shows four-fold axes variation condition. The aggregate frequency width of the electron spin resonance with the required minimum level of impurity concentration has been evaluate

Kleitos Papadopoulos

In this paper, we study the single-item economic lot-sizing problem with production cost functions that are piecewise linear. The lot-sizing problem stands as a foundational cornerstone within the domain of lot-sizing problems. It is also applicable to a variety of important production planning problems which are special cases to it according to \cite{ou}. T

Yihong Zhou, Chaimaa Essayeh, Thomas Morstyn

The growing demand for electrified heating, electrified transportation, and power-intensive data centres challenge distribution networks. If electrification projects are carried out without considering electrical distribution infrastructure, there could be unexpected blackouts and financial losses. Datasets containing real-world distribution network informat

Pankaj K. Agarwal, Xiao Hu, Stavros Sintos, Jun Yang

Finding patterns in graphs is a fundamental problem in databases and data mining. In many applications, graphs are temporal and evolve over time, so we are interested in finding durable patterns, such as triangles and paths, which persist over a long time. While there has been work on finding durable simple patterns, existing algorithms do not have provable

Hailey L. Johnson, Audra Sterling, Bilge Mutlu

Assistive technologies for adults with Down syndrome (DS) need designs tailored to their specific technology requirements. While prior research has explored technology design for individuals with intellectual disabilities, little is understood about the needs and expectations of adults with DS. Assistive technologies should leverage the abilities and interes

Mariana da Cruz, Diane Castonguay, Celina de Figueiredo, Diana Sasaki

A total coloring of a graph colors all its elements, vertices and edges, with no adjacency conflicts. The Total Coloring Conjecture (TCC) is a sixty year old challenge, says that every graph admits a total coloring with at most maximum degree plus two colors, and many graph parameters have been studied in connection with its validity. If a graph admits a tot

Andrey Blinov, Alonso Delfín, Ellen Weld

It is known that the multiplier algebra of an approximately unital and nondegenerate $L^p$-operator algebra is again an $L^p$-operator algebra. In this paper we investigate examples that drop both hypotheses. In particular, we show that the multiplier algebra of $T_2^p$, the algebra of strictly upper triangular $2 \times 2$ matrices acting on $\ell_2^p$, is

Alessandro Granelli

This review provides a succinct overview of the basic aspects of neutrino physics. The topics covered include: neutrinos in the standard model and the three-neutrino mixing scheme; the current status of neutrino oscillation measurements and what remains to be determined; the seesaw mechanisms for neutrino mass generation and the associated phenomenology, inc

Duc-Tri Vo, Ionela Prodan, Laurent Lefèvre, Vincent Vanel

This paper addresses the particularities in optimal control of the uranium extraction-scrubbing operation in the PUREX process. The control problem requires optimally stabilizing the system at a desired solvent saturation level, guaranteeing constraints, disturbance rejection, and adapting to set point variations. A qualified simulator named PAREX was develo

H. Harry Asada, Jose A. Solano-Castellanos

The modeling of nonlinear dynamics based on Koopman operator theory, which is originally applicable only to autonomous systems with no control, is extended to non-autonomous control system without approximation to input matrix B. Prevailing methods using a least square estimate of the B matrix may result in an erroneous input matrix, misinforming the control

Joost van der Heijden

The performance and accuracy of quantum electronics is substantially degraded when the temperature of the electrons in the devices is too high. The electron temperature can be reduced with appropriate thermal anchoring and by filtering both the low frequency and radio frequency noise. Ultimately, for high performance filters the electron temperature can appr

Sourya Dipta Das, Yash Vadi, Kuldeep Yadav

Automated Essay Scoring (AES) systems are widely popular in the market as they constitute a cost-effective and time-effective option for grading systems. Nevertheless, many studies have demonstrated that the AES system fails to assign lower grades to irrelevant responses. Thus, detecting the off-topic response in automated essay scoring is crucial in practic

Omar Alrawi, Miuyin Yong Wong, Athanasios Avgetidis, Kevin Valakuzhy

Malware sandboxes provide many benefits for security applications, but they are complex. These complexities can overwhelm new users in different research areas and make it difficult to select, configure, and use sandboxes. Even worse, incorrectly using sandboxes can have a negative impact on security applications. In this paper, we address this knowledge gap

Tarun Suresh, Shubham Ugare, Gagandeep Singh, Sasa Misailovic

We present the first in depth study on the robustness of existing watermarking techniques applied to code generated by large language models (LLMs). As LLMs increasingly contribute to software development, watermarking has emerged as a potential solution for detecting AI generated code and mitigating misuse, such as plagiarism or the automated generation of

kaiko. ai, Nanne Aben, Edwin D. de Jong, Ioannis Gatopoulos

Driven by the recent advances in deep learning methods and, in particular, by the development of modern self-supervised learning algorithms, increased interest and efforts have been devoted to build foundation models (FMs) for medical images. In this work, we present our scalable training pipeline for large pathology imaging data, and a comprehensive analysi

Huizi Yu, Lizhou Fan, Lingyao Li, Jiayan Zhou

Large Language Models (LLMs) have rapidly become important tools in Biomedical and Health Informatics (BHI), enabling new ways to analyze data, treat patients, and conduct research. This study aims to provide a comprehensive overview of LLM applications in BHI, highlighting their transformative potential and addressing the associated ethical and practical ch

Naoya Kumagai, Kenshiro Oguri

We address the problem of finite-horizon control of a discrete-time linear system, where the initial state distribution follows a Gaussian mixture model, the terminal state must follow a specified Gaussian distribution, and the state and control inputs must obey chance constraints. We show that, throughout the time horizon, the state and control distribution

Yao Kang, Xin Wang, Zhiling Lan

High-radix interconnects such as Dragonfly and its variants rely on adaptive routing to balance network traffic for optimum performance. Ideally, adaptive routing attempts to forward packets between minimal and non-minimal paths with the least congestion. In practice, current adaptive routing algorithms estimate routing path congestion based on local informa

Jasur Shukurov

With the ever-growing expansion of mobile technology worldwide, there is an increasing need for accommodation for those who are disabled. This project explores how machine learning and computer vision could be utilized to improve accessibility for people with visual impairments. There have been many attempts to develop various software that would improve acc

Lauran Toussaint, Florian Zeiser

We compute the formal Poisson cohomology groups of a real Poisson structure $\pi$ on $\mathbb{C}^2$ associated to the Lefschetz singularity $(z_1, z_2)\mapsto z_1^2+z_2^2$. In particular we correct an erroneous computation in the literature. The definition of $\pi$ depends on a choice of volume form. Using the main result we formally classify all Poisson str

M. A. Hosain, J-M. Le Floch, J. Krupka, M. E. Tobar

Impurity $Fe^{3+}$ ion electron spin resonance (ESR) spectroscopy using multiple dielectric modes in a $SrTiO_3$ dielectric resonator has been performed with a tuneable DC magnetic field of up to $1.6~T$. The $Ti^{4+}(d^0)$ ion is substituted by $Fe^{3+}$ ion forming $FeO_6$ octahedral complex with an iron-oxygen-vacancy $(Fe^{3+}-V_O)$. In such a metal-liga

Boyang Li, Yuping Fan, Matthew Dearing, Zhiling Lan

Emerging workloads in high-performance computing (HPC) are embracing significant changes, such as having diverse resource requirements instead of being CPU-centric. This advancement forces cluster schedulers to consider multiple schedulable resources during decision-making. Existing scheduling studies rely on heuristic or optimization methods, which are limi

Anamitra Chaudhuri, Georgios Fellouris, Ali Tajer

This paper considers the problem of sequentially detecting a change in the joint distribution of multiple data sources under a sampling constraint. Specifically, the channels or sources generate observations that are independent over time, but not necessarily independent at any given time instant. The sources follow an initial joint distribution, and at an u

Elham Daadmehr

Due to the variety of corporate risks in turmoil markets and the consequent financial distress especially in COVID-19 time, this paper investigates corporate resilience and compares different types of resilience that can be potential sources of heterogeneity in firms' implied rate of return. Specifically, the novelty is not only to quantify firms' financial

Ashish Chouhan, Michael Gertz

With the increase in legislative documents at the EU, the number of new terms and their definitions is increasing as well. As per the Joint Practical Guide of the European Parliament, the Council and the Commission, terms used in legal documents shall be consistent, and identical concepts shall be expressed without departing from their meaning in ordinary, l

Cemal Tugrul Yilmaz, Mamadou Diagne, Miroslav Krstic

Our recently developed "unbiased" extremum seeking (uES) algorithms ensure perfect convergence to the optimum at a user-assigned exponential rate or, more powerfully, within a user-prescribed time. Unlike classical approach, these algorithms use time-varying adaptation and controller gains, along with constant or time-varying probing frequencies (chirp signa

Boyang Li, Zhiling Lan, Michael E. Papka

In the field of high-performance computing (HPC), there has been recent exploration into the use of deep reinforcement learning for cluster scheduling (DRL scheduling), which has demonstrated promising outcomes. However, a significant challenge arises from the lack of interpretability in deep neural networks (DNN), rendering them as black-box models to syste

Christopher Wewer, Kevin Raj, Eddy Ilg, Bernt Schiele

We present latentSplat, a method to predict semantic Gaussians in a 3D latent space that can be splatted and decoded by a light-weight generative 2D architecture. Existing methods for generalizable 3D reconstruction either do not scale to large scenes and resolutions, or are limited to interpolation of close input views. latentSplat combines the strengths of

Siddharth Jha, Zichen Gui, Benjamin Delbos, Richard Moreau

In modern medical diagnostics, magnetic resonance imaging (MRI) is an important technique that provides detailed insights into anatomical structures. In this paper, we present a comprehensive methodology focusing on streamlining the segmentation, reconstruction, and visualization process of 3D MRI data. Segmentation involves the extraction of anatomical regi

Noé Zapata, Gerardo Pérez, Lucas Bonilla, Pedro Núñez

For robots to interact socially, they must interpret human intentions and anticipate their potential outcomes accurately. This is particularly important for social robots designed for human care, which may face potentially dangerous situations for people, such as unseen obstacles in their way, that should be avoided. This paper explores the Artificial Theory

Ali Nouri, Beatriz Cabrero-Daniel, Fredrik Törner, Hȧkan Sivencrona

Changes and updates in the requirement artifacts, which can be frequent in the automotive domain, are a challenge for SafetyOps. Large Language Models (LLMs), with their impressive natural language understanding and generating capabilities, can play a key role in automatically refining and decomposing requirements after each update. In this study, we propose

Yao Kang, Xin Wang, Zhiling Lan

Dragonfly interconnect is a crucial network technology for supercomputers. To support exascale systems, network resources are shared such that links and routers are not dedicated to any node pair. While link utilization is increased, workload performance is often offset by network contention. Recently, intelligent routing built on reinforcement learning demo

Ankit Agrawal, Philipp Zech, Michael Vierhauser

Failures in safety-critical Cyber-Physical Systems (CPS), both software and hardware-related, can lead to severe incidents impacting physical infrastructure or even harming humans. As a result, extensive simulations and field tests need to be conducted, as part of the verification and validation of system requirements, to ensure system safety. However, curre