May 2023 arXiv papers — page 175

Yang Deng, Wenqiang Lei, Wai Lam, Tat-Seng Chua

Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direction towards achieving pre-defined targets or fulfilling certain goals from the system side. It is empowered by advanced techniques to progress to more complicated tasks that requir

Zhongwei Yu, Jingqing Ruan, Dengpeng Xing

Generating explanations for reinforcement learning (RL) is challenging as actions may produce long-term effects on the future. In this paper, we develop a novel framework for explainable RL by learning a causal world model without prior knowledge of the causal structure of the environment. The model captures the influence of actions, allowing us to interpret

Nardine Osman, Mark d'Inverno

In the diverse array of work investigating the nature of human values from psychology, philosophy and social sciences, there is a clear consensus that values guide behaviour. More recently, a recognition that values provide a means to engineer ethical AI has emerged. Indeed, Stuart Russell proposed shifting AI's focus away from simply ``intelligence'' toward

Nicolò Piccione, Léa Bresque, Andrew N. Jordan, Robert S. Whitney

An effective time-dependent Hamiltonian can be implemented by making a quantum system fly through an inhomogeneous potential, realizing, for example, a quantum gate on its internal degrees of freedom. However, flying systems have a spatial spread that will generically entangle the internal and spatial degrees of freedom, leading to decoherence in the interna

Georgios Konstantopoulos, Yves Louet

In this work, we investigate the optimal beamformer design for the downlink of Multiple-Input Single-Output (MISO) Non-Orthogonal Multiple Access (NOMA), mainly focusing on a two-user scenario. We derive novel closed-form expressions for the Bit Error Rate (BER) experienced by both users when Quadrature Amplitude Modulation (QAM) is employed. Using these exp

Shun-Cheng Wu, Keisuke Tateno, Nassir Navab, Federico Tombari

3D semantic scene graphs are a powerful holistic representation as they describe the individual objects and depict the relation between them. They are compact high-level graphs that enable many tasks requiring scene reasoning. In real-world settings, existing 3D estimation methods produce robust predictions that mostly rely on dense inputs. In this work, we

Kaihao Hu, Kai Wang, Corina Constantinescu, Zhengjun Zhang

Advanced science and technology provide a wealth of big data from different sources for extreme value analysis. Classical extreme value theory was extended to obtain an accelerated max-stable distribution family for modelling competing risk-based extreme data in Cao and Zhang (2021). In this paper, we establish probability models for power normalized maxima

Hirdesh Kumar, Brajesh Kumar, S. P. Rajaguru

Gravity waves are generated by turbulent subsurface convection overshooting or penetrating locally into a stably stratified medium. While propagating energy upwards, their characteristic negative phase shift over height is a well-recognized observational signature. Since their first detailed observational detection and estimates of energy content, a number o

Fabio Nicola

A Gabor orthonormal basis, on a locally compact Abelian (LCA) group $A$, is an orthonormal basis of $L^2(A)$ which consists of time-frequency shifts of some template $f\in L^2(A)$. It is well-known that, on $\mathbb{R}^d$, the elements of such a basis cannot have a good time-frequency localization. The picture is drastically different on LCA groups containin

Wojciech Czerwiński, Eren Keskin, Sławomir Lasota, Roland Meyer

We study the languages recognized by well-structured transition systems (WSTS) with upward and downward compatibility. Our first result shows that every pair of disjoint WSTS languages is regularly separable: there is a regular language containing one of them while being disjoint from the other. As a consequence, if a language as well as its complement are b

Minjia Shi, Xiaoxiao Li, Denis S. Krotov, Ferruh Özbudak

The Galois ring GR$(4^\Delta)$ is the residue ring $Z_4[x]/(h(x))$, where $h(x)$ is a basic primitive polynomial of degree $\Delta$ over $Z_4$. For any odd $\Delta$ larger than $1$, we construct a partition of GR$(4^\Delta) \backslash \{0\}$ into $6$-subsets of type $\{a,b,-a-b,-a,-b,a+b\}$ and $3$-subsets of type $\{c,-c,2c\}$ such that the partition is inv

Wang-Wang Yu, Kai-Fu Yang, Hong-Mei Yan, Yong-Jie Li

Most micro- and macro-expression spotting methods in untrimmed videos suffer from the burden of video-wise collection and frame-wise annotation. Weakly-supervised expression spotting (WES) based on video-level labels can potentially mitigate the complexity of frame-level annotation while achieving fine-grained frame-level spotting. However, we argue that exi

Masaaki Fukasawa, Mikio Hirokane

We study the limit of the joint distribution of a multidimensional Generalized Tempered Stable (GTS) process and its quadratic covariation process when the stable index tends to two. Under a proper scaling, the GTS processes converges to a Brownian motion that is a stable process with stable index two. We renormalize their quadratic covariation processes so

Bryce Clarke

Delta lenses are functors equipped with a suitable choice of lifts, and are used to model bidirectional transformations between systems. In this paper, we construct an algebraic weak factorisation system whose R-algebras are delta lenses. Our approach extends a semi-monad for delta lenses previously introduced by Johnson and Rosebrugh, and generalises to any

Mehran Pourvahab, Seyed Jalaleddin Mousavirad, Virginie Felizardo, Nuno Pombo

Electrocardiogram (ECG) signals, which capture the heart's electrical activity, are used to diagnose and monitor cardiac problems. The accurate classification of ECG signals, particularly for distinguishing among various types of arrhythmias and myocardial infarctions, is crucial for the early detection and treatment of heart-related diseases. This paper pro

Maxwell T. West, Martin Sevior, Muhammad Usman

The recent physical realisation of quantum computers with dozens to hundreds of noisy qubits has given birth to an intense search for useful applications of their unique capabilities. One area that has received particular attention is quantum machine learning (QML), the study of machine learning algorithms running natively on quantum computers. Such algorith

Tomer Bucher, Ron Ruimy, Shai Tsesses, Raphael Dahan

The complex range of interactions between electrons and electromagnetic fields gave rise to countless scientific and technological advances. A prime example is photon-induced nearfield electron microscopy (PINEM), enabling the detection of confined electric fields in illuminated nanostructures with unprecedented spatial resolution. However, PINEM is limited

S L Parnovsky

We investigate possible astronomical manifestations of space-time anisotropy. The homogeneous vacuum Kasner solution was chosen as a reference anisotropic cosmological model because there are no effects caused by inhomogeneity in this simple model with a constant degree of anisotropy. This anisotropy cannot become weak. The study of its geodesic structure ma

Yuan Zhang, Weihua Chen, Yichen Lu, Tao Huang

Knowledge distillation is an effective paradigm for boosting the performance of pocket-size model, especially when multiple teacher models are available, the student would break the upper limit again. However, it is not economical to train diverse teacher models for the disposable distillation. In this paper, we introduce a new concept dubbed Avatars for dis

Imran Khan

To study symmetry and its breaking in particle physics, plays very important role in order to get useful information about the nature. The classification and arrangements of subatomic particles is also necessary to study particle physics. Particles which are building blocks of nature are quarks, gluons and leptons. Baryons and Mesons composed of quarks were

Ching-Kai Lin, Chin-Wen Chen, Yun-Chien Cheng

The purpose of this study is to develop a computer-aided diagnosis system for classifying benign and malignant lung lesions, and to assist physicians in real-time analysis of radial probe endobronchial ultrasound (EBUS) videos. During the biopsy process of lung cancer, physicians use real-time ultrasound images to find suitable lesion locations for sampling.

Daan Delabie, Chesney Buyle, Bert Cox, Liesbet Van der Perre

We present an indoor acoustic simulation framework that supports both ultrasonic and audible signaling. The framework opens the opportunity for fast indoor acoustic data generation and positioning development. The improved Pyroomacoustics-based physical model includes both an image-source model (ISM) and ray tracing method to simulate acoustic signaling in g

Nilson C. Bernardes, Alfredo Peris

In the present work we study the concepts of shadowing and chain recurrence in the setting of linear dynamics. We prove that shadowing and finite shadowing always coincide for operators on Banach spaces, but we exhibit operators on the Fr\'echet space $H(\mathbb{C})$ of entire functions that have the finite shadowing property but do not have the shadowing pr

Guochao Sun, Claude-André Faucher-Giguère, Christopher C. Hayward, Xuejian Shen

Both observations and simulations have shown strong evidence for highly time-variable star formation in low-mass and/or high-redshift galaxies, which has important observational implications because high-redshift galaxy samples are rest-UV selected and therefore particularly sensitive to the recent star formation. Using a suite of cosmological "zoom-in" simu

Manuel Asorey, Fernando Ezquerro

The dynamics of classical field theories is usually governed by field equations, but when fields are constrained to bounded domains it is also dependent on its boundary conditions. Usually boundary conditions are constrained by the requirement of preserving the maximal symmetry of the system. In the case of charged particles the symmetry is U(1), but there a

Annina Z. Lieberherr, Seth T. E. Furniss, Joseph E. Lawrence, David E. Manolopoulos

We assess the cavity molecular dynamics method for the calculation of vibrational polariton spectra, using liquid water as a specific example. We begin by disputing a recent suggestion that nuclear quantum effects may lead to a broadening of polariton bands, finding instead that they merely result in anharmonic red shifts in the polariton frequencies. We go

Simon Göppel, Markus Haltmeier, Jürgen Frikel

In this article, we address the challenge of solving the ill-posed reconstruction problem in computed tomography using a translation invariant diagonal frame decomposition (TI-DFD). First, we review the concept of a TI-DFD for general linear operators and the corresponding filter-based regularization. We then introduce the TI-DFD for the Radon transform on $

Enrico Bandiello, Samuel Gallego-Parra, Akun Liang, Juan Ángel Sans

GaGeTe is a layered topological semimetal that has been recently found to exist in at least two different polytypes, $\alpha$-GaGeTe ($R\bar{3}m$) and $\beta$-GaGeTe ($P6_3 mc$). Here we report a joint experimental and theoretical study of the structural, vibrational, and electronic properties of these two polytypes at high pressure. Both polytypes show anis

Yun-Feng Lo, Yen-Chi Lee, Min-Hsiu Hsieh

In this paper, we delve into the capacity problem of additive vertically-drifted first arrival position noise channel, which models a communication system where the position of molecules is harnessed to convey information. Drawing inspiration from the principles governing vector Gaussian interference channels, we examine this capacity problem within the cont

Yannan Chen, Licheng Zhao, Kaiming Shen

Fractional programming (FP) plays a crucial role in wireless network design because many relevant problems involve maximizing or minimizing ratio terms. Notice that the maximization case and the minimization case of FP cannot be converted to each other in general, so they have to be dealt with separately in most of the previous studies. Thus, an existing FP

Sultan Hassan, Christopher C. Lovell, Piero Madau, Marc Huertas-Company

An unprecedented array of new observational capabilities are starting to yield key constraints on models of the epoch of first light in the Universe. In this Letter we discuss the implications of the UV radiation background at cosmic dawn inferred by recent JWST observations for radio experiments aimed at detecting the redshifted 21-cm hyperfine transition o

Nicolas Peretto, Andrew J. Rigby, Fabien Louvet, Gary A. Fuller

The formation of stellar clusters dictates the pace at which galaxies evolve, and solving the question of their formation will undoubtedly lead to a better understanding of the Universe as a whole. While it is well known that star clusters form within parsec-scale over-densities of interstellar molecular gas called clumps, it is, however, unclear whether the

Shengkai Lin, Shizhen Zhao, Peirui Cao, Xinchi Han

Recent years have witnessed a widespread adoption of containers. While containers simplify and accelerate application development, existing container network technologies either incur significant overhead, which hurts performance for distributed applications, or lose flexibility or compatibility, which hinders the widespread deployment in production. We care

Xingwei Liang, You Zou, Ruifeng Xu

Emotion Recognition in Conversation~(ERC) across modalities is of vital importance for a variety of applications, including intelligent healthcare, artificial intelligence for conversation, and opinion mining over chat history. The crux of ERC is to model both cross-modality and cross-time interactions throughout the conversation. Previous methods have made

Xinyang Huang, Chuang Zhu, Wenkai Chen

In semi-supervised domain adaptation (SSDA), a few labeled target samples of each class help the model to transfer knowledge representation from the fully labeled source domain to the target domain. Many existing methods ignore the benefits of making full use of the labeled target samples from multi-level. To make better use of this additional data, we propo

Eric W Lee, Joyce C Ho

There has been rapid growth in biomedical literature, yet capturing the heterogeneity of the bibliographic information of these articles remains relatively understudied. Although graph mining research via heterogeneous graph neural networks has taken center stage, it remains unclear whether these approaches capture the heterogeneity of the PubMed database, a

Thomas F. Bloom

We prove that any positive rational number is the sum of distinct unit fractions with denominators in $\{p-1 : p\textrm{ prime}\}$. The same conclusion holds for the set $\{p-h : p\textrm{ prime}\}$ for any $h\in\mathbb{Z}\backslash\{0\}$, provided a necessary congruence condition is satisfied. We also prove that this is true for any subset of the primes of

Erlend Grong, Hans Z. Munthe-Kaas, Jonatan Stava

For a general affine connection with parallel torsion and curvature, we show that a post-Lie algebra structure exists on its space of vector fields, generalizing previous results for flat connections. However, for non-flat connections, the vector fields alone are not enough, as the presence of curvature also necessitates that we include endomorphisms corresp

Horia-Nicolai L. Teodorescu

It turns out that some empirical facts in Big Data are the effects of properties of large numbers. Zipf's law 'noise' is an example of such an artefact. We expose several properties of the power law distributions and of similar distribution that occur when the population is finite and the rank and counts of elements in the population are natural

Michał Ciszewski, Jakob Söhl, Ton Leenen, Bart van Trigt

Often the question arises whether $Y$ can be predicted based on $X$ using a certain model. Especially for highly flexible models such as neural networks one may ask whether a seemingly good prediction is actually better than fitting pure noise or whether it has to be attributed to the flexibility of the model. This paper proposes a rigorous permutation test

Hamze Bagherinejad, Ali Iloon Kashkooly, Rohollah Parvinianzadeh

Let $B(H)$ be the algebra of all bounded linear operators on infinite-dimensional complex Hilbert space $H$. For $T, S \in B(H)$ denote by $T\bullet S=TS+ST^{\ast}$ and $[T\circ S]_{\ast}=TS-ST^{\ast}$ the Jordan $\ast$-product and the skew Lie product of $T$ and $S$, respectively. Fix $\varepsilon > 0$ and $T \in B(H)$, let $σ_{\varepsilon}(T)$ denote the $

Joaquín J. Torres, Daniel Manzano

We present extensive simulations of a quantum version of the Hopfield Neural Network to explore its emergent behavior. The system is a network of $N$ qubits oscillating at a given $\Omega$ frequency and which are coupled via Lindblad jump operators built with local fields $h_i$ depending on some given stored patterns. Our simulations show the emergence of pa

Dongyan Fu, Bao-Dong Sun, Yubing Dong

The generalized parton distributions (GPDs) for the spin-3/2 $\Delta^+$ resonance are studied numerically by using a diquark spectator approach. Our results show that symmetric constraints from time reversal on GPDs are satisfied. The axial vector form factors of the system are also provided and compared with the lattice QCD calculation. Furthermore, the str

Alon Jacovi, Hendrik Schuff, Heike Adel, Ngoc Thang Vu

Word-level saliency explanations ("heat maps over words") are often used to communicate feature-attribution in text-based models. Recent studies found that superficial factors such as word length can distort human interpretation of the communicated saliency scores. We conduct a user study to investigate how the marking of a word's neighboring wor

Tizian Zeltner, Fabrice Rousselle, Andrea Weidlich, Petrik Clarberg

We present a complete system for real-time rendering of scenes with complex appearance previously reserved for offline use. This is achieved with a combination of algorithmic and system level innovations. Our appearance model utilizes learned hierarchical textures that are interpreted using neural decoders, which produce reflectance values and importance-sam

Teng Wang, Jinrui Zhang, Junjie Fei, Hao Zheng

Controllable image captioning is an emerging multimodal topic that aims to describe the image with natural language following human purpose, $\textit{e.g.}$, looking at the specified regions or telling in a particular text style. State-of-the-art methods are trained on annotated pairs of input controls and output captions. However, the scarcity of such well-

Youquan Fu, Michele Cappellari, Shude Mao, Shengdong Lu

We analyse the integral-field spectroscopy data for the $\approx10,000$ galaxies in final data release of the MaNGA survey. We identify 188 galaxies for which the emission lines cannot be described by single Gaussian components. These galaxies can be classified into (1) 38 galaxies with broad $H\alpha$ and [OIII] $\lambda$5007 lines, (2) 101 galaxies with br

Dylan Braithwaite, Mario Román

We introduce collages of string diagrams as a diagrammatic syntax for glueing multiple monoidal categories. Collages of string diagrams are interpreted as pointed bimodular profunctors. As the main examples of this technique, we introduce string diagrams for bimodular categories, string diagrams for functor boxes, and string diagrams for internal diagrams.

Ramanathan Rajendiran, Debaditya Roy, Basura Fernando

Humans have the natural ability to recognize actions even if the objects involved in the action or the background are changed. Humans can abstract away the action from the appearance of the objects which is referred to as compositionality of actions. We focus on this compositional aspect of action recognition to impart human-like generalization abilities to

J. -M. Rax, R. Gueroult, N. J. Fisch

Both spin and orbital angular momentum can be exchanged between a rotating wave and a rotating magnetized plasma. Through resonances the spin and orbital angular momentum of the wave can be coupled to both the cyclotron rotation and the drift rotation of the particles. It is however shown that the Landau and cyclotron resonance conditions which classically d

Simone Cepollaro, Goffredo Chirco, Gianluca Cuffaro, Vittorio D'Esposito

We investigate the multipartite entanglement of a uniformly curved quantum 3D space region with boundary, realised in terms of spin networks defined on a graph with non trivial SU(2) holonomies, in the framework of loop quantum gravity. The presence of intrinsic curvature in the region is encoded in closure (topological) defects associated with tag-spins att

Krishna Pal Thakur, Basabdatta Palit

In this work, we have proposed link adaptation-based joint spectrum and power allocation algorithms for the uplink communication in 5G Cellular Vehicle-to-Everything (C-V2X) systems. In C-V2X, vehicle-to-vehicle (V2V) users share radio resources with vehicle-to-infrastructure (V2I) users. Existing works primarily focus on the optimal pairing of V2V and V2I u

Bence Fitos, Gábor Takács

The recently proposed classification of integrability-breaking perturbations according to their strength is studied in the context of quantum field theories. Using random matrix methods to diagnose the resulting quantum chaotic behaviour, we investigate the $\phi^4$ and $\phi^6$ interactions of a massive scalar, by considering the crossover between Poissonia

Maryam Soleymaninia, Hadi Hashamipour, Hamzeh Khanpour, Samira Shoeib

In this work, we present a new global QCD analyses, referred to as PKHFF.23, for charged pion, kaon, and unidentified light hadrons. We utilize a Neural Network to fit the high-energy lepton-lepton and lepton-hadron scattering data, enabling us to determine parton-to-hadron fragmentation functions (FFs) at next-to-leading-order (NLO) accuracy. The analyses i

Matthias Plock, Martin Hammerschmidt, Sven Burger, Philipp-Immanuel Schneider

In optical nano metrology numerical models are used widely for parameter reconstructions. Using the Bayesian target vector optimization method we fit a finite element numerical model to a Grazing Incidence X-Ray fluorescence data set in order to obtain the geometrical parameters of a nano structured line grating. Gaussian process, stochastic machine learning

Régis de la Bretèche, Vivian Kuperberg

We consider an analog of a conjecture of Montgomery and Soundararajan on the moments of primes in short intervals in number fields; this analog was discussed and heuristically derived in a paper of the second author, Rodgers, and Roditty-Gershon. Adapting work of the first author and Fiorilli in the integer case, we establish lower bounds on a weighted versi

Sebastian Zielinski, Jonas Nüßlein, Jonas Stein, Thomas Gabor

3SAT instances need to be transformed into instances of Quadratic Unconstrained Binary Optimization (QUBO) to be solved on a quantum annealer. Although it has been shown that the choice of the 3SAT-to-QUBO transformation can impact the solution quality of quantum annealing significantly, currently only a few 3SAT-to-QUBO transformations are known. Additional

Yicheng Li, Zixiong Yu, Guhan Chen, Qian Lin

In this paper, we provide a strategy to determine the eigenvalue decay rate (EDR) of a large class of kernel functions defined on a general domain rather than $\mathbb S^{d}$. This class of kernel functions include but are not limited to the neural tangent kernel associated with neural networks with different depths and various activation functions. After pr

Shogo Kusano, Masayuki Uchida

We consider structural equation modeling (SEM) with latent variables for diffusion processes based on high-frequency data. The quasi-likelihood estimators for parameters in the SEM are proposed. The goodness-of-fit test is derived from the quasi-likelihood ratio. We also treat sparse estimation in the SEM. The goodness-of-fit test for the sparse estimation i

Yanyan Zheng, Nikolaos Kouvatsos, Jacob Golomb, Marco Cavaglià

We present a new, simulation-based inference method to compute the angular power spectrum of the distribution of foreground gravitational-wave transient events. As a first application of this method, we use the binary black hole mergers observed during the LIGO, Virgo, and KAGRA third observation run to test the spatial distribution of these sources. We find

Lingyi Chen, Shitong Wu, Wenhao Ye, Huihui Wu

The Blahut-Arimoto (BA) algorithm has played a fundamental role in the numerical computation of rate-distortion (RD) functions. This algorithm possesses a desirable monotonic convergence property by alternatively minimizing its Lagrangian with a fixed multiplier. In this paper, we propose a novel modification of the BA algorithm, wherein the multiplier is up

Keegan Dasilva Barbosa, Dragan Mašulović, Rajko Nenadov

In this short note we confirm the deep structural correspondence between the complexity of a countable scattered chain (= strict linear order) and its big Ramsey combinatorics: we show that a countable scattered chain has finite big Ramsey degrees if and only if it is of finite Hausdorff rank. This also provides a complete characterization of countable chain

Son T. Duong, Ha H. Nguyen, Ebrahim Bedeer, Robert Barton

This paper proposes a novel design of multi-symbol unitary constellation for non-coherent single-input multiple-output (SIMO) communications over block Rayleigh fading channels. To facilitate the design and the detection of large unitary constellations at reduced complexity, the proposed constellations are constructed as the Cartesian product of independent

Steffen Czolbe, Adrian V. Dalca

Neuroimage processing tasks like segmentation, reconstruction, and registration are central to the study of neuroscience. Robust deep learning strategies and architectures used to solve these tasks are often similar. Yet, when presented with a new task or a dataset with different visual characteristics, practitioners most often need to train a new model, or

Kilian Schäfer, Matthias Lutzi, Muhammad Bilal Khan, Lukas Schäfer

Additive manufacturing technologies enable the production of complex and bioinspired shapes using magneto-responsive materials, which find diverse applications in soft robotics. Particularly, the development of composites with controlled gradients in mechanical properties offers new prospects for advancements in magneto-active materials. However, achieving s

Yunlong Liu, Xiangdong Zhang

We investigate the quasinormal mode and greybody factor of Bardeen black holes with a string clouds by WKB approximation and verify them by Prony algorithm. We found that the imaginary part of the quasinormal modes spectra is always negative and the perturbation does not increase with the time, indicating that the system is stable under scalar field perturba

Marek Mezera, Camilo Florian, Gert-willem Römer, Jörg Krüger

Surface nanostructures provide the possibility to create and tailor surface functionalities mainly via controlling their topography along with other chemical and physical material properties. One of the most appealing technologies for surface functionalization via micro- and nanostructuring is based on laser processing. This can be done either via direct con

Hang Chen, Xinyu Yang, Qing Yang

Owing to the cross-pollination between causal discovery and deep learning, non-statistical data (e.g., images, text, etc.) encounters significant conflicts in terms of properties and methods with traditional causal data. To unify these data types of varying forms, we redefine causal data from two novel perspectives and then propose three data paradigms. Amon

Camilo Florian, Xiaohan Du, Craig B. Arnold

Pushing the limits of precision and reproducibility in ultrafast laser-based nanostructuring requires detailed control over the properties of the illumination. Most traditional methods of laser-based manufacturing rely on the simplicity of Gaussian beams for their well-understood propagation behavior and ease of generation. However, a variety of benefits can

Yiping Jin, Leo Wanner, Vishakha Laxman Kadam, Alexander Shvets

As pointed out by several scholars, current research on hate speech (HS) recognition is characterized by unsystematic data creation strategies and diverging annotation schemata. Subsequently, supervised-learning models tend to generalize poorly to datasets they were not trained on, and the performance of the models trained on datasets labeled using different

L. Y. Wu, K. Y. Zhang, H. Yan

The potential discovery of unparticles could have far-reaching implications for particle physics and cosmology. For over a decade, high-energy physicists have extensively studied the effects of unparticles. In this study, we derive six types of nonrelativistic potentials between fermions induced by unparticle exchange in coordinate space. We consider all pos

Jianwei Huang, Ziqin Yue, Andrey Baydin, Hanyu Zhu

Angle-resolved photoemission spectroscopy (ARPES) is a powerful tool for probing the momentum-resolved single-particle spectral function of materials. Historically, $\textit{in situ}$ magnetic fields have been carefully avoided as they are detrimental to the control of photoelectron trajectory during the photoelectron detection process. However, magnetic fie

Gianmarco Giovannardi, Dimitri Mugnai, Eugenio Vecchi

We prove the existence and multiplicity of weak solutions for a mixed local-nonlocal problem at resonance. In particular, we consider a not necessarily positive operator which appears in models describing the propagation of flames. A careful adaptation of well known variational methods is required to deal with the possible existence of negative eigenvalues.

C. H. Kim, K. Y. Chae, M. S. Smith, D. W. Bardayan

Physics models typically contain adjustable parameters to reproduce measured data. While some parameters correspond directly to measured features in the data, others are unobservable. These unobservables can, in some cases, cause ambiguities in the extraction of observables from measured data, or lead to questions on the physical interpretation of fits that

Jona Ruof, Max Bastian Mertens, Michael Buchholz, Klaus Dietmayer

Planning trajectories for automated vehicles in urban environments requires methods with high generality, long planning horizons, and fast update rates. Using a path-velocity decomposition, we contribute a novel planning framework, which generates foresighted trajectories and can handle a wide variety of state and control constraints effectively. In contrast

Kimitake Hayasaki, Ryo Yamazaki

We study the evolution of a non-relativistically expanding thin shell in radio-emitting tidal disruption events (TDEs) based on a one-dimensional spherically symmetric model considering the effect of both a time-dependent mass loss rate of the disk wind and the ambient mass distribution. The analytical solutions are derived in two extreme limits: one is the

Harsha A. Tanti, Abhirup Datta, S. Ananthakrishnan

The estimation of the direction of electromagnetic (EM) waves from a radio source using electrically short antennas is one of the challenging problems in the field of radio astronomy. In this paper we have developed an algorithm which performs better in direction and polarization estimations than the existing algorithms. Our proposed algorithm Snapshot Avera

Hang Chen, Jing Luo, Xinyu Yang, Wenjing Zhu

Our investigation into the Affective Reasoning in Conversation (ARC) task highlights the challenge of causal discrimination. Almost all existing models, including large language models (LLMs), excel at capturing semantic correlations within utterance embeddings but fall short in determining the specific causal relationships. To overcome this limitation, we p

Yuxuan Yin, Yu Wang, Peng Li

We introduce a novel semi-supervised learning approach, named Teacher-Student Bayesian Optimization ($\texttt{TSBO}$), integrating the teacher-student paradigm into BO to minimize expensive labeled data queries for the first time. $\texttt{TSBO}$ incorporates a teacher model, an unlabeled data sampler, and a student model. The student is trained on unlabeled

Fausto Barbero, Gabriel Sandu

In [4], we introduced an extension of team semantics (causal teams) which assigns an interpretation to interventionist counterfactuals and causal notions based on them (as e.g. in Pearl's and Woodward's manipulationist approaches to causation). We now present a further extension of this framework (causal multiteams) which allows us to talk about prob

Hiroshi Ando, Andreas Thom

Let $G$ be a Polish group and let $H \leq G$ be a compact subgroup. We prove that there exists a Borel set $T \subset G$ which is simultaneously a complete set of coset representatives of left and right cosets, provided that a certain index condition is satisfied. Moreover, we prove that this index condition holds provided that $G$ is locally compact and $G/

Song Dai, Tianqi Wu

We proved a rigidity result for Delaunay triangulations of the plane under Luo's discrete conformal change, extending previous results on hexagonal triangulations. Our result is a discrete analogue of the conformal rigidity of the plane. We followed Zhengxu He's analytical approach in his work on the rigidity of disk patterns, and developed a discrete Schwar

Daniil Homskiy, Narek Maloyan

In recent years, sentiment analysis has gained significant importance in natural language processing. However, most existing models and datasets for sentiment analysis are developed for high-resource languages, such as English and Chinese, leaving low-resource languages, particularly African languages, largely unexplored. The AfriSenti-SemEval 2023 Shared Ta

Jiaxin Wen, Hao Zhou, Jian Guan, Minlie Huang

Pre-training on large-scale open-domain dialogue data can substantially improve the performance of dialogue models. However, the pre-trained dialogue model's ability to utilize long-range context is limited due to the scarcity of long-turn dialogue sessions. Most dialogues in existing pre-training corpora contain fewer than three turns of dialogue. To allevi

Xiang Zheng, Xingjun Ma, Shengjie Wang, Xinyu Wang

Reinforcement learning agents are susceptible to evasion attacks during deployment. In single-agent environments, these attacks can occur through imperceptible perturbations injected into the inputs of the victim policy network. In multi-agent environments, an attacker can manipulate an adversarial opponent to influence the victim policy's observations indir

I. Bailleul, N. Moench

We study some systems of interacting fields whose evolution is given by some singular stochastic partial differential equations of mean field type. We provide a robust setting for their study and prove a well-posedness result and a propagation of chaos result.

Ruijie Meng, George Pîrlea, Abhik Roychoudhury, Ilya Sergey

Grey-box fuzzing is the lightweight approach of choice for finding bugs in sequential programs. It provides a balance between efficiency and effectiveness by conducting a biased random search over the domain of program inputs using a feedback function from observed test executions. For distributed system testing, however, the state-of-practice is represented

Chao Xu, Shaoting Zhu, Junwei Zhu, Tianxin Huang

Multimodal-driven talking face generation refers to animating a portrait with the given pose, expression, and gaze transferred from the driving image and video, or estimated from the text and audio. However, existing methods ignore the potential of text modal, and their generators mainly follow the source-oriented feature rearrange paradigm coupled with unst

Ke, Ma, Sophie Yanying Sheng, Haitian Xie

How does employer reputation affect the labor market? We investigate this question using a novel dataset combining reviews from Glassdoor.com and job applications data from Dice.com. Labor market institutions such as Glassdoor.com crowd-sources information about employers to alleviate information problems faced by workers when choosing an employer. Raw crowd

Ruoyu Feng, Yixin Gao, Xin Jin, Runsen Feng

Image compression techniques typically focus on compressing rectangular images for human consumption, however, resulting in transmitting redundant content for downstream applications. To overcome this limitation, some previous works propose to semantically structure the bitstream, which can meet specific application requirements by selective transmission and

Hao Zhang, Meng Yu, Yuzhong Wu, Tao Yu

Deep learning has been recently introduced for efficient acoustic howling suppression (AHS). However, the recurrent nature of howling creates a mismatch between offline training and streaming inference, limiting the quality of enhanced speech. To address this limitation, we propose a hybrid method that combines a Kalman filter with a self-attentive recurrent

Shaked Brody, Uri Alon, Eran Yahav

Layer Normalization (LayerNorm) is an inherent component in all Transformer-based models. In this paper, we show that LayerNorm is crucial to the expressivity of the multi-head attention layer that follows it. This is in contrast to the common belief that LayerNorm's only role is to normalize the activations during the forward pass, and their gradients d

Aurélien Djament, Thomas Gaujal

We study generic representations of general linear groups over a finite ring R with coefficients in a field k in which the cardinality of R is invertible, that is functors from finitely-generated projective R-modules to k-vector spaces. We obtain especially a classification of such simple representations, what allows to prove a conjecture of Djament-Touz{\'e

Jules Hoepner, Gary MacGillivray, Kieka Mynhardt

A broadcast on a connected graph G with vertex set V(G) is a function $f:V(G)\rightarrow \{0, 1, ..., \text{diam}(G)\}$ such that $f(v)\leq e(v)$ (the eccentricity of $v$) for all $v\in V$. A vertex $v$ is said to be broadcasting if $f(v)>0$, with the set of all such vertices denoted $V_f^+$. A vertex $u$ hears $f$ from $v\in V_f^+$ if $d_G(u, v)\leq f(v)$.

Ravi Tejwani, Chengyuan Ma, Paco Gomez-Paz, Paolo Bonato

Recent advancements have enabled human-robot collaboration through physical assistance and verbal guidance. However, limitations persist in coordinating robots' physical motions and speech in response to real-time changes in human behavior during collaborative contact tasks. We first derive principles from analyzing physical therapists' movements and speech

Sen Zhao, Wei Wei, Yifan Liu, Ziyang Wang

Conversational recommendation systems (CRS) aim to timely and proactively acquire user dynamic preferred attributes through conversations for item recommendation. In each turn of CRS, there naturally have two decision-making processes with different roles that influence each other: 1) director, which is to select the follow-up option (i.e., ask or recommend)

David Jekel, Jennifer Pi

Through the study of large deviations theory for matrix Brownian motion, Biane-Capitaine-Guionnet proved the inequality $\chi(X) \leq \chi^*(X)$ that relates two analogs of entropy in free probability defined by Voiculescu. We give a new proof of $\chi \leq \chi^*$ that is elementary in the sense that it does not rely on stochastic differential equations and

Chao Xu, Junwei Zhu, Jiangning Zhang, Yue Han

Recently, emotional talking face generation has received considerable attention. However, existing methods only adopt one-hot coding, image, or audio as emotion conditions, thus lacking flexible control in practical applications and failing to handle unseen emotion styles due to limited semantics. They either ignore the one-shot setting or the quality of gen

Owen Lynch, Brandon T. Shapiro, David I. Spivak

We show that the double category $\mathbb{C}\mathbf{at}^\#$ of comonoids in the category of polynomial functors (previously shown by Ahman-Uustalu and Garner to be equivalent to the double category of categories, cofunctors, and prafunctors) contains several formal settings for basic category theory and has subcategories equivalent to both the double categor

Sriram Bhyravarapu, Shiwali Gupta, Subrahmanyam Kalyanasundaram, Rogers Mathew

A conflict-free open neighborhood coloring of a graph is an assignment of colors to the vertices such that for every vertex there is a color that appears exactly once in its open neighborhood. For a graph $G$, the smallest number of colors required for such a coloring is called the conflict-free open neighborhood (CFON) chromatic number and is denoted by $\c