April 2024 arXiv papers — page 64

L. Aragão, A. Armigliato, R. Brancaccio, C. Brofferio

Many of the most sensitive physics experiments searching for rare events, like neutrinoless double beta ($0\nu\beta\beta$) decay and dark matter interactions, rely on cryogenic macro-calorimeters operating at the mK-scale. Located underground at the Gran Sasso National Laboratory (LNGS), in central Italy, CUORE (Cryogenic Underground Observatory for Rare Eve

J. -P. Allouche, J. -Y. Yao

In this work we introduce a new notion called opacity complexity to measure the complexity of automatic sequences. We study basic properties of this notion, and exhibit an algorithm to compute it. As applications, we compute the opacity complexity of some well-known automatic sequences, including in particular constant sequences, purely periodic sequences, t

Zirui Wang, Chen Yao, Yangtao Ge, Guowei Shi

So far, planetary surface exploration depends on various mobile robot platforms. The autonomous navigation and decision-making of these mobile robots in complex terrains largely rely on their terrain-aware perception, localization and mapping capabilities. In this paper we release the TAIL-Plus dataset, a new challenging dataset in deformable granular enviro

João Gama, Rita P. Ribeiro, Saulo Mastelini, Narjes Davarid

Predictive Maintenance applications are increasingly complex, with interactions between many components. Black box models are popular approaches based on deep learning techniques due to their predictive accuracy. This paper proposes a neural-symbolic architecture that uses an online rule-learning algorithm to explain when the black box model predicts failure

Zhijun Xu, Siyu Yuan, Lingjie Chen, Deqing Yang

Puns play a vital role in academic research due to their distinct structure and clear definition, which aid in the comprehensive analysis of linguistic humor. However, the understanding of puns in large language models (LLMs) has not been thoroughly examined, limiting their use in creative writing and humor creation. In this paper, we leverage three popular

Xinyang Du, Xuming Fang

The continuous evolution of future mobile communication systems is heading towards the integration of communication and computing, with Mobile Edge Computing (MEC) emerging as a crucial means of implementing Artificial Intelligence (AI) computation. MEC could enhance the computational performance of wireless edge networks by offloading computing-intensive ta

Ai-Ying Ye, Zhao Yang Zeng

Fano resonance is believed to arise when a direct path interferes with a resonant path. We demonstrate that this is not true for chiral electronic transmission without additional direct paths. To address the Fano effect in chiral electronic transport, we suggest an electronic Mach-Zehnder-Fano interferometer (MZFI), which combines a quantum dot with an elect

Bin Liu, Huanyuan Shan, Jiajun Zhang

We exploit the recent {\it James Webb Space Telescope} (JWST) determination of galaxy UV luminosity functions over the redshift range $z=9-14.5$ to derive constraints on warm dark matter (WDM) models. The delayed structure formation in WDM universes make high-redshift observations a powerful probe to set limits on the particle mass $m_\mathrm{x}$ of WDM cand

Hao Peng, Jingyun Zhang, Xiang Huang, Zhifeng Hao

Research on social bot detection plays a crucial role in maintaining the order and reliability of information dissemination while increasing trust in social interactions. The current mainstream social bot detection models rely on black-box neural network technology, e.g., Graph Neural Network, Transformer, etc., which lacks interpretability. In this work, we

Georgios Pantazopoulos, Alessandro Suglia, Oliver Lemon, Arash Eshghi

An effective method for combining frozen large language models (LLM) and visual encoders involves a resampler module that creates a `visual prompt' which is provided to the LLM, along with the textual prompt. While this approach has enabled impressive performance across many coarse-grained tasks like image captioning and visual question answering, more fine-

Yousef Khan, Ahmed Abdeen Hamed

Addressing the global challenge of breast cancer, this research explores the fusion of generative AI, focusing on ChatGPT 3.5 turbo model, and the intricacies of breast cancer risk assessment. The research aims to evaluate ChatGPT's reasoning capabilities, emphasizing its potential to process rules and provide explanations for screening recommendations. The

Pooja, Bikash Saha, Nitesh Choudhary, Pradip K. Maji

Strongly correlated system with competing ground states are often poised close to the quantum critical point. External perturbations such as pressure, strain, electric field, and chemical doping can stabilise its ground state with exotic physical properties. Cr-doping is the lone exception which enhances the Curie-temperature in one of such correlated system

Michael Herrmann, Dirk Janßen

We study single-interface solutions to a free boundary problem that couples bilinear bulk diffusion to the Stefan condition and a hysteretic flow rule for phase boundaries. We introduce a time-discrete approximation scheme and establish its convergence in the limit of vanishing step size. The main difficulty in our proof are strong microscopic oscillations w

Yifan Jiang, Jiarui Zhang, Kexuan Sun, Zhivar Sourati

While multi-modal large language models (MLLMs) have shown significant progress on many popular visual reasoning benchmarks, whether they possess abstract visual reasoning abilities remains an open question. Similar to the Sudoku puzzles, abstract visual reasoning (AVR) problems require finding high-level patterns (e.g., repetition constraints) that control

L. M. Martelo, Aires Ferreira

The emergence of strong relativistic spin-orbit effects in low-dimensional systems provides a rich opportunity for exploring unconventional states of matter. Here, we present a route to realise tunable relativistic band structures based on the lateral patterning of proximity-induced spin-orbit coupling. The concept is illustrated on a patterned graphene-tran

Marco Berrettini, Christian Hennig, Cinzia Viroli

Quantile-based classifiers can classify high-dimensional observations by minimising a discrepancy of an observation to a class based on suitable quantiles of the within-class distributions, corresponding to a unique percentage for all variables. The present work extends these classifiers by introducing a way to determine potentially different optimal percent

Huiqiang Chen, Tianqing Zhu, Xin Yu, Wanlei Zhou

Machine unlearning aims to enable models to forget specific data instances when receiving deletion requests. Current research centres on efficient unlearning to erase the influence of data from the model and neglects the subsequent impacts on the remaining data. Consequently, existing unlearning algorithms degrade the model's performance after unlearning, kn

Xiangyu Liang

In this paper, we prove that the product of a paired calibrated set and a set of codimension 1 calibrated by a coflat calibration with small singularity set is Almgren minimal. This is motivated by the attempt to classify all possible singularities for Almgren minimal sets--Plateau's problem in the setting of sets. In particular, a direct application of the

E. Keles, S. Czesla, K. Poppenhaeger, P. Hauschildt

Absorption lines from exoplanet atmospheres observed in transmission allow us to study atmospheric characteristics such as winds. We present a new high-resolution transit time-series of HD 189733b, acquired with the PEPSI instrument at the LBT and analyze the transmission spectrum around the Na D lines. We model the spectral signature of the RM-CLV-effect us

Shi Jin, Nana Liu, Yue Yu

This paper studies a quantum simulation technique for solving the Fokker-Planck equation. Traditional semi-discretization methods often fail to preserve the underlying Hamiltonian dynamics and may even modify the Hamiltonian structure, particularly when incorporating boundary conditions. We address this challenge by employing the Schrodingerization method-it

Zhanjie Zhang, Jiakai Sun, Guangyuan Li, Lei Zhao

Arbitrary style transfer holds widespread attention in research and boasts numerous practical applications. The existing methods, which either employ cross-attention to incorporate deep style attributes into content attributes or use adaptive normalization to adjust content features, fail to generate high-quality stylized images. In this paper, we introduce

Duy-Nam Bui, Manh Duong Phung

This paper addresses the problem of controlling multiple unmanned aerial vehicles (UAVs) cooperating in a formation to carry out a complex task such as surface inspection. We first use the virtual leader-follower model to determine the topology and trajectory of the formation. A double-loop control system combining backstepping and sliding mode control techn

L. K. Liu, C. L. Hu, X. H. He, S. S. Shi

The production of light nuclei and hyper-nuclei in heavy-ion collisions, particularly at high baryon density, is crucial for understanding the dynamical evolution of the collision system and exploring the internal state of nuclear matter of compacted stellar object. Despite being a topic of ongoing debate, an improved theoretical understanding is necessary.

Qingxin Xia, Takuya Maekawa, Jaime Morales, Takahiro Hara

In this study, we investigate a new self-supervised learning (SSL) approach for complex work activity recognition using wearable sensors. Owing to the cost of labeled sensor data collection, SSL methods for human activity recognition (HAR) that effectively use unlabeled data for pretraining have attracted attention. However, applying prior SSL to complex wor

E. E. Perepelkin, B. I. Sadovnikov, N. G. Inozemtseva, M. V. Klimenko

On the basis of the first principle -- the law of probability conservation and the Helmholtz decomposition theorem the authors have succeeded to construct the Schr\"odinger, Pauli, Dirac equation, the Hamilton-Jacobi equation and the Maxwell equations. The approach described in this paper makes it possible to naturally connect the classical and quantum syste

Xiaoran Zhao, Tianhao Wu, Yu Lai, Zhiliang Tian

Controllable text-to-image generation synthesizes visual text and objects in images with certain conditions, which are frequently applied to emoji and poster generation. Visual text rendering and layout-to-image generation tasks have been popular in controllable text-to-image generation. However, each of these tasks typically focuses on single modality gener

Salim Meddahi

A variational formulation based on velocity and stress is developed for linear fluid-structure interaction (FSI) problems. The well-posedness and energy stability of this formulation are established. To discretize the problem, a hybridizable discontinuous Galerkin method is employed. An $hp$-convergence analysis is performed for the resulting semi-discrete s

M. Anselmo, G. Castiglione, M. Flores, D. Giammarresi

In this paper we consider an edit distance with swap and mismatch operations, called tilde-distance, and introduce the corresponding definition of tilde-isometric word. Isometric words are classically defined with respect to Hamming distance and combine the notion of edit distance with the property that a word does not appear as factor in other words. A word

Songlin Dong, Yingjie Chen, Yuhang He, Yuhan Jin

Online task-free continual learning (OTFCL) is a more challenging variant of continual learning which emphasizes the gradual shift of task boundaries and learns in an online mode. Existing methods rely on a memory buffer composed of old samples to prevent forgetting. However,the use of memory buffers not only raises privacy concerns but also hinders the effi

Xu Yang, Jiapeng Zhang, Qifeng Zhang, Zhuo Tang

In federated learning, particularly in cross-device scenarios, secure aggregation has recently gained popularity as it effectively defends against inference attacks by malicious aggregators. However, secure aggregation often requires additional communication overhead and can impede the convergence rate of the global model, which is particularly challenging i

Luofu Liu, Chao Duan, Rui Wang

Trapping macromolecules is impoartant for the study of their conformations, interactions, dynamics and kinetic processes. Here, we develop a variational approach which self-consistently introduces a mean force that controls the center-of-mass position and a self-adjustable harmonic potential that counters the center-of-mass fluctuation. The effectiveness and

Bowen Qu, Xiaoyu Liang, Shangkun Sun, Wei Gao

The recent advancements in Text-to-Video Artificial Intelligence Generated Content (AIGC) have been remarkable. Compared with traditional videos, the assessment of AIGC videos encounters various challenges: visual inconsistency that defy common sense, discrepancies between content and the textual prompt, and distribution gap between various generative models

Ku-Jung Hsu, Lei Liu

In the past two decades, since the discovery of the figure-8 orbit by Chenciner and Montgomery, the variational method has became one of the most popular tools for constructing new solutions of the $N$-body problem and its extended problems. However, finding solutions to the restricted three-body problem, in particular, the two primaries form a collision Kep

Jiabin Guo

This article discusses the application of single vector hydrophones in the field of underwater acoustic signal processing for Direction Of Arrival (DOA) estimation. Addressing the limitations of traditional DOA estimation methods in multi-source environments and under noise interference, this study introduces a Vector Signal Reconstruction Sparse and Paramet

Jiaxin Zhang, Yiqi Wang, Xihong Yang, Siwei Wang

Graph Neural Networks have demonstrated great success in various fields of multimedia. However, the distribution shift between the training and test data challenges the effectiveness of GNNs. To mitigate this challenge, Test-Time Training (TTT) has been proposed as a promising approach. Traditional TTT methods require a demanding unsupervised training strate

Masayuki Yamaguchi, Takayuki Muto, Takashi Tsukagoshi, Hideko Nomura

In the past decade, ALMA observations of protoplanetary disks revealed various substructures including gaps and rings. Their origin may be probed through statistical studies on the physical properties of the substructures. We present the analyses of archival ALMA Band 6 continuum data of 43 disks (39 Class II and 4 Herbig Ae) in the Taurus-Auriga region. We

SeungHeon Doh, Jongpil Lee, Dasaem Jeong, Juhan Nam

Word embedding has become an essential means for text-based information retrieval. Typically, word embeddings are learned from large quantities of general and unstructured text data. However, in the domain of music, the word embedding may have difficulty understanding musical contexts or recognizing music-related entities like artists and tracks. To address

Jiabin Guo

This study investigates the application of single vector hydrophones in underwater acoustic signal processing for Direction of Arrival (DOA) estimation. Addressing the limitations of traditional DOA estimation methods in multi-source environments and under noise interference, this research proposes a Vector Signal Reconstruction (VSR) technique. This techniq

Suyeon Shin, Sujin jeon, Junghyun Kim, Gi-Cheon Kang

Embodied Instruction Following (EIF) is the task of executing natural language instructions by navigating and interacting with objects in interactive environments. A key challenge in EIF is compositional task planning, typically addressed through supervised learning or few-shot in-context learning with labeled data. To this end, we introduce the Socratic Pla

Abhilekha Dalal, Rushrukh Rayan, Adrita Barua, Eugene Y. Vasserman

A major challenge in Explainable AI is in correctly interpreting activations of hidden neurons: accurate interpretations would help answer the question of what a deep learning system internally detects as relevant in the input, demystifying the otherwise black-box nature of deep learning systems. The state of the art indicates that hidden node activations ca

Shadi Sartipi, Mujdat Cetin

Automated emotion recognition using electroencephalogram (EEG) signals has gained substantial attention. Although deep learning approaches exhibit strong performance, they often suffer from vulnerabilities to various perturbations, like environmental noise and adversarial attacks. In this paper, we propose an Inception feature generator and two-sided perturb

Gennaro Auricchio, Zihe Wang, Jie Zhang

In this paper, we investigate the Mechanism Design aspects of the $m$-Capacitated Facility Location Problem ($m$-CFLP) on a line. We focus on two frameworks. In the first framework, the number of facilities is arbitrary, all facilities have the same capacity, and the number of agents is equal to the total capacity of all facilities. In the second framework,

Panfeng Li, Qikai Yang, Xieming Geng, Wenjing Zhou

This study explores innovative methods for improving Visual Question Answering (VQA) using Generative Adversarial Networks (GANs), autoencoders, and attention mechanisms. Leveraging a balanced VQA dataset, we investigate three distinct strategies. Firstly, GAN-based approaches aim to generate answer embeddings conditioned on image and question inputs, showin

Yun Wu, Hao Xu, Maohua Gu, Zhongchuan Jiang

Dental fluorosis is a chronic disease caused by long-term overconsumption of fluoride, which leads to changes in the appearance of tooth enamel. It is an important basis for early non-invasive diagnosis of endemic fluorosis. However, even dental professionals may not be able to accurately distinguish dental fluorosis and its severity based on tooth images. C

Yu-Hong Liu, Jie-Qiao Liao

The preparation of mechanical quadrature-squeezed states holds significant importance in cavity optomechanics because the squeezed states have extensive applications in understanding fundamental quantum mechanics and exploiting modern quantum technology. Here, we propose a reliable scheme for generating mechanical quadrature squeezing in a typical cavity opt

Jie Yu, Luca Casagrande, Ioana Ciucă, Yuan-Sen Ting

Young {\alpha}-rich (YAR) stars within the old Galactic thick disk exhibit a dual characteristic of relative youth determined with asteroseismology and abundance enhancement in {\alpha} elements measured from high-resolution spectroscopy. The youth origin of YAR stars has been proposed to be binary evolution via mass transfer or stellar mergers. If that is t

Atsushi Hoshi, Toru Yamada, Mitsuru Kokubo, Yoshiki Matsuoka

We present the study on the relationship between SMBHs and their host galaxies using our variability-selected AGN sample ($i_\mathrm{AB} \leq 25.9,\ z \leq 4.5$) constructed from the HSC-SSP Ultra-deep survey in the COSMOS field. We estimated the BH mass ($M_\mathrm{BH}=10^{5.5-10}\ M_{\odot}$) based on the single-epoch virial method and the total stellar ma

Davide Spirito, María Barra-Burillo, Francesco Calavalle, Costanza Lucia Manganelli

Strain is an effective strategy to modulate the optoelectronic properties of 2D materials, but it has been almost unexplored in layered hybrid organic-inorganic metal halide perovskites (HOIPs) due to their complex band structure and mechanical properties. Here, we investigate the temperature-dependent microphotoluminescence (PL) of 2D $(C_6H_5CH_2CH_2NH_3)_

Lior Bary-Soroker, Noam Goldgraber

Choose a polynomial $f$ uniformly at random from the set of all monic polynomials of degree $n$ with integer coefficients in the box $[-L,L]^n$. The main result of the paper asserts that if $L=L(n)$ grows to infinity, then the Galois group of $f$ is the full symmetric group, asymptotically almost surely, as $n\to \infty$. When $L$ grows rapidly to infinity,

Haoyu Zheng, Wenqiao Zhang, Yaoke Wang, Juncheng Li

Revolutionary advancements in text-to-image models have unlocked new dimensions for sophisticated content creation, such as text-conditioned image editing, enabling the modification of existing images based on textual guidance. This capability allows for the generation of diverse images that convey highly complex visual concepts. However, existing methods pr

Xiaoyu Wang, Ryan P. Kelly, David J. Warne, Christopher Drovandi

Simulation based inference (SBI) methods enable the estimation of posterior distributions when the likelihood function is intractable, but where model simulation is feasible. Popular neural approaches to SBI are the neural posterior estimator (NPE) and its sequential version (SNPE). These methods can outperform statistical SBI approaches such as approximate

Kelong Mao, Chenlong Deng, Haonan Chen, Fengran Mo

Conversational search requires accurate interpretation of user intent from complex multi-turn contexts. This paper presents ChatRetriever, which inherits the strong generalization capability of large language models to robustly represent complex conversational sessions for dense retrieval. To achieve this, we propose a simple and effective dual-learning appr

Mahmood Saeedi kelishami, Amin Saeidi Kelishami, Sajjad Saeedi Kelishami

This study introduces an innovative approach to classifying various types of Persian rice using image-based deep learning techniques, highlighting the practical application of everyday technology in food categorization. Recognizing the diversity of Persian rice and its culinary significance, we leveraged the capabilities of convolutional neural networks (CNN

Alexandru Fikl, Aman Jhinga, Eva Kaslik, Argha Mondal

We introduce an efficient discretization of a novel fractional-order adaptive exponential (FrAdEx) integrate-and-fire model, which is used to study the fractional-order dynamics of neuronal activities. The discretization is based on extension of L1-type methods that can accurately handle the exponential growth and the spiking mechanism of the model. This new

Pengfei Huang, Hao Sun

In the wild nonabelian Hodge correspondence on curves, filtered Stokes G-local systems are regarded as the objects on the Betti side. In this paper, we demonstrate a construction of the moduli space of them, called the Betti moduli space, and it reduces to the wild character variety when the Betti weights are trivial. We study some particular examples includ

Kasra Naftchi-Ardebili, Mike D. Menz, Hossein Salahshoor, Gerald R. Popelka

Transcranial focused ultrasound stimulation (TUS) holds promise for non-invasive neural modulation in treating neurological disorders. Most clinically relevant targets are deep within the brain (near or at its geometric center), surrounded by other sensitive regions that need to be spared clinical intervention. However, in TUS, increasing frequency with the

Kin Wai Lau, Yasar Abbas Ur Rehman, Lai-Man Po

Recent research has successfully adapted vision-based convolutional neural network (CNN) architectures for audio recognition tasks using Mel-Spectrograms. However, these CNNs have high computational costs and memory requirements, limiting their deployment on low-end edge devices. Motivated by the success of efficient vision models like InceptionNeXt and Conv

Kang You, Kai Liu, Li Yu, Pan Gao

Despite considerable progress being achieved in point cloud geometry compression, there still remains a challenge in effectively compressing large-scale scenes with sparse surfaces. Another key challenge lies in reducing decoding latency, a crucial requirement in real-world application. In this paper, we propose Pointsoup, an efficient learning-based geometr

Bikash K. Das, C. Granados, M. Kruger, M. F. Ciappina

We investigate the interference of high-order perfect optical vortex (POV) beams with different topological charges. Through numerical simulations, we reveal a remarkable phenomenon: keeping the beam width, and beam radius fixed while changing the topological charge, the splitting of the composite POV beam into two distinct individual perfect vortices occurs

Shuai-Shuai Guo

The tidal interactions of planets affect the stellar evolutionary status and the constraint of their physical parameters by gyrochronology. In this work, we incorporate the tidal interaction and magnetic braking of the stellar wind into MESA and calculate a large grid of 25000 models, covering planets with masses of 0.1-13.0$\,$$M_{\mathrm{J}}$ with differen

H. Hedayatirad, T. L. Shateri

In the present paper, we introduce the notion of controlled $E$-frames. Then we investigate and study some properties of them and characterize all controlled $E$-duals associated with a given controlled $E$-frame.

Mao-Siang Chen, An-Zi Yen

To optimize the preparation process for educators in academic lectures and associated question-and-answer sessions, this paper presents E-QGen, a lecture abstract-based question generation system. Given a lecture abstract, E-QGen generates potential student inquiries. The questions suggested by our system are expected to not only facilitate teachers in prepa

Rishu Verma, Ankush, B. C. Chauhan

The nature of neutrino (whether Majorana or Dirac) and the origin of neutrino masses are still some of the mysteries to be resolved. Also, the recent results on (g-2)$_{e,\mu}$ measurements deviate from the Standard Model (SM) predictions and motivate us towards new physics beyond the SM. In this work, we propose a model with the minimal field content in the

Lida Zhang

Motivated by Einstein's thought experiment that a single quantum particle diffracted after a pinhole could in principle produce an action in two or several places on a hemispherical imaging screen, here we explore theoretically the possibility to simultaneously detect the action of a single photon at two remote places. This is considered in a cascade quantum

Jieyu Zheng, Haoliang Zhu, Yifan Dong, Zhenyu Song

TLS is extensively utilized for secure data transmission over networks. However, with the advent of quantum computers, the security of TLS based on traditional public-key cryptography is under threat. To counter quantum threats, it is imperative to integrate post-quantum algorithms into TLS. Most PQ-TLS research focuses on integration and evaluation, but few

Xiangyu Liang

This article is dedicated to discuss the sliding stability and the uniqueness property for the 2-dimensional minimal cone YXY in R4. This problem is motivated by the classification of singularities for Almgren minimal sets, a model for Plateau's problem in the setting of sets. Minimal cones are blow up limits of Almgren minimal sets, thus the list of all min

Ian R. Edmonds

Oceanic atmospheric oscillations and climate variability are tightly linked and both exhibit broad band spectral content that ranges, with roughly equal strength, from annual to centennial periodicity. The explanation for variability based on the integration of weather noise leads to a spectral content heavily weighted to low frequencies; explaining the vari

Haechan Lee, Wonjoon Jin, Seung-Hwan Baek, Sunghyun Cho

In this paper, we propose the first generalizable view synthesis approach that specifically targets multi-view stereo-camera images. Since recent stereo matching has demonstrated accurate geometry prediction, we introduce stereo matching into novel-view synthesis for high-quality geometry reconstruction. To this end, this paper proposes a novel framework, du

Xiangyu Liang

We prove that the k-medial axis of an arbitrary closed set in Rn is n-k+1-rectifiable (and hence of dimension at most n-k+1). This result gives a first stratification for medial axis of any closed set, which has been widely studied and used in pure and applied mathematics. This also answers a question proposed by Erdos[4], and leads to more further interesti

Saeid Alikhani, Fatemeh Aghaei

The domination polynomial (the total domination polynomial) of a graph $ G $ of order $ n $ is the generating function of the number of dominating sets (total dominating sets) of $ G $ of any size. In this paper, we study the domination polynomial and the total domination polynomial of zero-divisor graphs of the ring $ \mathbb{Z}_n $ where $ n\in\lbrace 2p,

Pramit Rej

Dark energy is one of the potential strategies for preventing compact objects from gravitationally collapsing into singularities. Because it is the cause of the accelerated expansion of our universe, it has the greatest impact on the cosmos. Thus, it is plausible that dark energy will interact with any stellar object that is compact in the universe [\textit{

Genggeng Chen, Kexin Dai, Kangzhen Yang, Tao Hu

In real-world scenarios, due to a series of image degradations, obtaining high-quality, clear content photos is challenging. While significant progress has been made in synthesizing high-quality images, previous methods for image restoration and enhancement often overlooked the characteristics of different degradations. They applied the same structure to add

Yuan Fang, Xianghao Yu, Jie Xu

This paper studies multi-active intelligent-reflecting-surface (IRS) cooperative sensing, in which multiple active IRSs are deployed in a distributed manner to help the base station (BS) provide multi-view sensing. We focus on the scenario where the sensing target is located in the non-line-of-sight (NLoS) area of the BS. Based on the received echo signal, t

Xueying Zeng, Youquan Xian, Chunpei Li, Zhengdong Hu

Blockchain technology ensures secure and trustworthy data flow between multiple participants on the chain, but interoperability of on-chain and off-chain data has always been a difficult problem that needs to be solved. To solve the problem that blockchain systems cannot access off-chain data, oracle is introduced. However, existing research mainly focuses o

Zhilin Huang, Yijie Yu, Ling Yang, Chujun Qin

With the advancement of AIGC, video frame interpolation (VFI) has become a crucial component in existing video generation frameworks, attracting widespread research interest. For the VFI task, the motion estimation between neighboring frames plays a crucial role in avoiding motion ambiguity. However, existing VFI methods always struggle to accurately predict

Sirui Chen, Jeannette Bohg, C. Karen Liu

Generating stable and robust grasps on arbitrary objects is critical for dexterous robotic hands, marking a significant step towards advanced dexterous manipulation. Previous studies have mostly focused on improving differentiable grasping metrics with the assumption of precisely known object geometry. However, shape uncertainty is ubiquitous due to noisy an

Andreas Bartel, Malak Diab, Andreas Frommer, Michael Günther

In the simulation of differential-algebraic equations (DAEs), it is essential to employ numerical schemes that take into account the inherent structure and maintain explicit or hidden algebraic constraints without altering them. This paper focuses on operator-splitting techniques for coupled systems and aims at preserving the structure in the port-Hamiltonia

Aviral Agrawal, Carlos Mateo Samudio Lezcano, Iqui Balam Heredia-Marin, Prabhdeep Singh Sethi

Video-based Question Answering (Video QA) is a challenging task and becomes even more intricate when addressing Socially Intelligent Question Answering (SIQA). SIQA requires context understanding, temporal reasoning, and the integration of multimodal information, but in addition, it requires processing nuanced human behavior. Furthermore, the complexities in

Rodrigo Aldana-López, Alessandro Macchelli, Giuseppe Notarstefano, Rosario Aragüés

This paper introduces a novel distributed optimization technique for networked systems, which removes the dependency on specific parameter choices, notably the learning rate. Traditional parameter selection strategies in distributed optimization often lead to conservative performance, characterized by slow convergence or even divergence if parameters are not

Wei Niu, Md Musfiqur Rahman Sanim, Zhihao Shu, Jiexiong Guan

This work is motivated by recent developments in Deep Neural Networks, particularly the Transformer architectures underlying applications such as ChatGPT, and the need for performing inference on mobile devices. Focusing on emerging transformers (specifically the ones with computationally efficient Swin-like architectures) and large models (e.g., Stable Diff

Jinghan A Zeng, Ruta Mehta

Fair division is the problem of allocating a set of items among agents in a fair manner. One of the most sought-after fairness notions is envy-freeness (EF), requiring that no agent envies another's allocation. When items are indivisible, it ceases to exist, and envy-freeness up to any good (EFX) emerged as one of its strongest relaxations. The existence of

Yu-Hui Wang, Li-Hang Ren, Ming-Liang Hu, Yan-Kui Bai

Coherence is intrinsically related to projective measurement. When the fixed projective measurement involves higher-rank projectors, the coherence resource is referred to as block coherence, which comes from the superposition of orthogonal subspaces. Here, we establish a set of quantitative relations for the interconversion between block coherence and multip

Bin Huang, Changchen Zhao, Zimeng Liu, Shenda Hong

Good health and well-being is among key issues in the United Nations 2030 Sustainable Development Goals. The rising prevalence of large-scale infectious diseases and the accelerated aging of the global population are driving the transformation of healthcare technologies. In this context, establishing large-scale public health datasets, developing medical mod

Renjie Xu, Tong Wei, Yimin Wei, Pengpeng Xie

Matrix decompositions in dual number representations have played an important role in fields such as kinematics and computer graphics in recent years. In this paper, we present a QR decomposition algorithm for dual number matrices, specifically geared towards its application in traveling wave identification, utilizing the concept of proper orthogonal decompo

Makoto Nagata, Yoshinori Takei

In a proof of the three gaps theorem, a class of permutations known as the S\'{o}s permutations was introduced. It is known that a S\'{o}s permutation, as a sequence, satisfies a certain recurrence (S\'{o}s's recurrence), however, whether the converse holds remains unknown. On the other hand, the inverses of S\'{o}s permutations have been studied also. It ha

Rajat Kumar Goyal

Current condensed matter research is centered on advanced materials and their distinctive features. The interest in Quantum materials (QMs) continues to increase without any decrease due to their novel phenomenon and potential as platforms for revolutionary new technologies in modern science and technology. This article emphasizes the exploration of diverse

Martin R. Pfaller, Marcos Latorre, Erica L. Schwarz, Fannie M. Gerosa

Equilibrated fluid-solid-growth (FSGe) is a fast, open source, three-dimensional (3D) computational platform for simulating interactions between instantaneous hemodynamics and long-term vessel wall adaptation through mechanobiologically equilibrated growth and remodeling (G&R). Such models can capture evolving geometry, composition, and material properties i

Ningsheng Zhao, Jia Yuan Yu, Krzysztof Dzieciolowski, Trang Bui

Shapley value attribution (SVA) is an increasingly popular explainable AI (XAI) method, which quantifies the contribution of each feature to the model's output. However, recent work has shown that most existing methods to implement SVAs have some drawbacks, resulting in biased or unreliable explanations that fail to correctly capture the true intrinsic relat

Yue Jiang, Changkong Zhou, Vikas Garg, Antti Oulasvirta

Present-day graphical user interfaces (GUIs) exhibit diverse arrangements of text, graphics, and interactive elements such as buttons and menus, but representations of GUIs have not kept up. They do not encapsulate both semantic and visuo-spatial relationships among elements. To seize machine learning's potential for GUIs more efficiently, Graph4GUI exploits

Samuel Fielder, Helen Kirk, Michael Dunham, Stella Offner

We present Atacama Large Millimeter/submillimeter Array (ALMA) Cycle 3 observations of 73 starless and protostellar cores in the Orion B North molecular cloud. We detect a total of 34 continuum sources at 106 GHz, and after comparisons with other data, 4 of these sources appear to be starless. Three of the four sources are located near groupings of protostel

Junwen Lai, Xiangyang Liu, Jie Zhan, Tianye Yu

Topological insulating states in two-dimensional (2D) materials are ideal systems to study different types of quantized response signals due to their in gap metallic states. Very recently, the quantum spin Hall (QSH) effect was discovered in monolayer $\text{TaIrTe}_4$ via the observation of quantized longitudinal conductance that rarely exists in other 2D t

Xiping Liu, Zhao Tan

The conversion of natural language queries into SQL queries, known as Text-to-SQL, is a critical yet challenging task. This paper introduces EPI-SQL, a novel methodological framework leveraging Large Language Models (LLMs) to enhance the performance of Text-to-SQL tasks. EPI-SQL operates through a four-step process. Initially, the method involves gathering i

Hongyu Zhu, Sichu Liang, Wentao Hu, Fangqi Li

With the rise of Machine Learning as a Service (MLaaS) platforms,safeguarding the intellectual property of deep learning models is becoming paramount. Among various protective measures, trigger set watermarking has emerged as a flexible and effective strategy for preventing unauthorized model distribution. However, this paper identifies an inherent flaw in t

Zhifu Gao, Luiz C. Garcia de Andrade

In this paper, we delve into the influence of torsion axial pseudo vector on dark photons in an axion torsionic background, as investigated previously by Duncan et al[ Nucl Phys B 387:215 (1992)]. Notably, axial torsion, owing to its significantly greater mass compared to axions, gives rise to magnetic helicity in torsionful Chern-Simons (CS) electrodynamics

Tanmoy Bhattacharya, Vincenzo Cirigliano, Rajan Gupta, Emanuele Mereghetti

We present results from our lattice QCD study of the contribution of the isovector quark cEDM (qcEDM) operator to the neutron EDM. The calculation was carried out on four 2+1+1-flavor highly improved staggered quark ensembles (provided to us by the MILC collaboration) using Wilson-clover quarks to construct correlation functions. We use the nonsinglet axial

Yuxuan Zhu, Jiachen Liu, Mosharaf Chowdhury, Fan Lai

Federated learning (FL) aims to train machine learning (ML) models across potentially millions of edge client devices. Yet, training and customizing models for FL clients is notoriously challenging due to the heterogeneity of client data, device capabilities, and the massive scale of clients, making individualized model exploration prohibitively expensive. S

Anna Maria Bigatti, Elisa Palezzato, Michele Torielli

A Comprehensive Grobner system for a parametric ideal I in K(A)[X] represents the collection of all Grobner bases of the ideals I' in K[X] obtained as the values of the parameters A vary in K. The recent algorithms for computing them comprehensive Grobner systems consider the corresponding ideal J in K[A,X], and are based on stability of Grobner bases of ide

Jinghao Deng, Deping Guo, Yao Wen, Shuangzan Lu

A reduced dimensionality of multiferroic materials is highly desired for device miniaturization, but the coexistence of ferroelectricity and magnetism at the two-dimensional limit is yet to be conclusively demonstrated. Here, we used a NbSe2 substrate to break both the C3 rotational and inversion symmetries in monolayer VCl3 and thus introduced exceptional i

Yilang Hao, Zhibin Chen, Xiaotong Sun, Lu Tong

Truck platooning, a linking technology of trucks on the highway, has gained enormous attention in recent years due to its benefits in energy and operation cost savings. However, most existing studies on truck platooning limit their focus on scenarios in which each truck can serve only one customer demand and is thus with a specified origin-destination pair,

Sagar Chakraborty

Information is everywhere in nature which is very uncertain and unpredictable. But information, in itself, is a very ambiguous term. In this cursory write-up, we attempt to understand the formal meaning of information by quantifying uncertainty and discuss how it naturally appears in two core topics of classical physics -- classical mechanics and statistical