April 2023 arXiv papers — page 127

Fabio Santos, Joseph Vargovich, Bianca Trinkenreich, Italo Santos

Labeling issues with the skills required to complete them can help contributors to choose tasks in Open Source Software projects. However, manually labeling issues is time-consuming and error-prone, and current automated approaches are mostly limited to classifying issues as bugs/non-bugs. We investigate the feasibility and relevance of automatically labelin

Xiaohui Gao

Ionization is one of the most fundamental processes in intense laser-matter interaction. It is extremely efficient for clusters in laser fields and often leads to surprisingly high charge states at moderate laser intensities. Here we reveal a novel ionization mechanism in laser-cluster interaction through particle-in-cell simulations. As the laser field ioni

Seongmoon Jun, Joonyun Kim, Minho Choi, Byungsu Kim

Perovskite nanocrystals (NCs) have attracted increasing interest for the realization of single-photon emitters, owing to their ease of chemical synthesis, wide spectral tunability, fast recombination rate, scalability, and high quantum yield. However, the integration of a single perovskite NC into a photonic structure is yet to be accomplished. We successful

Tamitake Itoh, Yuko S. Yamamoto

In non-relativistic quantum electrodynamics, an electromagnetic (EM) interaction between a photon and a molecular exciton can be expressed by a Ap term and A^2 term, where A and p are the operators of the vector potential of the EM field and the momentum of the exciton, respectively. We developed a method for investigating the contribution of the Ap and A^2

Kensuke Yoshida, Taro Toyoizumi

Sleep is considered to play an essential role in memory reorganization. Despite its importance, classical theoretical models did not focus on some sleep characteristics. Here, we review recent theoretical approaches investigating their roles in learning and discuss the possibility that non-rapid eye movement (NREM) sleep selectively consolidates memory, and

Zdenek Sekanina

Noting that the extensive astrometric observations of the double comet Wirtanen (C/1956 F1) made by E. Roemer have never been published, I replicate the contents of a fortuitously discovered copy of her measurement records of the companion's offsets from the main mass in 1957-1959 and use with such data by others to refine the fragmentation solution. The sub

Martin Bunder, Joseph Tonien

In this paper, we study the linear space of all two-sided generalized Fibonacci sequences $\{F_n\}_{n \in \mathbb{Z}}$ that satisfy the recurrence equation of order $k$: $F_n = F_{n-1} + F_{n-2} + \dots + F_{n-k}$. We give two types of explicit formula, one is based on generalized binomial coefficients and the other based on generalized multinomial coefficie

Alexandru Rusescu, Brooke Lampe, Weizhi Meng

Companies that have an online presence-in particular, companies that are exclusively digital-often subscribe to this business model: collect data from the user base, then expose the data to advertisement agencies in order to turn a profit. Such companies routinely market a service as "free", while obfuscating the fact that they tend to "charge" users in the

Jevgeni Tarassov, Nicolas Houlié

In this study, we investigate the BTC price time-series (17 August 2010-27 June 2021) and show that the 2017 pricing episode is not unique. We describe at least ten new events, which occurred since 2010-2011 and span more than five orders of price magnitudes ($US 1-$US 60k). We find that those events have a similar duration of approx. 50-100 days. Although w

Tae Gab Ha, Seyun Kim

In this paper, we consider the following attraction repulsion chemotaxis model with nonlinear signal term: \begin{align*} &u_{t}=\nabla \cdot(\nabla u-\xi_{1} u \nabla v +\xi_{2} u \nabla w), \quad &0=\Delta v -\lambda_{1}v +f_{1}(u), \quad &0=\Delta w -\lambda_{2}w +f_{2}(u), \quad x \in \mathbb{R}^{N}, t>0, \end{align*} where $\xi_{1},\xi_{2},\lambda_{1},\

Conor Atkins, Benjamin Zi Hao Zhao, Hassan Jameel Asghar, Ian Wood

One of the new developments in chit-chat bots is a long-term memory mechanism that remembers information from past conversations for increasing engagement and consistency of responses. The bot is designed to extract knowledge of personal nature from their conversation partner, e.g., stating preference for a particular color. In this paper, we show that this

Chen Feng Tsai, Xiaochen Zhou, Sierra S. Liu, Jing Li

Large language models (LLMs) such as ChatGPT and GPT-4 have recently demonstrated their remarkable abilities of communicating with human users. In this technical report, we take an initiative to investigate their capacities of playing text games, in which a player has to understand the environment and respond to situations by having dialogues with the game w

Yuhao Huang, Sanping Zhou, Junjie Zhang, Jinpeng Dong

Efficient representation of point clouds is fundamental for LiDAR-based 3D object detection. While recent grid-based detectors often encode point clouds into either voxels or pillars, the distinctions between these approaches remain underexplored. In this paper, we quantify the differences between the current encoding paradigms and highlight the limited vert

R. E. Smail, M. Batelaan, R. Horsley, Y. Nakamura

At the TeV scale, low-energy precision observations of neutron characteristics provide unique probes of novel physics. Precision studies of neutron decay observables are susceptible to beyond the Standard Model (BSM) tensor and scalar interactions, while the neutron electric dipole moment, $d_n$, also has high sensitivity to new BSM CP-violating interactions

Shi Jin, Nana Liu

Quantum simulation is known to be capable of simulating certain dynamical systems in continuous time -- Schrodinger's equations being the most direct and well-known -- more efficiently than classical simulation. Any linear dynamical system can in fact be transformed into a system of Schrodinger's equations via a method called Schrodingerisation. Building on

John S. Caughman, Ari J. Herman, Taiyo S. Terada

For any non-negative integers $v > k > i$, the {\em generalized Johnson graph}, $J(v,k,i)$, is the undirected simple graph whose vertices are the $k$-subsets of a $v$-set, and where any two vertices $A$ and $B$ are adjacent whenever $|A \cap B| =i$. In this article, we derive formulas for the girth, odd girth, distance function, and diameter of $J(v,k,i)$.

Ali Khezeli

In this work, we define the notion of unimodular random measured metric spaces as a common generalization of various other notions. This includes the discrete cases like unimodular graphs and stationary point processes, as well as the non-discrete cases like stationary random measures and the continuum metric spaces arising as scaling limits of graphs. We pr

Sambhavi Tiwari, Manas Gogoi, Shekhar Verma, Krishna Pratap Singh

Meta-learning aims to solve unseen tasks with few labelled instances. Nevertheless, despite its effectiveness for quick learning in existing optimization-based methods, it has several flaws. Inconsequential connections are frequently seen during meta-training, which results in an over-parameterized neural network. Because of this, meta-testing observes unnec

Emma J. Pretty, Renan Guarese, Haytham M. Fayek, Fabio Zambetta

Replicability is absent in games research; a lack of transparency in protocol detail hinders scientific consensus and willingness to publish public datasets, impacting the application of these techniques in video games research. To combat this, we propose and give an example of the use of a set of experimental considerations, such as games and materials choi

Tao Gao, Yuanbo Wen, Kaihao Zhang, Peng Cheng

Rain-by-snow weather removal is a specialized task in weather-degraded image restoration aiming to eliminate coexisting rain streaks and snow particles. In this paper, we propose RSFormer, an efficient and effective Transformer that addresses this challenge. Initially, we explore the proximity of convolution networks (ConvNets) and vision Transformers (ViTs)

Zhengzhong Tu, Peyman Milanfar, Hossein Talebi

Image resizing operation is a fundamental preprocessing module in modern computer vision. Throughout the deep learning revolution, researchers have overlooked the potential of alternative resizing methods beyond the commonly used resizers that are readily available, such as nearest-neighbors, bilinear, and bicubic. The key question of our interest is whether

Azal Ahmad Khan, Omkar Chaudhari, Rohitash Chandra

Class imbalance (CI) in classification problems arises when the number of observations belonging to one class is lower than the other. Ensemble learning combines multiple models to obtain a robust model and has been prominently used with data augmentation methods to address class imbalance problems. In the last decade, a number of strategies have been added

Diego A. Gómez-Espinoza, Sergio Torres-Flores, Verónica Firpo, Philippe Amram

We present, for the first time, spatially resolved spectroscopy for the entire Hickson Compact Group 31 obtained with the MUSE instrument at the VLT,and an in-depth analysis of this compact group. To obtain a complete understanding of the system, we derived radial velocity and dispersion velocity maps, maps of the ionization mechanism of the system, chemical

Yutong Huang, Shengshi Pang

A quantum computer encodes information in quantum states and runs quantum algorithms to surpass the classical counterparts by exploiting quantum superposition and quantum correlation. Grover's quantum search algorithm is a typical quantum algorithm that proves the superiority of quantum computing over classical computing. It has a quadratic reduction in the

Ramkrishna Mishan

High penetration of distributed generators (DG) in modern power grids creates angle, voltage, and frequency instabilities. Most of the work in the literature has focused on small-signal stability analysis of single grid-connected inverters without thoroughly investigating their transient stability for large disturbances and interactions between parallel-conn

Maozhou Huang

We define successive minimal bases (SMBs) for the space of $u^{n}$-division points of a Drinfeld $\mathbb{F}_{q}[t]$-module over a local field, where $u$ is a finite prime of $\mathbb{F}_{q}[t]$ and $n$ is a positive integer. These SMBs share similar properties to those of SMBs of the lattices associated to Drinfeld modules. We study the relations between th

Yang Jin, Yongzhi Li, Zehuan Yuan, Yadong Mu

This paper aims to establish a generic multi-modal foundation model that has the scalable capability to massive downstream applications in E-commerce. Recently, large-scale vision-language pretraining approaches have achieved remarkable advances in the general domain. However, due to the significant differences between natural and product images, directly ap

Jessica S. Velasco, Jomer V. Catipon, Edmund G. Monilar, Villamor M. Amon

Automatic classification of skin disease plays an important role in healthcare especially in dermatology. Dermatologists can determine different skin diseases with the help of an android device and with the use of Artificial Intelligence. Deep learning requires a lot of time to train due to the number of sequential layers and input data involved. Powerful co

Borui Cai, Guangyan Huang, Shuiqiao Yang, Yong Xiang

Shapelets that discriminate time series using local features (subsequences) are promising for time series clustering. Existing time series clustering methods may fail to capture representative shapelets because they discover shapelets from a large pool of uninformative subsequences, and thus result in low clustering accuracy. This paper proposes a Semi-super

Huu-Dinh Huynh, Wen-Han Hwang

A class of occupancy models for detection/non-detection data is proposed to relax the closure assumption of N$-$mixture models. We introduce a community parameter $c$, ranging from $0$ to $1$, which characterizes a certain portion of individuals being fixed across multiple visits. As a result, when $c$ equals $1$, the model reduces to the N$-$mixture model;

Kazuki Nakazawa, Koujiro Hoshi, Jotaro J. Nakane, Jun-ichiro Ohe

Spin Hall effect of spin-texture origin is explored theoretically for antiferromagnetic (AF) metals. It is found that a vector chirality formed by the N\'eel vector gives rise to a topological spin Hall effect. This is topological since it is proportional to the winding number counted by in-plane vector chirality along the sample edge, which can be nonvanish

Erik Englesson, Amir Mehrpanah, Hossein Azizpour

A natural way of estimating heteroscedastic label noise in regression is to model the observed (potentially noisy) target as a sample from a normal distribution, whose parameters can be learned by minimizing the negative log-likelihood. This formulation has desirable loss attenuation properties, as it reduces the contribution of high-error examples. Intuitiv

Lei Qi, Dongjia Zhao, Yinghuan Shi, Xin Geng

Despite the significant success of deep learning in computer vision tasks, cross-domain tasks still present a challenge in which the model's performance will degrade when the training set and the test set follow different distributions. Most existing methods employ adversarial learning or instance normalization for achieving data augmentation to solve this t

Jonas Ngnawe, Marianne Abemgnigni Njifon, Jonathan Heek, Yann Dauphin

Deep networks have achieved impressive results on a range of well-curated benchmark datasets. Surprisingly, their performance remains sensitive to perturbations that have little effect on human performance. In this work, we propose a novel extension of Mixup called Robustmix that regularizes networks to classify based on lower-frequency spatial features. We

Shreyank N Gowda

Generalized Zero-Shot Learning (GZSL) has emerged as a pivotal research domain in computer vision, owing to its capability to recognize objects that have not been seen during training. Despite the significant progress achieved by generative techniques in converting traditional GZSL to fully supervised learning, they tend to generate a large number of synthet

Xunyu Zhu, Jian Li, Yong Liu, Weiping Wang

Neural Architectures Search (NAS) becomes more and more popular over these years. However, NAS-generated models tends to suffer greater vulnerability to various malicious attacks. Lots of robust NAS methods leverage adversarial training to enhance the robustness of NAS-generated models, however, they neglected the nature accuracy of NAS-generated models. In

Yuya Hattori, Shunsuke Yoshizawa, Keisuke Sagisaka, Yuki Tokumoto

Scanning tunneling microscopy and transport measurements have been performed to investigate the electronic structure and its temperature dependence in heavily Sr and Na codoped PbTe, which is recognized as one of the most promising thermoelectric materials. Our main findings are as follows: (i) Below T=4.5 K, all carriers are distributed in the first valence

Yu-Xin Wu, Jin-Fu Chen, Ji-Hui Pei, Fan Zhang

The stochastic thermodynamics of systems with a few degrees of freedom has been studied extensively so far. We would like to extend the study to systems with more degrees of freedom and even further-continuous fields with infinite degrees of freedom. The simplest case for a continuous stochastic field is the Edwards-Wilkinson elastic manifold. It is an exact

Ivan May-Cen, Ricardo Legarda-Saenz, Carlos Brito-Loeza

In this paper, we introduce a total variation based variational model for denoising wrapped phase images. Our model improves on former methods by preserving discontinuities of the phase map and enforcing the fundamental Pythagorean trigonometric identity between the real and imaginary parts of the phase map enhancing the quality of the restored phase. The ex

Zhijie Deng, Yucen Luo

Unsupervised semantic segmentation is a long-standing challenge in computer vision with great significance. Spectral clustering is a theoretically grounded solution to it where the spectral embeddings for pixels are computed to construct distinct clusters. Despite recent progress in enhancing spectral clustering with powerful pre-trained models, current appr

Yite Wang, Dawei Li, Ruoyu Sun

Pruning neural networks before training has received increasing interest due to its potential to reduce training time and memory. One popular method is to prune the connections based on a certain metric, but it is not entirely clear what metric is the best choice. Recent advances in neural tangent kernel (NTK) theory suggest that the training dynamics of lar

Madiha Zahrah Choksi, David Goedicke

Intelligent or generative writing tools rely on large language models that recognize, summarize, translate, and predict content. This position paper probes the copyright interests of open data sets used to train large language models (LLMs). Our paper asks, how do LLMs trained on open data sets circumvent the copyright interests of the used data? We start by

Nan Wang, Xuezhi Wen, Dalin Zhang, Xibin Zhao

APT detection is difficult to detect due to the long-term latency, covert and slow multistage attack patterns of Advanced Persistent Threat (APT). To tackle these issues, we propose TBDetector, a transformer-based advanced persistent threat detection method for APT attack detection. Considering that provenance graphs provide rich historical information and h

P. Darriulat, D. T. Hoai, P. T. Nhung, P. N. Diep

The commonly accepted mechanism governing the formation of the nascent wind in oxygen-rich AGB stars combines an initial boost above the photosphere, given by shock waves resulting from stellar pulsations and convective cell granulation, with a subsequent acceleration fuelled by the radiation pressure of the star on dust grains. We use six nearby stars, for

Thomas Z. Li, John M. Still, Kaiwen Xu, Ho Hin Lee

The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic health records (EHRs). However, clinically routine modalities such as imaging and diagnostic codes can be asynchronous and irregularly sampled over different time scales which are obs

Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui

With the greater emphasis on privacy and security in our society, the problem of graph unlearning -- revoking the influence of specific data on the trained GNN model, is drawing increasing attention. However, ranging from machine unlearning to recently emerged graph unlearning methods, existing efforts either resort to retraining paradigm, or perform approxi

Jinsol Lee, Charlie Lehman, Mohit Prabhushankar, Ghassan AlRegib

We analyze the data-dependent capacity of neural networks and assess anomalies in inputs from the perspective of networks during inference. The notion of data-dependent capacity allows for analyzing the knowledge base of a model populated by learned features from training data. We define purview as the additional capacity necessary to characterize inference

Anas Gouda, Moritz Roidl

How can we segment varying numbers of objects where each specific object represents its own separate class? To make the problem even more realistic, how can we add and delete classes on the fly without retraining or fine-tuning? This is the case of robotic applications where no datasets of the objects exist or application that includes thousands of objects (

Xinyue Li, Jian Wang, Wei Song, Yanling Du

The mainstream researche in deep metric learning can be divided into two genres: proxy-based and pair-based methods. Proxy-based methods have attracted extensive attention due to the lower training complexity and fast network convergence. However, these methods have limitations as the poxy optimization is done by network, which makes it challenging for the p

Qiong Wu, Siyuan Wang, Pingyi Fan, Qiang Fan

In the traditional vehicular network, computing tasks generated by the vehicles are usually uploaded to the cloud for processing. However, since task offloading toward the cloud will cause a large delay, vehicular edge computing (VEC) is introduced to avoid such a problem and improve the whole system performance, where a roadside unit (RSU) with certain comp

STAR Collaboration

We report directed flow ($v_1$) of multistrange baryons ($\Xi$ and $\Omega$) and improved $v_1$ data for $K^{-}$, $\bar{p}$, $\bar{\Lambda}$ and $\phi$ in Au+Au collisions at $\sqrt{s_{\mathrm{NN}}}=$27 and 200 GeV from the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). We focus on particles whose constituent quarks are not transported from t

Zichong Ou, Chenyang Qiu, Dandan Wang, Jie Lu

In this paper, we develop a distributed mixing-accelerated primal-dual proximal algorithm, referred to as MAP-Pro, which enables nodes in multi-agent networks to cooperatively minimize the sum of their nonconvex, smooth local cost functions in a decentralized fashion. The proposed algorithm is constructed upon minimizing a computationally inexpensive augment

Ali Kazemi Arani, Mansooreh Zahedi, Triet Huynh Minh Le, Muhammad Ali Babar

Continuous Integration (CI) has become a well-established software development practice for automatically and continuously integrating code changes during software development. An increasing number of Machine Learning (ML) based approaches for automation of CI phases are being reported in the literature. It is timely and relevant to provide a Systemization o

Noa Garcia, Yusuke Hirota, Yankun Wu, Yuta Nakashima

The increasing tendency to collect large and uncurated datasets to train vision-and-language models has raised concerns about fair representations. It is known that even small but manually annotated datasets, such as MSCOCO, are affected by societal bias. This problem, far from being solved, may be getting worse with data crawled from the Internet without mu

Hoigi Seo, Hayeon Kim, Gwanghyun Kim, Se Young Chun

The increasing demand for high-quality 3D content creation has motivated the development of automated methods for creating 3D object models from a single image and/or from a text prompt. However, the reconstructed 3D objects using state-of-the-art image-to-3D methods still exhibit low correspondence to the given image and low multi-view consistency. Recent s

Xiong Liu, Rongchun Ge, Xinrui Li, Jinglei Du

All-optical information communication, processing and computation have received substantial interest of both fundamental and applied research due to its unrivaled speed and broad bandwidth. Compared to its electronic counterpart, photons seldom interact with each other which makes them obtain a long coherence time on one hand and relieved from heavy energy d

Phillip A. Kerger, David E. Bernal Neira, Zoe Gonzalez Izquierdo, Eleanor G. Rieffel

The CONGEST and CONGEST-CLIQUE models have been carefully studied to represent situations where the communication bandwidth between processors in a network is severely limited. Messages of only $O(log(n))$ bits of information each may be sent between processors in each round. The quantum versions of these models allow the processors instead to communicate an

Wenqian Xing, Shixiang Zhu, Yao Xie

Motivated by the operations of the Atlanta Police Department, where heavy workloads and staffing shortages increasingly require units to patrol across overlapping service regions, we develop a generalized hypercube queueing model, extending Larson (1974), for spatial service systems with overlapping coverage. Designing effective service regions requires capt

Jeffrey S. Case, Eric Chen, Yi Wang, Paul Yang

We discuss the solution of the Neumann problem associated with the CR Yamabe operator on a subset $\Omega$ of the CR manifold $\mathbb{S}^3$ bounded by the Clifford torus $\Sigma$. We also discuss the Yamabe-type problem of finding a contact form on $\Omega$ which has zero Tanaka--Webster scalar curvature and for which $\Sigma$ has constant $p$-mean curvatur

Avinash Bhat, Disha Shrivastava, Jin L. C. Guo

Despite the potential of Large Language Models (LLMs) as writing assistants, they are plagued by issues like coherence and fluency of the model output, trustworthiness, ownership of the generated content, and predictability of model performance, thereby limiting their usability. In this position paper, we propose to adopt Norman's seven stages of action as a

L. D. Blokhintsev, A. S. Kadyrov, A. M. Mukhamedzhanov, D. A. Savin

Asymptotic normalization coefficients (ANC) determine the overall normalization of cross sections of peripheral radiative capture reactions. In a recent paper [Blokhintsev et al., Eur. Phys. J. A 58, 257 (2022)], we considered the ANC $C_0$ for the virtual decay $^{16}$O$(0^+; 6.05$ MeV)$\to \alpha+^{12}$C(g.s.). In the present paper, which can be regarded a

Arnaldo Rodriguez-Gonzalez

This work describes the way that topological mixing and chaos in continua, as induced by discrete dynamical systems, can or can't be understood through topological conjugacy with symbolic dynamical systems. For example, there is no symbolic dynamical system that is topologically conjugate to any discrete dynamical system on an entire continuum, and there is

Zheyuan Zhu, Joe H. Doerr, Guifang Li, Shuo Pang

Multi-plane light converter (MPLC) designs supporting hundreds of modes are attractive in high-throughput optical communications. These photonic structures typically comprise >10 phase masks in free space, with millions of independent design parameters. Conventional MPLC design using wavefront matching updates one mask at a time while fixing the rest. Here w

Weixin Liang, Mert Yuksekgonul, Yining Mao, Eric Wu

The rapid adoption of generative language models has brought about substantial advancements in digital communication, while simultaneously raising concerns regarding the potential misuse of AI-generated content. Although numerous detection methods have been proposed to differentiate between AI and human-generated content, the fairness and robustness of these

Mario Ghossoub, Giulio Principi, Lorenzo Stanca

We provide a Sandwich Theorem (K\"onig (1972)) for positively homogeneous functionals that satisfy additivity only on a restricted domain. Our relaxation of additivity is based on a binary relation called convex-conic symmetric preorder, whereby additivity is restricted to all couples of elements that belong to such relation. We then study applications of ou

Ilia Ponomarenko, Andrey V. Vasil'ev

Let $m\ge 3$ be an integer. It is proved that the $m$-closure of a given solvable permutation group of degree $n$ can be constructed in time $n^{O(m)}$.

Shengwen Gan

We introduce small cap square function estimates for parabola and cone, and prove the sharp estimates. More precisely, we study the inequalities of form \[ \|f\|_p\le C_{\alpha,p}(R) \Big\|(\sum_{\gamma\in\Gamma_\alpha(R^{-1})}|f_\gamma|^2)^{1/2}\Big\|_p, \] where $\Gamma_\alpha(R^{-1})$ is the set of small caps of width $R^{-\alpha}$. We find the sharp cons

Cheongho Han, Andrew Gould, Youn Kil Jung, Ian A. Bond

We investigate the data collected by the high-cadence microlensing surveys during the 2022 season in search for planetary signals appearing in the light curves of microlensing events. From this search, we find that the lensing event MOA-2022-BLG-249 exhibits a brief positive anomaly that lasted for about 1 day with a maximum deviation of $\sim 0.2$~mag from

Wei Chen, HongWei Xu, Jelo Wang

We present a high-precision real-time facial animation pipeline suitable for animators to use on their desktops. This pipeline is about to be launched in FACEGOOD's Avatary\footnote{https://www.avatary.com/} software, which will accelerate animators' productivity. The pipeline differs from professional head-mounted facial capture solutions in that it only re

Pengyuan Lu, Ivan Ruchkin, Matthew Cleaveland, Oleg Sokolsky

Models of actual causality leverage domain knowledge to generate convincing diagnoses of events that caused an outcome. It is promising to apply these models to diagnose and repair run-time property violations in cyber-physical systems (CPS) with learning-enabled components (LEC). However, given the high diversity and complexity of LECs, it is challenging to

Katherine Stasaski, Marti A. Hearst

Linguistic pragmatics state that a conversation's underlying speech acts can constrain the type of response which is appropriate at each turn in the conversation. When generating dialogue responses, neural dialogue agents struggle to produce diverse responses. Currently, dialogue diversity is assessed using automatic metrics, but the underlying speech acts d

Muhammad Usman, Milos Ercegovac, Jeong-A Lee

Multiplication is indispensable and is one of the core operations in many modern applications including signal processing and neural networks. Conventional right-to-left (RL) multiplier extensively contributes to the power consumption, area utilization and critical path delay in such applications. This paper proposes a low latency multiplier based on online

Haoyang Zheng, Yao Huang, Ziyang Huang, Wenrui Hao

Due to the complex behavior arising from non-uniqueness, symmetry, and bifurcations in the solution space, solving inverse problems of nonlinear differential equations (DEs) with multiple solutions is a challenging task. To address this, we propose homotopy physics-informed neural networks (HomPINNs), a novel framework that leverages homotopy continuation an

Kurt Thomas, Sarah Meiklejohn, Michael A. Specter, Xiang Wang

With the accelerated adoption of end-to-end encryption, there is an opportunity to re-architect security and anti-abuse primitives in a manner that preserves new privacy expectations. In this paper, we consider two novel protocols for on-device blocklisting that allow a client to determine whether an object (e.g., URL, document, image, etc.) is harmful based

Zhangju Liu, Yunhe Sheng

In this paper, first we introduce the notion of an omni-representation of a Leibniz algebra $\g$ on a vector space $V$ as a Leibniz algebra homomorphism from $\g$ to the omni-Lie algebra $\gl(V)\oplus V$. Then we introduce the omni-cohomology theory associated to omni-representations and establish the relation between omni-cohomology groups and Loday-Pirashv

Qingsong Gu, Xueping Huang, Yuhua Sun

Let $M$ be a complete non-compact Riemannian manifold and $\sigma $ be a Radon measure on $M$, we study the existence and non-existence of positive solutions to a nonlocal elliptic inequality \begin{equation*} (-\Delta)^{\alpha} u\geq u^{q}\sigma\quad \text{in}\,\,M, \end{equation*} with $q>1$. When the Green function $G^{(\alpha)}$ of the fractional Laplaci

Takeshi Isobe, Tian Xu

This paper is part of a program to establish the existence theory for the conformally invariant Dirac equation \[ D_{\textit{g}}\psi=f(x)|\psi|_{\textit{g}}^{\frac2{m-1}}\psi \] on a closed spin manifold $(M,\textit{g})$ of dimension $m\geq2$ with a fixed spin structure, where $f:M\to\mathbb{R}$ is a given function. The study on such nonlinear equation is mo

Haotao Wang, Ziyu Jiang, Yuning You, Yan Han

Graph neural networks (GNNs) have found extensive applications in learning from graph data. However, real-world graphs often possess diverse structures and comprise nodes and edges of varying types. To bolster the generalization capacity of GNNs, it has become customary to augment training graph structures through techniques like graph augmentations and larg

Qilong Guo, Pengxin Liu, Chen Li, Dong Sun

In the hybrid RANS-LES simulations, proper turbulent fluctuations should be added at the RANS-to-LES interface to drive the numerical solution restoring to a physically resolved turbulence as rapidly as possible. Such turbulence generation methods mostly need to know the distribution of the characteristic length scale of the background RANS model, which is i

Heyou Liu, Muhammad Salman Bashir, Mohamed-Slim Alouini

For acquisition of narrow-beam free-space optical (FSO) terminals, a Global Positioning System (GPS) is typically required for coarse localization of the terminal. However, the GPS signal may be shadowed, or may not be present at all, especially in rough or unnameable terrains. In this study, we propose a lidar-assisted acquisition of an unmanned aerial vehi

Jiwon Chung, Joon Hyeop Lee, Hyunjin Jeong, Suk Kim

The presence of transitional dwarf galaxies in filaments and cluster outskirts may be closely related to pre-processing in the filament; however, the underlying mechanism is not yet comprehensively understood. We present the spatially resolved chemical and kinematical properties of three blue-cored dwarf early-type galaxies (dE(bc)s) in the Virgo cluster and

Che Chen Tho, San-Dong Guo, Shi-Jun Liang, Wee-Liat Ong

Recent experimental synthesis of ambient-stable MoSi2N4 monolayer have garnered enormous research interests. The intercalation morphology of MoSi2N4 - composed of a transition metal nitride (Mo-N) inner sub-monolayer sandwiched by two silicon nitride (Si-N) outer sub-monolayers - have motivated the computational discovery of an expansive family of synthetic

Fangping Xie, Pierre Le Meur, Charith Fernando

Planning from demonstrations has shown promising results with the advances of deep neural networks. One of the most popular real-world applications is automated handwriting using a robotic manipulator. Classically it is simplified as a two-dimension problem. This representation is suitable for elementary drawings, but it is not sufficient for Japanese callig

Siyi Zhou, Luca Luceri, Emilio Ferrara

The COVID-19 pandemic has intensified numerous social issues that warrant academic investigation. Although information dissemination has been extensively studied, the silenced voices and censored content also merit attention due to their role in mobilizing social movements. In this paper, we provide empirical evidence to explore the relationships among COVID

Jingkun Guo, Jin Chang, Xiong Yao, Simon Gröblacher

Preparing a massive mechanical resonator in a state with quantum limited motional energy provides a promising platform for studying fundamental physics with macroscopic systems and allows to realize a variety of applications, including precise sensing. While several demonstrations of such ground-state cooled systems have been achieved, in particular in sideb

Laya Rafiee Sevyeri, Ivaxi Sheth, Farhood Farahnak, Alexandre See

While neural networks are capable of achieving human-like performance in many tasks such as image classification, the impressive performance of each model is limited to its own dataset. Source-free domain adaptation (SFDA) was introduced to address knowledge transfer between different domains in the absence of source data, thus, increasing data privacy. Dive

Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rares Ambrus

Differentiable volumetric rendering is a powerful paradigm for 3D reconstruction and novel view synthesis. However, standard volume rendering approaches struggle with degenerate geometries in the case of limited viewpoint diversity, a common scenario in robotics applications. In this work, we propose to use the multi-view photometric objective from the self-

Xin Hu, Yu Tian, Keisuke Nagato, Masayuki Nakao

Recent advancements in Natural Language Processing have opened up new possibilities for the development of large language models like ChatGPT, which can facilitate knowledge management in the design process by providing designers with access to a vast array of relevant information. However, integrating ChatGPT into the design process also presents new challe

Mehran Makhtoumi

Satellites are subject to various severe vibration during different phases of flight. The concept of satellite smart adapter is proposed in this study to achieve active vibration control of launch vehicle on satellite. The satellite smart adapter has 18 active struts in which the middle section of each strut is made of piezoelectric stack actuator. Comprehen

Sucheol Shin, Guang Shi, D. Thirumalai

Contact probabilities between loci, separated by arbitrary genomic distance, for a number of cell types have been reported using genome-wide chromosome conformation capture (Hi-C) experiments. How to extract the effective interaction energies between active euchromatin (A) and inactive heterochromatin (B) directly from the experimental data, without an under

Roberto Morán-Tovar, Michael Lässig

The immune response to an acute primary infection is a coupled process of antigen proliferation, molecular recognition by naive B cells, and their subsequent proliferation and antibody shedding. This process contains a fundamental problem: the recognition of an exponentially time-dependent antigen signal. Here we show that B cells can efficiently recognise n

Rowina S. Nathan, Matthew T. Miles, Gregory Ashton, Paul D. Lasky

Precision pulsar timing is integral to the detection of the nanohertz stochastic gravitational-wave background as well as understanding the physics of neutron stars. Conventional pulsar timing often uses fixed time and frequency-averaged templates to determine the pulse times of arrival, which can lead to reduced accuracy when the pulse profile evolves over

Alireza Askarian, Jaesang Park, Srinivasa Salapaka

This paper presents an extensive framework focused on the control design, along with stability and performance analysis, of Grid-Following Inverters (GFL). It aims to ensure their effective operation under both stiff and weak grid conditions. The proposed framework leverages the coupled algebraic structure of the transmission line dynamics in the $dq$ frame

Jörn Callies, Wenbo Wu, Shirui Peng, Zhongwen Zhan

Seismically generated sound waves that propagate through the ocean are used to infer temperature anomalies and their vertical structure in the deep East Indian Ocean. These T waves are generated by earthquakes off Sumatra and received by hydrophone stations off Diego Garcia and Cape Leeuwin. Between repeating earthquakes, a T wave's travel time changes in re

Tiantian Zhang, Mira Maiwöger, Filippo Borselli, Yevhenii Kuriatnikov

Quantum simulators built from ultracold atoms promise to study quantum phenomena in interacting many-body systems. However, it remains a challenge to experimentally prepare strongly correlated continuous systems such that the properties are dominated by quantum fluctuations. Here, we show how to enhance the quantum correlations in a one-dimensional multimode

Nic Fellini, M. Ram Murty

In this article, we present streamlined proofs of results of Ankeny, Artin, and Chowla concerning the fundamental unit of the real quadratic field $\mathbb{Q}(\sqrt{p})$ for primes $p\equiv 1 \bmod{4}$ while providing a generalization of their conjecture. Using our generalization, we relate Fermat quotients of quadratic non-residues $\bmod{p}$ to sums of har

Kota Hattori

We generalize the notion of calibrated submanifolds to smooth maps and show that the several examples of smooth maps appearing in the differential geometry become the examples of our situation. Moreover, we apply these notion to give the lower bound to the energy of smooth maps in the given homotopy class between Riemannian manifolds, and consider the energy

Pavlos Fragkogiannis, Martina Forster, Grace E. Lee, Dell Zhang

For many business applications that require the processing, indexing, and retrieval of professional documents such as legal briefs (in PDF format etc.), it is often essential to classify the pages of any given document into their corresponding types beforehand. Most existing studies in the field of document image classification either focus on single-page do

Zhenting Wang, Kai Mei, Juan Zhai, Shiqing Ma

The backdoor attack, where the adversary uses inputs stamped with triggers (e.g., a patch) to activate pre-planted malicious behaviors, is a severe threat to Deep Neural Network (DNN) models. Trigger inversion is an effective way of identifying backdoor models and understanding embedded adversarial behaviors. A challenge of trigger inversion is that there ar

Marcellus Amadeus, Paulo Branco

Improving machine learning performance while increasing model generalization has been a constantly pursued goal by AI researchers. Data augmentation techniques are often used towards achieving this target, and most of its evaluation is made using English corpora. In this work, we took advantage of different existing data augmentation methods to analyze their