May 2023 arXiv papers — page 120

Jana Rodriguez Hertz

This is more or less the content of a 5-hour mini-course that I have given at KTH in the program ``Master class in low-dimensional dynamics'' during May 1-5, 2023. It was not intended to be exhaustive but to give the students a grasp of basic ideas in Pesin Theory in a very short period. It is to be taken as a first approximation and as an invitation to stud

Bartosz Mirecki, Mikołaj Rogalski, Piotr Arcab, Piotr Rogujski

Exposure to laser light alters cell culture examination via optical microscopic imaging techniques, also based on label-free coherent digital holography. To mitigate this detrimental feature, researchers tend to use a broader spectrum and lower intensity of illumination, which can decrease the quality of holographic imaging due to lower resolution and higher

Yaxin Fan, Feng Jiang, Peifeng Li, Haizhou Li

Large language models, like ChatGPT, have shown remarkable capability in many downstream tasks, yet their ability to understand discourse structures of dialogues remains less explored, where it requires higher level capabilities of understanding and reasoning. In this paper, we aim to systematically inspect ChatGPT's performance in two discourse analysis tas

Shreya Das, Kundan Kumar, Shovan Bhaumik

This paper considers a bearings-only tracking problem using noisy measurements of unknown noise statistics from a passive sensor. It is assumed that the process and measurement noise follows the Gaussian distribution where the measurement noise has an unknown non-zero mean and unknown covariance. Here an adaptive nonlinear filtering technique is proposed whe

Linli Yao, Yuanmeng Zhang, Ziheng Wang, Xinglin Hou

Automatically narrating videos in natural language complying with user requests, i.e. Controllable Video Captioning task, can help people manage massive videos with desired intentions. However, existing works suffer from two shortcomings: 1) the control signal is single-grained which can not satisfy diverse user intentions; 2) the video description is genera

Hajime Ogawa, Miho Aoki

Let $L_n$ be a simplest cubic field with Galois group $G=\rm{Gal} (L_n/\mathbb Q)$. The associated order is denoted as ${\cal A}_{L_n/\mathbb Q}:= \{ x\in {\mathbb Q} [G] \, |\, x \cdot \cal{O}_{L_n} \subset {\cal O}_{L_n } \}$, where ${\cal O}_{L_n}$ is the ring of integers of $L_n$. Leopoldt showed that $\cal{O}_{L_n} \simeq {\cal A}_{L_n/\mathbb Q}$ as ${

Zitan Chen

Convolutional codes with a maximum distance profile attain the largest possible column distances for the maximum number of time instants and thus have outstanding error-correcting capability especially for streaming applications. Explicit constructions of such codes are scarce in the literature. In particular, known constructions of convolutional codes with

Guorui Chen, Ya-Hui Zhang, Aaron Sharpe, Zuocheng Zhang

Wigner crystals are predicted as the crystallization of the dilute electron gas moving in a uniform background when the electron-electron Coulomb energy dominates the kinetic energy. The Wigner crystal has previously been observed in the ultraclean two-dimensional electron gas (2DEG) present on the surface of liquid helium and in semiconductor quantum wells

Jialong Zuo, Jiahao Hong, Feng Zhang, Changqian Yu

Language-image pre-training is an effective technique for learning powerful representations in general domains. However, when directly turning to person representation learning, these general pre-training methods suffer from unsatisfactory performance. The reason is that they neglect critical person-related characteristics, i.e., fine-grained attributes and

Takeru Matsuda

In estimation of a normal mean matrix under the matrix quadratic loss, we develop a general formula for the matrix quadratic risk of orthogonally invariant estimators. The derivation is based on several formulas for matrix derivatives of orthogonally invariant functions of matrices. As an application, we calculate the matrix quadratic risk of a singular valu

Mingyu Hao, Keyang Qian, Sid Chi-Kin Chau

Traditional Insurance, a popular approach of financial risk management, has suffered from the issues of high operational costs, opaqueness, inefficiency and a lack of trust. Recently, blockchain-enabled "parametric insurance" through authorized data sources (e.g., remote sensing and IoT) aims to overcome these issues by automating the underwriting and claim

Takumi Nishi

The study involved the analysis of emotion-associated language in the UK Conservative and Labour party general election manifestos between 2000 to 2019. While previous research have shown a general correlation between ideological positioning and overlap of public policies, there are still conflicting results in matters of sentiments in such manifestos. Using

Yeruoxi Chen, Hong Yao, Min Liu, Junlong Tian

Considering energy dependence of the barrier radius in heavy-ion fusion reactions, a modified Siwek-Wilczy\'{n}ski (MSW) fusion cross section formula is proposed. With the MSW formula, the fusion barrier parameters for 367 reaction systems are systematically extracted, based on 443 datasets of measured cross sections. We find that the fusion excitation funct

Haixin Wang, Xinlong Yang, Jianlong Chang, Dian Jin

Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence. The core is to adapt the model to downstream tasks with only a small set of parameters. Recently, researchers have leveraged such proven techniques in multimodal tasks and achieve promi

Miroslav Popovic, Marko Popovic, Branislav Kordic, Huibiao Zhu

Many online transaction scheduler architectures and algorithms for various software transactional memories have been designed in order to maintain good system performance even for high concurrency workloads. Most of these algorithms were directly implemented in a target programming language, and experimentally evaluated, without theoretical proofs of correct

Rabeeh Karimi Mahabadi, Hamish Ivison, Jaesung Tae, James Henderson

Diffusion models have emerged as a powerful paradigm for generation, obtaining strong performance in various continuous domains. However, applying continuous diffusion models to natural language remains challenging due to its discrete nature and the need for a large number of diffusion steps to generate text, making diffusion-based generation expensive. In t

Adam Morawiec

Static recrystallization is an important aspect of metal processing. The initial stage of recrystallization - nucleation of new grains - determines its later stages. The accepted mechanisms of recrystallization nucleation are based on the assumption that embryos with orientations of the nuclei preexist in the deformed matrix. However, this standard picture s

Xiaofei Sun, Xiaoya Li, Jiwei Li, Fei Wu

Despite the remarkable success of large-scale Language Models (LLMs) such as GPT-3, their performances still significantly underperform fine-tuned models in the task of text classification. This is due to (1) the lack of reasoning ability in addressing complex linguistic phenomena (e.g., intensification, contrast, irony etc); (2) limited number of tokens all

Mazhar Ali

Recently, it has been shown that locally randomized measurements can be employed to get partial transpose moments of a density matrix [Elben A., {\it et al.} Phys. Rev. Lett. {\bf 125}, 200501 (2020)]. Consequently, two general entanglement detection methods were proposed based on partial transpose moments of a density matrix [Yu X-D., {\it et al.} Phys. Rev

Daisuke Yokota, Yuichi Sudo, Fukuhito Ooshita, Toshimitsu Masuzawa

We propose a self-stabilizing leader election (SS-LE) protocol on ring networks in the population protocol model. Given an integer $ψ$ satisfying $\log n \le ψ\le \log n+O(1)$, where $n$ is the population size, the proposed protocol reaches a safe configuration within $O(n^2 \log n)$ steps with high probability from any initial configuration, and thereafter

Keshav Das Agarwal, Tanoy Kanti Konar, Leela Ganesh Chandra Lakkaraju, Aditi Sen De

The non-Hermitian model exhibits counterintuitive phenomena that are not observed in the Hermitian counterparts. To probe the competition between non-Hermitian and Hermitian interacting components of the Hamiltonian, we focus on a system containing non-Hermitian $XY$ spin chain and Hermitian Kaplan-Shekhtman-Entin-Aharony (KSEA) interactions along with the t

Mahdi Javadi, Daniel Harnack, Paula Stocco, Shivesh Kumar

Brachiation is a dynamic, coordinated swinging maneuver of body and arms used by monkeys and apes to move between branches. As a unique underactuated mode of locomotion, it is interesting to study from a robotics perspective since it can broaden the deployment scenarios for humanoids and animaloids. While several brachiating robots of varying complexity have

Peipei Liu, Hong Li, Yimo Ren, Jie Liu

Mining structured knowledge from tweets using named entity recognition (NER) can be beneficial for many down stream applications such as recommendation and intention understanding. With tweet posts tending to be multimodal, multimodal named entity recognition (MNER) has attracted more attention. In this paper, we propose a novel approach, which can dynamical

Junfeng Jiang, Chengzhang Dong, Sadao Kurohashi, Akiko Aizawa

Dialogue segmentation is a crucial task for dialogue systems allowing a better understanding of conversational texts. Despite recent progress in unsupervised dialogue segmentation methods, their performances are limited by the lack of explicit supervised signals for training. Furthermore, the precise definition of segmentation points in conversations still r

Xinyu Liu, Qingsheng Yang, Wei Rao

Owing to the possibility of controlling its specific mechanical behaviors up taken by irradiated by light at particular wavelengths, the photoisomerization hydrogels have a broad range of potential applications. A theory connecting the optical excitation to mechanical behavior is essential to precisely control the photo-mechanical behaviors of the hydrogel.

Amareshwara Sainadh Chamarthi, Natan Hoffmann, Steven Frankel

In this work, we propose a novel selective discontinuity sensor approach for numerical simulations of the compressible Navier-Stokes equations. Since transformation to characteristic space is already a common approach to reduce high-frequency oscillations during interpolation to cell interfaces, we exploit the characteristic wave structure of the Euler equat

Yan Zhuang, Daxiong Piao, Yanmin Niu

We consider the existence of invariant curves of real analytic reversible mappings which are quasi-periodic in the angle variables. By the normal form theorem, we prove that under some assumptions, the original mapping is changed into its linear part via an analytic convergent transformation, so that invariants curves are obtained. In the iterative process,

Boyu Liu, Lianke Qin, Zhao Song, Yitan Wang

Submodular function maximization is a critical building block for diverse tasks, such as document summarization, sensor placement, and image segmentation. Yet its practical utility is often limit by the $O(knd^2)$ computational bottleneck. In this paper, we propose an integrated framework that addresses efficiency and privacy simultaneously. First, we introd

Hiroto Honda, Yusuke Uchida

Lane marker detection is a crucial component of the autonomous driving and driver assistance systems. Modern deep lane detection methods with row-based lane representation exhibit excellent performance on lane detection benchmarks. Through preliminary oracle experiments, we firstly disentangle the lane representation components to determine the direction of

Miika Soikkeli, Anton Murros, Arto Rantala, Oihana Txoperena

The reliability of analysis is becoming increasingly important as point-of-care diagnostics are transitioning from single analyte detection towards multiplexed multianalyte detection. Multianalyte detection benefits greatly from complementary metal-oxide semiconductor (CMOS) integrated sensing solutions, offering miniaturized multiplexed sensing arrays with

D. Batic, P. Guha, A. Ghose Choudhury

We show how the Gambier equation arises in connection to Friedmann-Lema$\mbox{\^{i}}$tre-Robertson-Walker (FLRW) cosmology and a Dark Matter equation of state. Moreover, we provide a correspondence between the Friedmann equations and the Gambier equations that possess the Painlev$\acute{\mbox{e}}$ property in $2+1$ dimensions. We also consider special cases

Fabian Göttsch, Noboru Osawa, Yoshiaki Amano, Issei Kanno

We consider fairness scheduling in a user-centric cell-free massive MIMO network, where $L$ remote radio units, each with $M$ antennas, serve $K_{\rm tot} \approx LM$ user equipments (UEs). Recent results show that the maximum network sum throughput is achieved where $K_{\rm act} \approx \frac{LM}{2}$ UEs are simultaneously active in any given time-frequency

Masaru Siino

To comprehend the shadow of a black hole in a general spacetime, we have investigated the concept of the maximal black room (MBR). The boundary of the MBR is a non-spacelike hypersurface that contains at least one null geodesic tangent to its boundary, which we refer to as the rays' surface. Our aim is to explore the geometry of this surface. From our curren

Samuel Stevens, Yu Su

Over-parameterized neural language models (LMs) can memorize and recite long sequences of training data. While such memorization is normally associated with undesired properties such as overfitting and information leaking, our work casts memorization as an unexplored capability of LMs. We propose the first symmetric encryption algorithm with autoregressive l

Hidekazu Yoshioka

Conventional harvesting problems for natural resources often assume physiological homogeneity of the body length/weight among individuals. However, such assumptions generally are not valid in real-world problems, where heterogeneity plays an essential role in the planning of biological resource harvesting. Furthermore, it is difficult to observe heterogeneit

Chao Liu, Xuanlin Bao, Hongyu Zhang, Neng Zhang

Automated code generation can be a powerful technique for software development, significantly reducing developers' efforts and time required to create new code by generating it automatically based on requirements. Recently, OpenAI's language model ChatGPT has emerged as a powerful tool for generating human-like responses to a wide range of textual inputs (i.

Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong Zhang

Recent studies have shown that episodic reinforcement learning (RL) is no harder than bandits when the total reward is bounded by $1$, and proved regret bounds that have a polylogarithmic dependence on the planning horizon $H$. However, it remains an open question that if such results can be carried over to adversarial RL, where the reward is adversarially c

Shuangyi Chen, Anuja Modi, Shweta Agrawal, Ashish Khisti

Vertical federated learning (VFL) enables the collaborative training of machine learning (ML) models in settings where the data is distributed amongst multiple parties who wish to protect the privacy of their individual data. Notably, in VFL, the labels are available to a single party and the complete feature set is formed only when data from all parties is

Chihiro Harada, Atsushi Ono, Joji Nasu

The Kitaev quantum spin liquid possesses two fractional quasiparticles, itinerant Majorana fermions and localized visons. It provides a promising platform for realizing a Majorana zero mode trapped by a vison excitation. This local mode behaves as a non-Abelian anyon capable of applications to quantum computation. However, creating, observing, and manipulati

Linhao Ma, Jim Fuller

Gravitational wave observations indicate the existence of merging black holes (BHs) with high spin ($a\gtrsim0.3$), whose formation pathways are still an open question. A possible way to form those binaries is through the tidal spin-up of a Wolf-Rayet (WR) star by its BH companion. In this work, we investigate this scenario by directly calculating the tidal

Michela Eleuteri, Francesca Prinari, Elvira Zappale

$3d-2d$ dimensional reduction for hyperelastic thin films modeled through energies with point dependent growth, assuming that the sample is clamped on the lateral boundary, is performed in the framework of $\Gamma$-convergence. Integral representation results, with a more regular lagrangian related to the original energy density, are provided for the lower d

Xianhan Tan, Junming Zhu, Jianmin Zhang, Yueming Wang

Speech brain-computer interfaces (BCIs), which translate brain signals into spoken words or sentences, have shown significant potential for high-performance BCI communication. Phonemes are the fundamental units of pronunciation in most languages. While existing speech BCIs have largely focused on English, where words contain diverse compositions of phonemes,

Zhao Song, Weixin Wang, Chenbo Yin, Junze Yin

The online weighted matching problem is a fundamental problem in machine learning due to its numerous applications. Despite many efforts in this area, existing algorithms are either too slow or don't take $\mathrm{deadline}$ (the longest time a node can be matched) into account. In this paper, we introduce a market model with $\mathrm{deadline}$ first. Next,

Hiroshi Hayasaka, Takashi Imoto, Yuichiro Matsuzaki, Shiro Kawabata

The counter diabatic (CD) driving has attracted much attention for suppressing non-adiabatic transition in quantum annealing (QA). However, it can be intractable to construct the CD driving in the actual experimental setup due to the non-locality of the CD dariving Hamiltonian and necessity of exact diagonalization of the QA Hamiltonian in advance. In this p

Ben Burgess-Limerick, Chris Lehnert Jurgen Leitner, Peter Corke

We present a robot base placement and control method that enables a mobile manipulator to gracefully recover from manipulation failures while performing tasks on-the-move. A mobile manipulator in motion has a limited window to complete a task, unlike when stationary where it can make repeated attempts until successful. Existing approaches to manipulation on-

Yue Wu, Jiafan He, Quanquan Gu

Recently, there has been remarkable progress in reinforcement learning (RL) with general function approximation. However, all these works only provide regret or sample complexity guarantees. It is still an open question if one can achieve stronger performance guarantees, i.e., the uniform probably approximate correctness (Uniform-PAC) guarantee that can impl

F. Michel Dekking

In the base phi expansion any natural number is written uniquely as a sum of powers of the golden mean with coefficients 0 and 1, where it is required that the product of two consecutive digits is always 0. We tackle the problem of describing how these expansions look like. We classify the positive parts of the base phi expansions according to their suffices

Yanling Li, Bowei Zou, Yifan Fan, Mengxing Dong

We tackle Multi-party Dialogue Reading Comprehension (abbr., MDRC). MDRC stands for an extractive reading comprehension task grounded on a batch of dialogues among multiple interlocutors. It is challenging due to the requirement of understanding cross-utterance contexts and relationships in a multi-turn multi-party conversation. Previous studies have made gr

Zhifeng Li, Bowei Zou, Yifan Fan, Yu Hong

Generative commonsense question answering (GenCQA) is a task of automatically generating a list of answers given a question. The answer list is required to cover all reasonable answers. This presents the considerable challenges of producing diverse answers and ranking them properly. Incorporating a variety of closely-related background knowledge into the enc

Clauvin Almeida, Marcos Kalinowski, Anderson Uchoa, Bruno Feijo

Context: While most research shows positive effects of gamification, the focus on its adverse effects is considerably smaller and further understanding is needed. Objective: To provide a comprehensive overview on research reporting negative effects of game design elements and to provide insights into the awareness of developers on these effects and into how

Fengyuan Xuan, MingRui Lai, Yaze Wu, Su Ying Quek

We show that excitonic resonances and interexciton transitions can enhance the probability of spontaneous parametric down-conversion, a second-order optical response which generates entangled photon pairs. We benchmark our ab initio many-body calculations using experimental polar plots of second harmonic generation in NbOI$_2$, clearly demonstrating the rele

Wei-I Lin, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama

Complementary-label Learning (CLL) is a form of weakly supervised learning that trains an ordinary classifier using only complementary labels, which are the classes that certain instances do not belong to. While existing CLL studies typically use novel loss functions or training techniques to solve this problem, few studies focus on how complementary labels

Atsushi Yoshimura, Takahiro Harada

Ray tracing is an essential operation for realistic image synthesis. The acceleration of ray tracing has been studied for a long period of time because algorithms such as light transport simulations require a large amount of ray tracing. One of the major approaches to accelerate the intersections is to use bounding volumes for early pruning for primitives in

Zhongyi Jiang, Chunmei Wang, Haizhao Yang

Nonlinear dynamics is a pervasive phenomenon observed in scientific and engineering disciplines. However, the task of deriving analytical expressions to describe nonlinear dynamics from limited data remains challenging. In this paper, we shall present a novel deep symbolic learning method called the "finite expression method" (FEX) to discover governing equa

Kotaro Suzuki, Tokuro Hata, Yuya Sato, Takafumi Akiho

Dynamics of integrable systems, such as Tomonaga-Luttinger (TL) liquids, is deterministic, and the absence of stochastic thermalization processes provides unique characteristics, such as long-lived non-thermal metastable states with many conserved quantities. Here, we show such non-thermal states can emerge even when the TL liquid is excited with extremely h

Ahnaf Rafi

Experiments that use covariate adaptive randomization (CAR) are commonplace in applied economics and other fields. In such experiments, the experimenter first stratifies the sample according to observed baseline covariates and then assigns treatment randomly within these strata so as to achieve balance according to pre-specified stratum-specific target assig

Danni Yu, Luyang Li, Hang Su, Matteo Fuoli

Certain forms of linguistic annotation, like part of speech and semantic tagging, can be automated with high accuracy. However, manual annotation is still necessary for complex pragmatic and discursive features that lack a direct mapping to lexical forms. This manual process is time-consuming and error-prone, limiting the scalability of function-to-form appr

Qingmin Zhang, Yuhao Zhou, Chuan Li, Qiao Li

In this paper, we carry out a detailed analysis of the M1.6 class eruptive flare occurring in NOAA active region 13078 on 2022 August 19. The flare is associated with a fast coronal mass ejection (CME) propagating in the southwest direction with an apparent speed of $\sim$926 km s$^{-1}$. Meanwhile, a shock wave is driven by the CME at the flank. The eruptio

Alex H. Lang, Anton D. Loukianov, Charles K. Fisher

Conditional generative models are capable of using contextual information as input to create new imaginative outputs. Conditional Restricted Boltzmann Machines (CRBMs) are one class of conditional generative models that have proven to be especially adept at modeling noisy discrete or continuous data, but the lack of expressivity in CRBMs have limited their w

Chenhao Li, Trung Thanh Ngo, Hajime Nagahara

In this work, we propose an inverse rendering model that estimates 3D shape, spatially-varying reflectance, homogeneous subsurface scattering parameters, and an environment illumination jointly from only a pair of captured images of a translucent object. In order to solve the ambiguity problem of inverse rendering, we use a physically-based renderer and a ne

Randolph Loh, Vrizlynn L. L. Thing

Self-Healing Cyber-Physical Systems (SH-CPS) effectively recover from system perceived failures without human intervention. They ensure a level of resilience and tolerance to unforeseen situations that arise from intrinsic system and component degradation, errors, or malicious attacks. Implicit redundancy can be exploited in SH-CPS to structurally adapt with

Yu Zeng, Alioscia Hamma, Yu-Ran Zhang, Qiang Liu

Effective light cones, characterized by Lieb-Robinson bounds, emerge in nonrelativistic local quantum systems. Here, we present several analytical results derived from logarithmic light cones (LLCs). Possible origins of LLCs include the one-dimensional (1D) disordered XXZ model and a phenomenological model of many-body localization (MBL). In the LLC regime,

Satoru Hayami, Yasuyuki Kato

A magnetic bubble crystal is a two-dimensional soliton lattice consisting of multiple spin density waves similar to a magnetic skyrmion crystal. Nevertheless, the emergence of the bubble crystal with a collinear spin texture is rare compared to that of the skyrmion crystal with a noncoplanar spin texture. Here we theoretically report the stabilization mechan

Miku Yoshida, Hiroto Arima, Aichi Yamashita, Ken-ichi Uchida

Thermal switching by magnetic fields is one of the important functionalities in thermal management technologies. In low-temperature devices, superconducting states can be used as a magneto-thermal-switching (MTS) component, because carrier thermal conductivity (\k{appa}) is strongly suppressed in superconducting states. Recently, we demonstrated that the MTS

Addisu Paulos

A Halin graph is a graph constructed by embedding a tree with no vertex of degree two in the plane and then adding a cycle to join the tree's leaves. The Halin Tur\'an number of a graph $F$, denoted as $\ex_{\hh}(n,F)$, is the maximum number of edges in an $n$-vertex Halin graph. In this paper, we give the exact value of $\ex_{\mathcal{H}}(n,C_4)$, where $C_

Rui Yang, Ercai Chen, Xiaoyao Zhou

It is well-known that $\epsilon$-stable sets have a deep connection with the topological entropy of dynamical systems. In the present paper, we investigate the relationships of three types of upper metric mean dimensions with potential between \emph{the blocks of $\epsilon$-stable sets, $\epsilon$-stable sets, the dispersion of preimages of $\epsilon$-stable

Ning An, Jiguang Bao, Zixiao Liu

The Liouville type theorem on the parabolic Monge--Amp\`ere equation $-u_t\det D^2u=1$ states that any entire parabolically convex classical solution must be of form $-t+|x|^2/2$ up to a re-scaling and transformation, under additional assumption that partial derivative with respect to time variable $u_t$ is strictly negative and bounded. In this paper, we st

Penghui Wei, Hongjian Dou, Shaoguo Liu, Rongjun Tang

Conversion rate (CVR) estimation aims to predict the probability of conversion event after a user has clicked an ad. Typically, online publisher has user browsing interests and click feedbacks, while demand-side advertising platform collects users' post-click behaviors such as dwell time and conversion decisions. To estimate CVR accurately and protect data p

Hao Wang, Chaobo Dong, Yaliang Gui, Jiachi Ye

Van der Waals (vdWs) heterostructures assembled by stacking 2D crystal layers have proven to be a new material platform for high-performance optoelectronic applications such as thin film transistors, photodetectors, and emitters. Here, we demonstrate a novel device with strain tuning capabilities using MoS2/Sb2Te3 vdWs p-n heterojunction devices designed for

Yun-Cheng Tsai

This paper explores the potential developments of self-directed learning in the metaverse in response to Education 4.0 and the Fourth Industrial Revolution. It highlights the importance of education keeping up with technological advancements and adopting learner-centered approaches. Additionally, it focuses on exploring value exchange systems through natural

Chih-Yuan Yao, Husan-Ting Chou, Yu-Sheng Lin, Kuo-wei Chen

Manga, as a widely beloved form of entertainment around the world, have shifted from paper to electronic screens with the proliferation of handheld devices. However, as the demand for image quality increases with screen development, high-quality images can hinder transmission and affect the viewing experience. Traditional vectorization methods require a sign

Bruce Olberding, Elaine A. Walker

We introduce the notion of a bisector field, which is a maximal collection of pairs of lines such that for each line in each pair, the midpoint of the points where the line crosses every pair is the same, regardless of choice of pair. We use this to study asymptotic properties of pencils of affine conics over fields and show that pairs of lines in the plane

Yang Liu, Tim Althoff, Jeffrey Heer

A multiverse analysis evaluates all combinations of "reasonable" analytic decisions to promote robustness and transparency, but can lead to a combinatorial explosion of analyses to compute. Long delays before assessing results prevent users from diagnosing errors and iterating early. We contribute (1) approximation algorithms for estimating multiverse sensit

Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang

New NLP benchmarks are urgently needed to align with the rapid development of large language models (LLMs). We present C-Eval, the first comprehensive Chinese evaluation suite designed to assess advanced knowledge and reasoning abilities of foundation models in a Chinese context. C-Eval comprises multiple-choice questions across four difficulty levels: middl

Ri He, Hua Wang, Fucai Liu, Shi Liu

The switching dynamics of ferroelectric materials is a crucial intrinsic property which directly affects the operation and performance of ferroelectric devices. In conventional ferroelectric materials, the typical ferroelectric switching mechanism is governed by a universal process of domain wall motion. However, recent experiments indicate that Van der Waal

Rohan Pandey

What is sentence meaning and its ideal representation? Much of the expressive power of human language derives from semantic composition, the mind's ability to represent meaning hierarchically & relationally over constituents. At the same time, much sentential meaning is outside the text and requires grounding in sensory, motor, and experiential modalities to

V. V. Kocharovsky, Vl. V. Kocharovsky, W. D. Shannon, S. V. Tarasov

We describe boson sampling of interacting atoms from the noncondensed fraction of Bose-Einstein-condensed (BEC) gas confined in a box trap as a new platform for studying computational #P-hardness and quantum supremacy of many-body systems. We calculate the characteristic function and statistics of atom numbers via newly found hafnian master theorem. Using Bl

Suguman Bansal, Yong Li, Lucas Martinelli Tabajara, Moshe Y. Vardi

The innovations in reactive synthesis from {\em Linear Temporal Logics over finite traces} (LTLf) will be amplified by the ability to verify the correctness of the strategies generated by LTLf synthesis tools. This motivates our work on {\em LTLf model checking}. LTLf model checking, however, is not straightforward. The strategies generated by LTLf synthesis

Shuhang Tan, Hengyu Liu, Zhiling Wang

Relocalization is the basis of map-based localization algorithms. Camera and LiDAR map-based methods are pervasive since their robustness under different scenarios. Generally, mapping and localization using the same sensor have better accuracy since matching features between the same type of data is easier. However, due to the camera's lack of 3D information

Maziar Goudarzi, Reza Azimi, Julian Humecki, Faizaan Rehman

Load-Dependent Branches (LDB) often do not exhibit regular patterns in their local or global history and thus are inherently hard to predict correctly by conventional branch predictors. We propose a software-to-hardware branch pre-resolution mechanism that allows software to pass branch outcomes to the processor frontend ahead of fetching the branch instruct

Ziyuan Zhao, Peisheng Qian, Xulei Yang, Zeng Zeng

Protein-protein interactions (PPIs) are crucial in various biological processes and their study has significant implications for drug development and disease diagnosis. Existing deep learning methods suffer from significant performance degradation under complex real-world scenarios due to various factors, e.g., label scarcity and domain shift. In this paper,

Hone-Jay Chu, Po-Hung Chen, Sheng-Mao Chang, Muhammad Zeeshan Ali

Geographically weighted regression (GWR) is a popular tool for modeling spatial heterogeneity in a regression model. However, the current weighting function used in GWR only considers the geographical distance, while the attribute similarity is totally ignored. In this study, we proposed a covariate weighting function that combines the geographical distance

Taira Kawamura, Daichi Kagamihara, Yoji Ohashi

We theoretically investigate a Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) type superfluid phase transition in a driven-dissipative two-component Fermi gas. The system is assumed to be in the non-equilibrium steady state, which is tuned by adjusting the chemical potential difference between two reservoirs that are coupled with the system. Including pairing fluct

Yu Funami, Kazushi Aoyama

We theoretically investigate the effects of surface acoustic waves (SAWs) on an electric-field-driven sliding motion of a one-dimensional charge density wave (CDW), which is initially pinned by impurities. By numerically analyzing an extended Fukuyama-Lee-Rice model, we show that a mechanical vibration of the SAW, which, in the model, is assumed to affect th

Dongyi Wang, Yuanchen Deng, Mourad Oudich, Wladimir A. Benalcazar

Higher-order topological band theory has transformed the landscape of topological phases in quantum and classical systems. Here, we experimentally demonstrate a two-dimensional (2D) higher-order topological phase (HOTP), referred to as the multiple chiral topological phase (MCTP), which is protected by a multipole chiral number (MCN). Our realization differs

J. G. Gluschke, J. Seidl, R. W. Lyttleton, K. Nguyen

A central endeavour in bioelectronics is the development of logic elements to transduce and process ionic to electronic signals. Motivated by this challenge, we report fully monolithic, nanoscale logic elements featuring n- and p-type nanowires as electronic channels that are proton-gated by electron-beam patterned Nafion. We demonstrate inverter circuits wi

Xing-Shuo Xu, Xiang-Fa Zhou, Guang-Can Guo, Zheng-Wei Zhou

In open systems, topological edge states quickly lose coherence and cannot be used in topological quantum computation and quantum memory. Here we show that for dissipative quantum spin (or fermionic) systems, topologically non-Hermitian Liouville-Majorana edge modes (LMEMs) can survive in the extended Liouville-Fock space, which is beyond the scope of topolo

Shuning Lin, Yong Chen

We propose gradient-enhanced PINNs based on transfer learning (TL-gPINNs) for inverse problems of the function coefficient discovery in order to overcome deficiency of the discrete characterization of the PDE loss in neural networks and improve accuracy of function feature description, which offers a new angle of view for gPINNs. The TL-gPINN algorithm is ap

Dara Tafazoli

Over the last two decades, technology use in language learning and teaching has significantly advanced and is now referred to as Computer-Assisted Language Learning (CALL). Recently, the integration of Artificial Intelligence (AI) into CALL has brought about a significant shift in the traditional approach to language education both inside and outside the cla

J. Seidl, J. G. Gluschke, X. Yuan, H. H. Tan

We report on the post-growth shaping of free-standing 2D InAs nanofins that are grown by selective-area epitaxy and mechanically transferred to a separate substrate for device fabrication. We use a citric acid based wet etch that enables complex shapes, e.g., van der Pauw cloverleaf structures, with patterning resolution down to 150 nm as well as partial thi

Bill Jacob, Nathan Schley

Let $p$ be an odd prime, $F$ a field with a primitive $p^2$th root of unity, and $E=F(\sqrt[p]{b_1},\sqrt[p]{b_2})$ an elementary abelian extension of degree $p^2$. This paper studies the cohomological kernel $H^n(E/F,{\mathbb Z}/p{\mathbb Z}):={\rm ker}(H^n(F,{\mathbb Z}/p{\mathbb Z})\rightarrow H^n(E,{\mathbb Z}/p{\mathbb Z}))$ for all $n$. When $p=3$, usi

Yue Wu, Lin Zhong

The Minimum-Weight Perfect Matching (MWPM) decoder is widely used in Quantum Error Correction (QEC) decoding. Despite its high accuracy, existing implementations of the MWPM decoder cannot catch up with quantum hardware, e.g., 1 million measurements per second for superconducting qubits. They suffer from a backlog of measurements that grows exponentially and

Byunggi Kim, Hodaka Kurokawa, Katsuta Sakai, Kazuki Koshino

Quantum transduction between microwave and optical photons plays a key role in quantum communication among remote qubits. Although the quantum transduction schemes generating communication photons have been successfully demonstrated by using optomechanical interfaces, the low conversion efficiency remains an obstacle to the implementation of a quantum networ

Ziyang Gan, Kaixuan Zhang, Yuan Gao, Ahai Chen

The nature of electronic motion and structural information of atoms and molecules is encoded into strong-field induced radiations ranging from terahertz (THz) to extreme ultraviolet wavelength. The dependence of THz yields in bi-chromatic laser fields on ellipticity and interpulse phase delay were experimentally measured, and the trajectory calculations esta

D. Maryenko, I. V. Maznichenko, S. Ostanin, M. Kawamura

Design of epitaxial interfaces is a pivotal way to engineer artificial structures where new electronic phases can emerge. Here we report a systematic emergence of interfacial superconducting state in epitaxial heterostructures of LaTiO3 and KTaO3. The superconductivity transition temperature increases with decreasing the thickness of LaTiO3. Such behavior is

Qiyu Hu, Yunlong Cai, Guangyi Zhang, Guanding Yu

The stringent performance requirements of future wireless networks, such as ultra-high data rates, extremely high reliability and low latency, are spurring worldwide studies on defining the next-generation multiple-input multiple-output (MIMO) transceivers. For the design of advanced transceivers in wireless communications, optimization approaches often lead

Aboli Marathe, Sanjana Prabhu

In the classical supervised learning settings, classifiers are fit with the assumption of balanced label distributions and produce remarkable results on the same. In the real world, however, these assumptions often bend and in turn adversely impact model performance. Identifying bad learners in skewed target distributions is even more challenging. Thus achie

Zexue He, An Yan, Amilcare Gentili, Julian McAuley

Sharing medical reports is essential for patient-centered care. A recent line of work has focused on automatically generating reports with NLP methods. However, different audiences have different purposes when writing/reading medical reports -- for example, healthcare professionals care more about pathology, whereas patients are more concerned with the diagn

Silvio Alonso, Marcos Kalinowski, Bruna Ferreira, Simone D. J. Barbosa

[Background] The MVP concept has influenced the way in which development teams apply Software Engineering practices. However, the overall understanding of this influence of MVPs on SE practices is still poor. [Objective] Our goal is to characterize the publication landscape on practices that have been used in the context of software MVPs and to gather practi

Jerry Wei, Le Hou, Andrew Lampinen, Xiangning Chen

We present symbol tuning - finetuning language models on in-context input-label pairs where natural language labels (e.g., "positive/negative sentiment") are replaced with arbitrary symbols (e.g., "foo/bar"). Symbol tuning leverages the intuition that when a model cannot use instructions or natural language labels to figure out a task, it must instead do so