October 2022 arXiv papers — page 138

Zeyu Gao, Yao Mu, Chen Chen, Jingliang Duan

End-to-end autonomous driving provides a feasible way to automatically maximize overall driving system performance by directly mapping the raw pixels from a front-facing camera to control signals. Recent advanced methods construct a latent world model to map the high dimensional observations into compact latent space. However, the latent states embedded by t

Sergey A. Melikhov

We use a triple-point version of the Whitney trick to show that ornaments of three orientable $(2k-1)$-manifolds in $\mathbb R^{3k-1}$, $k>2$, are classified by the $\mu$-invariant. A very similar (but not identical) construction was found independently by I. Mabillard and U. Wagner, who also made it work in a much more general situation and obtained impress

Sergey A. Melikhov

We present a short proof of S. Parsa's theorem that there exists a compact $n$-polyhedron $P$, $n\ge 2$, non-embeddable in $\mathbb R^{2n}$, such that $P*P$ embeds in $\mathbb R^{4n+2}$. This proof can serve as a showcase for the use of geometric cohomology. We also show that a compact $n$-polyhedron $X$ embeds in $\mathbb R^m$, $m\ge\frac{3(n+1)}2$, if eith

Yabo Xiao, Xiaojuan Wang, Dongdong Yu, Kai Su

Multi-person pose estimation generally follows top-down and bottom-up paradigms. Both of them use an extra stage ($\boldsymbol{e.g.,}$ human detection in top-down paradigm or grouping process in bottom-up paradigm) to build the relationship between the human instance and corresponding keypoints, thus leading to the high computation cost and redundant two-sta

Shuyuan Zhang, Jichen Sun, Shengkang Chen

Huffman coding is well known to be useful in certain decision problems involving minimizing the average number of (freely chosen) queries to determine an unknown random variable. However, in problems where the queries are more constrained, the original Huffman coding no longer works. In this paper, we proposed a general model to describe such problems and tw

Therdpong Daengsi

This article aims to present the results from a study of the quality of service of 5G networks provided by two major 5G network providers, using a field trial approach within 60 BTS SkyTrain stations. The results obtained from the tests using 4 applications on a 5G mobile phone showed that the performance of 5G networks provided by both operators are differe

Gadi Fibich, Amit Golan, Steve Schochet

We introduce a new method for proving the convergence and the rate of convergence of discrete Bass models on various networks to their respective compartmental Bass models, as the population size $M$ becomes infinite. In this method, the full set of master equations is reduced to a smaller system of equations, which is closed and exact. The reduced finite sy

Taesoo Song, Ilia Grishmanovskii, Olga Soloveva

We apply the Low's theorem to soft gluon emission from heavy quark scattering in the nonperturbative strongly interacting quark-gluon plasma (sQGP). The sQGP is described in terms of the dynamical quasi-particles and adjusted to reproduce the EoS from lQCD at finite temperature and chemical potential. Since the emitted gluon is soft and of long wavelength, i

Ahmed Gaber

We solve the two Diophantine equations $P_k=J_n+J_m$ and $Q_k=J_n+J_m$ where $\left\lbrace P_{k}\right\rbrace_{k\geq0}$, $\left\lbrace Q_{k}\right\rbrace_{k\geq0}$ and $\left\lbrace J_{k}\right\rbrace_{k\geq0}$ are the sequences of Pell numbers, Pell-Lucas numbers and Jacobsthal numbers, respectively. The main tool is the theory of linear forms in logarithms

Diluka Moratuwage, Changbeom Shim, Yuthika Punchihewa

Multi-target state estimation refers to estimating the number of targets and their trajectories in a surveillance area using measurements contaminated with noise and clutter. In the Bayesian paradigm, the most common approach to multi-target estimation is by recursively propagating the multi-target filtering density, updating it with current measurements set

Taesoo Song

Assuming that quark and antiquark numbers are separately conserved during hadronization, we calculate Bremsstrahlung photon from a hadronizing quark-gluon plasma. The quark and antiquark numbers are obtained from the hadron numbers in the statistical model and the transition amplitudes for the hadronization from the constraint that all quarks and antiquarks

Xinwei Yu, Xiaohua Zhang

For the current 3D human pose estimation task, a group of methods mainly learn the rules of 2D-3D projection from spatial and temporal correlation. However, earlier methods model the global features of the entire body joint in the time domain, but ignore the motion trajectory of individual joint. The recent work [29] considers that there are differences in m

Ziyuan Ye, Youzhi Qu, Zhichao Liang, Mo Wang

Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and neural engineering. However, existing machine learning methods for fMRI-based brain decoding either suffer from low classification performance or poor explainability. Here, we address this issue by proposing a biologically inspired architect

Christos Bakalis, Andrew Benwell, Daron Chabot, Lawrence Doolittle

LCLS-II is currently in its commissioning phase at SLAC. It is an X-ray FEL driven by a CW superconducting LINAC. The beam injector plays a crucial role in the overall performance of the accelerator, and is critical to the final electron beam performance parameters. The LCLS-II injector comprises of a 185.7 MHz VHF copper gun cavity, and a 1.3 GHz two-cell L

Ismael Delgado Gaspar, Thomas Buchert, Jan J. Ostrowski

We develop a new nonlinear method to model structure formation in general relativity from a generalization of the relativistic Lagrangian perturbation schemes, controlled by Szekeres (and LTB) exact solutions. The overall approach can be interpreted as the evolution of a deformation field on an inhomogeneous reference model, obeying locally Friedmann-like eq

Antoine Ducros, Ehud Hrushovski, François Loeser, Jinhe Ye

We prove a general finiteness statement for the ordered abelian group of tropical functions on skeleta in Berkovich analytifications of algebraic varieties. Our approach consists in working in the framework of stable completions of algebraic varieties, a model-theoretic version of Berkovich analytifications, for which we prove a similar result, of which the

Forough Shahab Samani, Rolf Stadler

We present a framework that lets a service provider achieve end-to-end management objectives under varying load. Dynamic control actions are performed by a reinforcement learning (RL) agent. Our work includes experimentation and evaluation on a laboratory testbed where we have implemented basic information services on a service mesh supported by the Istio an

Raghul Parthipan, Damon J. Wischik

How can we learn from all available data when training machine-learnt climate models, without incurring any extra cost at simulation time? Typically, the training data comprises coarse-grained high-resolution data. But only keeping this coarse-grained data means the rest of the high-resolution data is thrown out. We use a transfer learning approach, which ca

Bo Wang, Dong-Ze He, Ling-Feng Wang, Hai-Li Li

We explore the constraints on cosmological parameters in interacting dark energy (IDE) models described by energy transfer rates $Q = \beta H \rho_{\rm de}$ and $Q = \beta H \rho_{\rm c}$, using simulated gravitational-wave (GW) bright siren data from pulsar timing arrays (PTAs) and the Planck 2018 cosmic microwave background (CMB) data. In particular, we si

Cunxiao Du, Zhaopeng Tu, Longyue Wang, Jing Jiang

Recently, a new training oaxe loss has proven effective to ameliorate the effect of multimodality for non-autoregressive translation (NAT), which removes the penalty of word order errors in the standard cross-entropy loss. Starting from the intuition that reordering generally occurs between phrases, we extend oaxe by only allowing reordering between ngram ph

Piergiorgio Ladisa, Henrik Plate, Matias Martinez, Olivier Barais

Open-source software supply chain attacks aim at infecting downstream users by poisoning open-source packages. The common way of consuming such artifacts is through package repositories and the development of vetting strategies to detect such attacks is ongoing research. Despite its popularity, the Java ecosystem is the less explored one in the context of su

Francisco Estrada, José Holanda

Here, we study the magneto-optical interactions in magnetic structures considering the dependence of the interactions with the magnetic field. We perform numerical simulations in a structure of magnetic nanowires, considering them as one chain of strongly interacting single-domain particles. Robustly, we obtain a quantitative value for the interactions, whic

Jeffrey Shallit

In a recent talk of Robbert Fokkink, some conjectures related to the infinite Tribonacci word were stated by the speaker and the audience. In this note we show how to prove (or disprove) the claims easily in a "purely mechanical" fashion, using the Walnut theorem-prover.

Niels Feld

We prove that the Chow-Witt group of zero-cycles is a birational invariant of smooth proper schemes over a base field.

Yuxia Geng, Jiaoyan Chen, Jeff Z. Pan, Mingyang Chen

In knowledge graph completion (KGC), predicting triples involving emerging entities and/or relations, which are unseen when the KG embeddings are learned, has become a critical challenge. Subgraph reasoning with message passing is a promising and popular solution. Some recent methods have achieved good performance, but they (i) usually can only predict tripl

M. Kretlow

Outer main belt asteroid (223) Rosa is a possible flyby target of opportunity for ESA's (European Space Agency) JUpiter ICy moons Explorer (JUICE) mission when passing the asteroid belt on the way to Jupiter. The very low albedo and the featureless red spectra indicate a P-type asteroid in the Tholen taxonomy, though the yet known bulk density did not match

Asahi Ushio, Fernando Alva-Manchego, Jose Camacho-Collados

Powerful generative models have led to recent progress in question generation (QG). However, it is difficult to measure advances in QG research since there are no standardized resources that allow a uniform comparison among approaches. In this paper, we introduce QG-Bench, a multilingual and multidomain benchmark for QG that unifies existing question answeri

Randall Pruim, Maria-Cristiana Gîrjău, Nicholas J. Horton

Many data science students and practitioners don't see the value in making time to learn and adopt good coding practices as long as the code "works". However, code standards are an important part of modern data science practice, and they play an essential role in the development of data acumen. Good coding practices lead to more reliable code and save more t

Silvia Beddar-Wiesing, Giuseppe Alessio D'Inverno, Caterina Graziani, Veronica Lachi

Graph Neural Networks (GNNs) are a large class of relational models for graph processing. Recent theoretical studies on the expressive power of GNNs have focused on two issues. On the one hand, it has been proven that GNNs are as powerful as the Weisfeiler-Lehman test (1-WL) in their ability to distinguish graphs. Moreover, it has been shown that the equival

Aditya Dewanto Hartono, Linh Thi Hoai Nguyen, Ton Viet Ta

This paper presents a system of stochastic differential equations (SDEs) as mathematical model to describe the spatial-temporal dynamics of predator-prey system in an artificial aquatic environment with schooling behavior imposed upon the associated prey. The proposed model follows the particle-like approach where interactions among the associated units are

Alejandro Rodriguez Dominguez, David Stynes

We present a geometric version of Quickest Change Detection (QCD) and Quickest Hub Discovery (QHD) tests in correlation structures that allows us to include and combine new information with distance metrics. The topic falls within the scope of sequential, nonparametric, high-dimensional QCD and QHD, from which state-of-the-art settings developed global and l

N. Kravets, U. Mur, M. Ravnik, S. Zumer

Geometric phase optical elements made of space-variant anisotropic media customarily find their optimal operating conditions when the half-wave retardance condition is fulfilled, which allows imparting polarization-dependent changes to an incident wavefront. In practice, intrinsic limitations of man-made manufacturing process or the finite spectrum of the li

Xueyang Li, Shangqing Liu, Ruitao Feng, Guozhu Meng

Automatically fixing compilation errors can greatly raise the productivity of software development, by guiding the novice or AI programmers to write and debug code. Recently, learning-based program repair has gained extensive attention and became the state-of-the-art in practice. But it still leaves plenty of space for improvement. In this paper, we propose

Lei Sha, Yuhang Song, Yordan Yordanov, Tommaso Salvatori

Transformers have become an indispensable module for text generation models since their great success in machine translation. Previous works attribute the~success of transformers to the query-key-value dot-product attention, which provides a robust inductive bias by the fully connected token graphs. However, we found that self-attention has a severe limitati

Tai Hoang, Alona Kharchenko, Simon Trendel, Rafael Hostettler

Roboy 3.0 is an open-source tendon-driven humanoid robot that mimics the musculoskeletal system of the human body. Roboy 3.0 is being developed as a remote robotic body - or a robotic avatar - for humans to achieve remote physical presence. Artificial muscles and tendons allow it to closely resemble human morphology with 3-DoF neck, shoulders and wrists. Rob

Jing Liu, Qi-Fang Lü, Chun-Hua Liu, Dian-Yong Chen

In this work, we propose to investigate the $d_{N\Omega}$ dibaryon production in the process $K^- p \rightarrow d_{N\Omega} \bar{\Xi}^0$ by utilizing the kaon beam with the typical momentum to be around 10 GeV, which may be available at COMPASS, OKA@U-70 and SPS@CERN. The cross sections for $K^- p \rightarrow d_{N\Omega} \bar{\Xi}^0$ are estimated and in par

Andreas Juhl

For any hypersurface $M$ of a Riemannian manifold $X$, recent works introduced the notions of extrinsic conformal Laplacians and extrinsic $Q$-curvatures. Here we derive explicit formulas for the extrinsic version ${\bf P}_4$ of the Paneitz operator and the corresponding extrinsic fourth-order $Q$-curvature ${\bf Q}_4$ in general dimensions. This result invo

K. K. Kataria, M. Khandakar, P. Vellaisamy

We introduce a non-homogeneous version of the generalized counting process (GCP), namely, the non-homogeneous generalized counting process (NGCP). We time-change the NGCP by an independent inverse stable subordinator to obtain its fractional version, and call it as the non-homogeneous generalized fractional counting process (NGFCP). A generalization of the N

Gregory Baker, Diego Molla-Aliod

A simple machine learning model of pluralisation as a linear regression problem minimising a p-adic metric substantially outperforms even the most robust of Euclidean-space regressors on languages in the Indo-European, Austronesian, Trans New-Guinea, Sino-Tibetan, Nilo-Saharan, Oto-Meanguean and Atlantic-Congo language families. There is insufficient evidenc

Junhao Zheng, Zhanxian Liang, Haibin Chen, Qianli Ma

Continual Learning for Named Entity Recognition (CL-NER) aims to learn a growing number of entity types over time from a stream of data. However, simply learning Other-Class in the same way as new entity types amplifies the catastrophic forgetting and leads to a substantial performance drop. The main cause behind this is that Other-Class samples usually cont

Zhi-Xuan Li, Shuai Yin, Yu-Rong Shu

We explore the imaginary-time relaxation dynamics near quantum critical points with semi-ordered initial states. Different from the case with homogeneous ordered initial states, in which the order parameter $M$ decays homogeneously as $M\propto \tau^{-\beta/\nu z}$, here $M$ depends on the location $x$, showing rich scaling behaviors. Similar to the classica

Wei-Min Shang, Xing-Yan Fan, Fu-Lin Zhang, Jing-Ling Chen

Quantum information masking is a protocol that hides the original quantum information from subsystems and spreads it over quantum correlation, which is available to multipartite except bipartite systems. In this work, we explicitly study the quantum information masking in multipartite scenario and prove that all the k-level quantum states can be masked into

Umang Malik, Rob Sharp, A. Penton, Z. Yu

Reverberation mapping measurements have been used to constrain the relationship between the size of the broad-line region and luminosity of active galactic nuclei (AGN). This $R-L$ relation is used to estimate single-epoch virial black hole masses, and has been proposed for use to standardise AGN to determine cosmological distances. We present reverberation

R. D. Muelas-Hurtado, K. Volke-Sepulveda, J. L. Ealo, F. Nori

Polarization singularities and topological polarization structures are generic features of inhomogeneous vector wave fields of any nature. However, their experimental studies mostly remain restricted to optical waves. Here we report observation of polarization singularities, topological Mobius-strip structures and skyrmionic textures in 3D polarization field

Matin Macktoobian

In this study, we synthesize a novel dynamical approach for ant colonies enabling them to migrate to new nest sites in a self-organizing fashion. In other words, we realize ant colony migration as a self-organizing phenotype-level collective behavior. For this purpose, we first segment the edges of the graph of ants' pathways. Then, each segment, attributed

Xuejun Yan, Hongyu Yan, Jingjing Wang, Hang Du

The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion methods are solely feedforward, and high-level information is rarely reused to improve low-level feature learning. To this end, we propose a novel Feedback Network (FBNet) for point cloud completion, in wh

Haddi Ahmadi, Zahra Ahmadi, Nasrin Razmjooei, Amin Khavasi

Line waves are defined as confined edge modes propagating at the interface of dual electromagnetic metasurfaces that preserve mirror reflection symmetries. Previous works have theoretically and practically explored these waves, showing that they occur at microwave regimes and terahertz ranges. It is also demonstrated that line waves can happen when there is

Mohammad R. Hosseini, Mohammad R. Garousi

It is known that, in the static gauge, the world-volume and the transverse Kaluza-Klein (KK) reductions of the O-plane effective actions on a circle satisfy the T-duality constraint for arbitrary base space background. In this paper we show that due to the presence of the second fundamental form in the D-brane couplings at order $\alpha'$ and higher, the T-d

Niklas Stoehr, Lucas Torroba Hennigen, Josef Valvoda, Robert West

Measuring the intensity of events is crucial for monitoring and tracking armed conflict. Advances in automated event extraction have yielded massive data sets of "who did what to whom" micro-records that enable data-driven approaches to monitoring conflict. The Goldstein scale is a widely-used expert-based measure that scores events on a conflictual-cooperat

Yong He, Cheng Wang, Shun Zhang, Nan Li

Medical text learning has recently emerged as a promising area to improve healthcare due to the wide adoption of electronic health record (EHR) systems. The complexity of the medical text such as diverse length, mixed text types, and full of medical jargon, poses a great challenge for developing effective deep learning models. BERT has presented state-of-the

Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo

Point-of-Interest (POI) recommendation, which benefits from the proliferation of GPS-enabled devices and location-based social networks (LBSNs), plays an increasingly important role in recommender systems. It aims to provide users with the convenience to discover their interested places to visit based on previous visits and current status. Most existing meth

Iona Xia, Jian Ge, Kevin Willis, Yinan Zhao

Quasar absorption line analysis is critical for studying gas and dust components and their physical and chemical properties as well as the evolution and formation of galaxies in the early universe. Ca II absorbers, which are one of the dustiest absorbers and are located at lower redshifts than most other absorbers, are especially valuable when studying physi

Tong Wei, Zhen Mao, Jiang-Xin Shi, Yu-Feng Li

Multi-label learning has attracted significant attention from both academic and industry field in recent decades. Although existing multi-label learning algorithms achieved good performance in various tasks, they implicitly assume the size of target label space is not huge, which can be restrictive for real-world scenarios. Moreover, it is infeasible to dire

Huiyang Shao, Qianqian Xu, Zhiyong Yang, Shilong Bao

The Partial Area Under the ROC Curve (PAUC), typically including One-way Partial AUC (OPAUC) and Two-way Partial AUC (TPAUC), measures the average performance of a binary classifier within a specific false positive rate and/or true positive rate interval, which is a widely adopted measure when decision constraints must be considered. Consequently, PAUC optim

S. Matsumoto

In this paper, we show a no-go theorem for static spherically symmetric black holes with vector hair in Einstein-$\Lambda$-Vector-Tensor-Gauss-Bonnet theory where a complex vector field non-minimally couples with Gauss-Bonnet invariant. For this purpose, we expand metric functions and radial functions of a vector field around the event horizon, and substitut

Andreas Theodorou, Juan Carlos Nieves, Virginia Dignum

Developed and used responsibly Artificial Intelligence (AI) is a force for global sustainable development. Given this opportunity, we expect that the many of the existing guidelines and recommendations for trustworthy or responsible AI will provide explicit guidance on how AI can contribute to the achievement of United Nations' Sustainable Development Goals

Kohei Motegi

We investigate the $K$-theoretic Gysin map for type $A$ partial flag bundles from the viewpoint of integrability. We introduce several types of partition functions for one version of $q=0$ degeneration of $U_q(\widehat{sl_n})$ vertex models on rectangular grids which differ by boundary conditions and sizes, and can be viewed as Grothendieck classes of the Gr

Dongsheng Zhu, Zhenyu Mao, Jinghui Lu, Rui Zhao

Contrastive learning has recently achieved compelling performance in unsupervised sentence representation. As an essential element, data augmentation protocols, however, have not been well explored. The pioneering work SimCSE resorting to a simple dropout mechanism (viewed as continuous augmentation) surprisingly dominates discrete augmentations such as crop

Tse-Tin Chan, Jian Feng, Haoyuan Pan

This paper studies low-power random access protocols for timely status update systems with information freshness requirements, measured by age of information (AoI). In an extensive network, a fundamental challenge is scheduling a large number of transmitters to access the wireless channel in a way that achieves low network-wide AoI while consuming minimal po

Aravind Reddy, Zhao Song, Lichen Zhang

In this work, we initiate the study of \emph{Dynamic Tensor Product Regression}. One has matrices $A_1\in \mathbb{R}^{n_1\times d_1},\ldots,A_q\in \mathbb{R}^{n_q\times d_q}$ and a label vector $b\in \mathbb{R}^{n_1\ldots n_q}$, and the goal is to solve the regression problem with the design matrix $A$ being the tensor product of the matrices $A_1, A_2, \dot

K. Chang, Z. Zheng, J. E. Sipe, J. L. Cheng

We theoretically study the optical activity in a doped system and derive the optical activity tensor from a light wavevector-dependent linear optical conductivity. Although the light-matter interaction is introduced through the velocity gauge from a minimal coupling Hamiltonian, we find that the well-known ``false divergences'' problem can be avoided in prac

Jun Gao, Binlong Li, Jie Ma, Tianying Xie

Bondy and Vince showed that every graph with minimum degree at least three contains two cycles of lengths differing by one or two.We prove the following average degree counterpart that every $n$-vertex graph $G$ with at least $\frac52(n-1)$ edges, unless $4|(n-1)$ and every block of $G$ is a clique $K_5$, contains two cycles of consecutive even lengths. Our

Tianxun Hu, Tianzheng Wang, Qingqing Zhou

Modern database applications often change their schemas to keep up with the changing requirements. However, support for online and transactional schema evolution remains challenging in existing database systems. Specifically, prior work often takes ad hoc approaches to schema evolution with 'patches' applied to existing systems, leading to many corner cases

Sanjay Kumar, Avijeet Prasad, Ranadeep Sarkar, Ramit Bhattacharyya

Magnetohydrodynamics simulation of active region NOAA 11515 is performed to examine the initiation of the M5.6 flaring event that starts around 10:43 UT on 2012 July 2. The simulation is conducted using an extrapolated non-force-free magnetic field generated from the photospheric vector magnetogram of the active region as the initial magnetic field. The magn

Yaohua Wang, FangYi Zhang, Ming Lin, Senzhang Wang

Graph structure learning aims to learn connectivity in a graph from data. It is particularly important for many computer vision related tasks since no explicit graph structure is available for images for most cases. A natural way to construct a graph among images is to treat each image as a node and assign pairwise image similarities as weights to correspond

Clément de Seguins Pazzis

Let $V$ be a finite-dimensional vector space over a field $\mathbb{F}$, equipped with a symmetric or alternating non-degenerate bilinear form $b$. When the characteristic of $\mathbb{F}$ is not $2$, we characterize the endomorphisms $u$ of $V$ that split into $u=a_1+a_2$ for some pair $(a_1,a_2)$ of $b$-selfadjoint (respectively, $b$-skew-selfadjoint) endomo

Wei Mao, Miaomiao Liu, Richard Hartley, Mathieu Salzmann

In this paper, we tackle the task of scene-aware 3D human motion forecasting, which consists of predicting future human poses given a 3D scene and a past human motion. A key challenge of this task is to ensure consistency between the human and the scene, accounting for human-scene interactions. Previous attempts to do so model such interactions only implicit

Chenze Shao, Yang Feng

Non-autoregressive translation (NAT) models are typically trained with the cross-entropy loss, which forces the model outputs to be aligned verbatim with the target sentence and will highly penalize small shifts in word positions. Latent alignment models relax the explicit alignment by marginalizing out all monotonic latent alignments with the CTC loss. Howe

Mohammed Hammad

Modern day applications, especially information retrieval webapps that involve "search" as their use cases are gradually moving towards "answering" modules. Conversational chatbots which have been proved to be more engaging to users, use Question Answering as their core. Since, precise answering is computationally expensive, several approaches have been deve

Peizhe Jiang, Wei Yang, Xiaoqing Ye, Xiao Tan

Monocular depth estimation (MDE) in the self-supervised scenario has emerged as a promising method as it refrains from the requirement of ground truth depth. Despite continuous efforts, MDE is still sensitive to scale changes especially when all the training samples are from one single camera. Meanwhile, it deteriorates further since camera movement results

Hamzah Luqman

Sign language recognition has attracted the interest of researchers in recent years. While numerous approaches have been proposed for European and Asian sign languages recognition, very limited attempts have been made to develop similar systems for the Arabic sign language (ArSL). This can be attributed partly to the lack of a dataset at the sentence level.

Yi-De Jing, Lu Zheng, Shutao Yang, Xuefeng Zhang

TianQin is a proposed geocentric space-based gravitational wave observatory mission, which requires time-delay interferometry (TDI) to cancel laser frequency noise. With high demands for precision, solar-wind plasma environment at $\sim 10^5$ km above the Earth may constitute a non-negligible noise source to laser interferometric measurements between satelli

Ji Qi, Bin Xu, Kaisheng Zeng, Jinxin Liu

Document-level relation extraction with graph neural networks faces a fundamental graph construction gap between training and inference - the golden graph structure only available during training, which causes that most methods adopt heuristic or syntactic rules to construct a prior graph as a pseudo proxy. In this paper, we propose $\textbf{ConstGCN}$, a no

Pavan Reddy M., SaiDhiraj Amuru, Kiran Kuchi

In this letter, we present in detail the system-level modeling of reconfigurable intelligent surface (RIS)-assisted cellular systems by considering a 3-dimensional channel model between base station, RIS, and user. We prove that the optimal placement of RIS to achieve wider coverage is exactly opposite to the base station, under the constraint of single RIS

Xinli Shi, Guanghui Wen, Xinghuo Yu

This paper focuses on finite-time (FT) convergent distributed algorithms for solving time-varying (TV) distributed optimization (TVDO). The objective is to minimize the sum of local TV cost functions subject to the possible TV constraints by the coordination of multiple agents in finite time. Specifically, two classes of TVDO are investigated included uncons

Tohru Koma

We present a concrete example of fractional Chern insulator whose fermion Hamiltonian consists of hopping and Coulomb repulsive interaction terms. Both of them are of finite range on the square lattice. In a strong coupling limit for the interaction Hamiltonian, we show that the Hall conductance is fractionally quantized to $1/2$ in the sense of the expectat

Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari

Large language models (LLMs) have shown exceptional performance on a variety of natural language tasks. Yet, their capabilities for HTML understanding -- i.e., parsing the raw HTML of a webpage, with applications to automation of web-based tasks, crawling, and browser-assisted retrieval -- have not been fully explored. We contribute HTML understanding models

Chengjian Luo, Xuefeng Zhang

The paper is a sequel to our previous work (Zhang et al. Phys. Rev. D 103, 062001 (2021)). For proposed geocentric space-based gravitational wave detectors such as TianQin, gLISA, and GADFLI, the gravity-field disturbances, i.e., the so called ``orbital noise'', from the Earth-Moon system on the sensitive intersatellite laser interferometric measurements sho

Jaydip Sen, Abhishek Dutta

Portfolio optimization is a challenging problem that has attracted considerable attention and effort from researchers. The optimization of stock portfolios is a particularly hard problem since the stock prices are volatile and estimation of their future volatilities and values, in most cases, is very difficult, if not impossible. This work uses three ratios,

Hang Du, Xuejun Yan, Jingjing Wang, Di Xie

Point cloud upsampling focuses on generating a dense, uniform and proximity-to-surface point set. Most previous approaches accomplish these objectives by carefully designing a single-stage network, which makes it still challenging to generate a high-fidelity point distribution. Instead, upsampling point cloud in a coarse-to-fine manner is a decent solution.

Hsin-Ying Lee, Hung-Ting Su, Bing-Chen Tsai, Tsung-Han Wu

While recent large-scale video-language pre-training made great progress in video question answering, the design of spatial modeling of video-language models is less fine-grained than that of image-language models; existing practices of temporal modeling also suffer from weak and noisy alignment between modalities. To learn fine-grained visual understanding,

Lu Zhang, Yang Wang, Jiaogen Zhou, Chenbo Zhang

Few-shot object detection (FSOD) is to detect objects with a few examples. However, existing FSOD methods do not consider hierarchical fine-grained category structures of objects that exist widely in real life. For example, animals are taxonomically classified into orders, families, genera and species etc. In this paper, we propose and solve a new problem ca

Barak Or, Itzik Klein

Autonomous underwater vehicles (AUV) are commonly used in many underwater applications. Usually, inertial sensors and Doppler velocity log readings are used in a nonlinear filter to estimate the AUV navigation solution. The process noise covariance matrix is tuned according to the inertial sensors' characteristics. This matrix greatly influences filter accur

B. G. Konopelchenko, G. Ortenzi

Blow-ups of derivatives and gradient catastrophes for the $n$-dimensional homogeneous Euler equation are discussed. It is shown that, in the case of generic initial data, the blow-ups exhibit a fine structure in accordance of the admissible ranks of certain matrix generated by the initial data. Blow-ups form a hierarchy composed by $n+1$ levels with the stro

H. Sekhavatmaneshand, S. Mastellone

Renewable energy resources and power electronics-interfaced loads introduce fast dynamics in distribution networks. These dynamics cannot be regulated by slow conventional solutions and require fast controllable energy resources such as Battery Energy Storage Systems (BESSs). To compensate for the high costs associated to BESSs, their energy and power manage

Tina Torkaman, Yongquan Zhang

Recent works [MMO1, arXiv:1802.03853, arXiv:1802.04423, arXiv:2101.08956] have shed light on the topological behavior of geodesic planes in the convex core of a geometrically finite hyperbolic 3-manifolds $M$ of infinite volume. In this paper, we focus on the remaining case of geodesic planes outside the convex core of $M$, giving a complete classification o

Giovanni Toffetti, Leonardo Militano, Seán Murphy, Remo Maurer

In this paper we discuss our experience in teaching the Robotic Applications Programming course at ZHAW combining the use of a Kubernetes (k8s) cluster and real, heterogeneous, robotic hardware. We discuss the main advantages of our solutions in terms of seamless simulation-to-real experience for students and the main shortcomings we encountered with network

Sanjiv Kumar Bariwal, Ankik Kumar Giri, Rajesh Kumar

Collisional breakage in the particulate process has a lot of recent curiosity. We study the pure collisional breakage equation which is nonlinear in nature accompanied by locally bounded breakage kernel and collision kernel. The continuous equation is discretized using a finite volume scheme (FVS) and the weak convergence of the approximated solution towards

Alexander Rubtsov, Mikhail Vyalyi

We consider general computational models: one-way and two-way finite automata, and logarithmic space Turing machines, all equipped with an auxiliary data structure (ADS). The definition of an ADS is based on the language of protocols of work with the ADS. We describe the connection of automata-based models with ``Balloon automata'' that are another general f

Junting Ren, Fabian J. E. Telschow, Armin Schwartzman

Motivated by the questions of risk assessment in climatology (temperature change in North America) and medicine (impact of statin usage and COVID-19 on hospitalized patients), we address the problem of estimating the set in the domain of a function whose image equals a predefined subset. Existing methods that construct confidence sets require strict assumpti

Akanksha Agrawal, Saket Saurabh, Meirav Zehavi

The \emph{Delaunay graph} of a point set $P \subseteq \mathbb{R}^2$ is the plane graph with the vertex-set $P$ and the edge-set that contains $\{p,p'\}$ if there exists a disc whose intersection with $P$ is exactly $\{p,p'\}$. Accordingly, a triangulated graph $G$ is \emph{Delaunay realizable} if there exists a triangulation of the Delaunay graph of some $P

Dragomir Ž. Djoković

The first examples of D-optimal matrices of orders 222, 234, 258 and 278 are constructed.

Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee

The Transformer architecture has achieved remarkable success in a number of domains including natural language processing and computer vision. However, when it comes to graph-structured data, transformers have not achieved competitive performance, especially on large graphs. In this paper, we identify the main deficiencies of current graph transformers:(1) E

Baoxiong Jia, Ting Lei, Song-Chun Zhu, Siyuan Huang

Understanding human tasks through video observations is an essential capability of intelligent agents. The challenges of such capability lie in the difficulty of generating a detailed understanding of situated actions, their effects on object states (i.e., state changes), and their causal dependencies. These challenges are further aggravated by the natural p

J. Wang, D. W. Xu, J. Y. Bai, T. G. Brink

The widely accepted active galactic nucleus (AGN) paradigm has been recently challenged by the discovery of the so-called ``changing-look'' (CL) phenomenon characterized by spectral-type transitions. By comparing the SDSS-V and SDSS DR16 spectroscopic datasets, here we report the identification of 14 new CL-AGNs (redshift $z<0.5$) exhibiting spectral-type ch

Elan Rosenfeld, Preetum Nakkiran, Hadi Pouransari, Oncel Tuzel

Recent advances in learning aligned multimodal representations have been primarily driven by training large neural networks on massive, noisy paired-modality datasets. In this work, we ask whether it is possible to achieve similar results with substantially less training time and data. We achieve this by taking advantage of existing pretrained unimodal encod

Hamed Bastami, Majid Moradikia, Hamid Behroozi, Lajos Hanzo

The Cooperative Rate-Splitting (CRS) scheme, proposed evolves from conventional Rate Splitting (RS) and relies on forwarding a portion of the RS message by the relaying users. In terms of secrecy enhancement, it has been shown that CRS outperforms its non-cooperative counterpart for a two-user Multiple Input Single Output (MISO) Broadcast Channel (BC). Given

Yufeng Zhong, Long Xu, Jiebo Luo, Lin Ma

3D dense captioning, as an emerging vision-language task, aims to identify and locate each object from a set of point clouds and generate a distinctive natural language sentence for describing each located object. However, the existing methods mainly focus on mining inter-object relationship, while ignoring contextual information, especially the non-object d

Jon Cheah

This project considers the finite symmetry subgroups of the orthogonal group $\mathrm{O}(3) \subset \mathrm{GL}(3,\mathbb{R})$ and the index $2$ containments $G\lhd \widehat{G}$. The special orthogonal group $\mathrm{SO}(3) \subset \mathrm{SL}(3,\mathbb{R})$ admits a double cover from the spinor group $\mathrm{Spin}(3) \cong \mathrm{SU}(2) \subset \mathrm{SL

Yi Yang, Chen Zhang, Dawei Song

Recent advances in distilling pretrained language models have discovered that, besides the expressiveness of knowledge, the student-friendliness should be taken into consideration to realize a truly knowledgable teacher. Based on a pilot study, we find that over-parameterized teachers can produce expressive yet student-unfriendly knowledge and are thus limit