February 2024 arXiv papers — page 140

Zhiyuan Ma, Xiangyu Zhu, Guojun Qi, Chen Qian

Speech-driven 3D facial animation is important for many multimedia applications. Recent work has shown promise in using either Diffusion models or Transformer architectures for this task. However, their mere aggregation does not lead to improved performance. We suspect this is due to a shortage of paired audio-4D data, which is crucial for the Transformer to

Muslim Chochlov, Michael English, Jim Buckley

Feature location attempts to assist developers in discovering functionality in source code. Many textual feature location techniques utilize information retrieval and rely on comments and identifiers of source code to describe software entities. An interesting alternative would be to employ the changeset descriptions of the code altered in that changeset as

Hassan Cheraghpour, Bojan Kuzma

We classify all the irreducible characters of a symmetric group such that the induced immanant function $d_{\chi}$ vanishes identically on alternate matrices with the entries in the complex field.

Yiluo Wei, Gareth Tyson

Nostr is a decentralized social network launched in 2022, emphasizing high availability and censorship resistance. Since launching, it has gained substantial attention, boasting over 100 million posts. Nostr resembles a micro-blogging service like Twitter but with distinct underlying infrastructure. Nostr introduces the concept of relays, which act as open s

Heather Battey, Nancy Reid

The paper is concerned with inference for a parameter of interest in models that share a common interpretation for that parameter but that may differ appreciably in other respects. We study the general structure of models under which the maximum likelihood estimator of the parameter of interest is consistent under arbitrary misspecification of the nuisance p

Mihály Kovács, Mihály András Vághy

In this paper we develop a Neumann-Neumann type domain decomposition method for elliptic problems on metric graphs. We describe the iteration in the continuous and discrete setting and rewrite the latter as a preconditioner for the Schur complement system. Then we formulate the discrete iteration as an abstract additive Schwarz iteration and prove that it co

Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, Ohsung Kwon

Recent work shows promising results in expanding the capabilities of large language models (LLM) to directly understand and synthesize speech. However, an LLM-based strategy for modeling spoken dialogs remains elusive, calling for further investigation. This paper introduces an extensive speech-text LLM framework, the Unified Spoken Dialog Model (USDM), desi

Sebastien Colla, Julien M. Hendrickx

We establish that in distributed optimization, the prevalent strategy of minimizing the second-largest eigenvalue modulus (SLEM) of the averaging matrix for selecting communication weights, while optimal for existing theoretical performance bounds, is generally not optimal regarding the exact worst-case performance of the algorithms. This exact performance c

Ioseph Buchbinder, Evgeny Ivanov, Nikita Zaigraev

A brief review of the harmonic superspace approach to the construction of $\mathcal{N}=2$ supersymmetric higher spin theories is given. We define off-shell analytic harmonic gauge potentials of $\mathcal{N}=2$ supersymmetric higher-spin multiplets and of $\mathcal{N}=2$ superconformal higher-spin multiplets for an arbitrary integer highest spin. The componen

Giorgio Angelotti, Caroline P. C. Chanel, Adam H. M. Pinto, Christophe Lounis

The integration of physiological computing into mixed-initiative human-robot interaction systems offers valuable advantages in autonomous task allocation by incorporating real-time features as human state observations into the decision-making system. This approach may alleviate the cognitive load on human operators by intelligently allocating mission tasks b

Arne Lien, Robin Schabert

We study a natural stratification of certain affine slices of univariate hyperbolic polynomials. We look into which posets of strata can be realized and show that the dual of the poset of strata is a shellable simplicial complex and in particular a combinatorial sphere. From this we obtain a g-theorem and an upper bound theorem on the number of strata. We us

V. H. Dao, R. Frésard

The functional integral formulation of the Hubbard model when treated in its Kotliar-Ruckenstein representation in the radial gauge involves fermionic, as well as complex and radial slave boson fields. In order to improve on the understanding of the interplay of the three types of fields, and on the nature of the latter, we perform a comprehensive investigat

Marta Fernandez, Hugo G. Espinosa, David Guerra, Ivan Pena

Human exposure to electromagnetic fields produced by two wearable antennas operating in the 2.4 GHz frequency band was assessed by computational tools. Both antennas were designed to be attached to the skin, but they were intended for different applications. The first antenna was designed for off-body applications, i.e. to communicate with a device placed ou

Dhruvi Shah, Shruti Mehta, Ashish Agrawal, Shishir Purohit

Ring artifacts in X-ray micro-CT images are one of the primary causes of concern in their accurate visual interpretation and quantitative analysis. The geometry of X-ray micro-CT scanners is similar to the medical CT machines, except the sample is rotated with a stationary source and detector. The ring artifacts are caused by a defect or non-linear responses

Xianghe Pang, Shuo Tang, Rui Ye, Yuxin Xiong

Aligning large language models (LLMs) with human values is imperative to mitigate potential adverse effects resulting from their misuse. Drawing from the sociological insight that acknowledging all parties' concerns is a key factor in shaping human values, this paper proposes a novel direction to align LLMs by themselves: social scene simulation. To achieve

Malik Muhammad Qirtas, Evi Zafeiridi, Eleanor Bantry White, Dirk Pesch

Loneliness is a growing health concern as it can lead to depression and other associated mental health problems for people who experience feelings of loneliness over prolonged periods of time. Utilizing passive sensing methods that use smartphone and wearable sensor data to capture daily behavioural patterns offers a promising approach for the early detectio

V. A. Yurko

Non-self-adjoint second-order ordinary differential operators on a finite interval with complex weights are studied. Properties of spectral characteristics are established and the inverse problem of recovering operators from their spectral characteristics are investigated. For this class of nonlinear inverse problems an algorithm for constructing the global

Mihailo Stojnic

We consider the capacity of \emph{treelike committee machines} (TCM) neural networks. Relying on Random Duality Theory (RDT), \cite{Stojnictcmspnncaprdt23} recently introduced a generic framework for their capacity analysis. An upgrade based on the so-called \emph{partially lifted} RDT (pl RDT) was then presented in \cite{Stojnictcmspnncapliftedrdt23}. Both

R. D. Prokaj, P. Raith

We consider iterated function systems on the real line that consist of continuous, piecewise linear functions. We show that typically the natural dimension of these systems changes continuously with respect to the parameters that define the system. As an application of this property, we prove a result on the positivity of the Lebesgue measure of the attracto

Muskan Arora, Pranav Chokkara, Jasleen Lugani

Photonic integrated optical components, notably straight waveguides, serve as pivotal elements for on-chip generation and manipulation of quantum states of light. In this work, we focus on optimizing waveguides based on lithium niobate on insulator (LNOI) to generate photon pairs at telecom wavelength using spontaneous parametric down-conversion (SPDC). Spec

Shuo Li, Yi Cui, Zhenyuan Zeng, Yue Wang

We performed nuclear magnetic resonance studies on a kagome antiferromagnet YCu$_3$(OH)$_6$Br$_2$[Br$_{1-x}$(OH)$_{x}$]. No significant NMR spectral broadening is found in the Br center peak from 1 K down to 0.05 K, indicating absence of static antiferromagnetic ordering. In contrast to signatures of dominant 2D kagome antiferromagnetic fluctuations at tempe

Nigel B. Wilding, Robert Evans, Francesco Turci

Measurements of local density fluctuations are crucial to characterizing the interfacial properties of equilibrium fluids. A specific case that has been well-explored involves the heightened compressibility of water near hydrophobic entities. Commonly, a spatial profile of local fluctuation strength is constructed from measurements of the mean and variance o

Daniil Vankov, Angelia Nedich, Lalitha Sankar

Variational Inequality (VI) problems have attracted great interest in the machine learning (ML) community due to their application in adversarial and multi-agent training. Despite its relevance in ML, the oft-used strong-monotonicity and Lipschitz continuity assumptions on VI problems are restrictive and do not hold in practice. To address this, we relax smo

Philipp Sohr, Sebastian Ecker, Lukas Bulla, Martin Bohmann

High-quality, distributed quantum entanglement is the distinctive resource for quantum communication and forms the foundation for the unequalled level of security that can be assured in quantum key distribution. While the entanglement provider does not need to be trusted, the secure key rate drops to zero if the entanglement used is too noisy. In this paper,

Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang

We consider the infinite-horizon, average-reward restless bandit problem in discrete time. We propose a new class of policies that are designed to drive a progressively larger subset of arms toward the optimal distribution. We show that our policies are asymptotically optimal with an $O(1/\sqrt{N})$ optimality gap for an $N$-armed problem, assuming only a un

Lukas Lanza

A feedback controller is proposed to perform output reference tracking with prescribed performance for nonlinear continuous-time systems of relative degree two. The controller is of sampled-data type, i.e., measurements are available only at sampling times - a typical situation in real systems when sensors are involved. Furthermore, only output information i

Gabriel Martins de Jesus, Onel Luis Alcaraz Lopez, Richard Demo Souza, Nurul Huda Mahmood

Wireless communication systems must increasingly support a multitude of machine-type communications (MTC) devices, thus calling for advanced strategies for active user detection (AUD). Recent literature has delved into AUD techniques based on compressed sensing, highlighting the critical role of signal sparsity. This study investigates the relationship betwe

Zhuo Chen, Natalia Ivanova

Luminous red novae (LRNe) and their connection to common envelope evolution (CEE) remain elusive in astrophysics. Here, we present a radiation hydrodynamic model capable of simulating the light curves of material ejected during a CEE. For the first time, the radiation hydrodynamic model incorporates complete recombination physics for hydrogen and helium. The

Lin-Jie Chen, Shun-Cai Zhao, Ya-Fang Tian

For efficient photovoltaic conversion, it is important to understand how quantum entropy-related quantities evolve during the photovoltaic process. In this study, using a double quantum dot (DQD) photocell model, we explored the dynamic quantum entropy-related parameters during the photovoltaic output. The findings demonstrate that the dynamic photovoltaic p

Patrick Wienholt, Alexander Hermans, Firas Khader, Behrus Puladi

This study investigates the application of ordinal regression methods for categorizing disease severity in chest radiographs. We propose a framework that divides the ordinal regression problem into three parts: a model, a target function, and a classification function. Different encoding methods, including one-hot, Gaussian, progress-bar, and our soft-progre

V. Garcia-Marina, I. Fernandez de Bustos, G. Urkullu, R. Ansola

The deformed energy method has shown to be a good option for dimensional synthesis of mechanisms. In this paper the introduction of some new features to such approach is proposed. First, constraints fixing dimensions of certain links are introduced in the error function of the synthesis problem. Second, requirements on distances between determinate nodes are

R. L. P. G. Amaral, V. E. R. Lemes, O. S. Ventura, L. C. Q. Vilar

We show that gauge fields after a spontaneous symmetry breaking (SSB) mechanism do not have a Gribov problem along the broken directions. In order to make this proof, we describe a gauge fixing procedure inspired on Morse theory leading to the concept of a gauge fixing generating functional. This approach is specially suited in order to understand the unitar

Xinxing Tang, Shing-Tung Yau

In \cite{TY}, we investigate the pair $(P, \Supp(P))$ of minimal path $P$ and its supporting sub-digraph $\Supp(P)$ in the path complex of a digraph $G$ under the strongly regular condition. In this paper, first, we consider the special minimal path $P$ specified by the admissible condition (Definition \ref{admpair}), which means that $(P,\Supp(P))$ admits a

Christian Ortlieb, Jens M. Schmidt

Given a spanning tree $T$ of a planar graph $G$, the co-tree of $T$ is the spanning tree of the dual graph $G^*$ with edge set $(E(G)-E(T))^*$. Gr\"unbaum conjectured in 1970 that every planar 3-connected graph $G$ contains a spanning tree $T$ such that both $T$ and its co-tree have maximum degree at most 3. While Gr\"unbaum's conjecture remains open, Biedl

Reijo Jaakkola, Tomi Janhunen, Antti Kuusisto, Masood Feyzbakhsh Rankooh

We introduce a method for computing immediately human interpretable yet accurate classifiers from tabular data. The classifiers obtained are short Boolean formulas, computed via first discretizing the original data and then using feature selection coupled with a very fast algorithm for producing the best possible Boolean classifier for the setting. We demons

Francesco Scotti, Andrea Flori, Piercesare Secchi, Marika Arena

This paper aims to explore the factors stimulating different tourism behaviours, with specific reference to same-day visits and overnight stays. To this aim, we employ mobile network data referred to the area of Lombardy. The paper highlights that larger availability of tourism accommodations, cultural and natural endowments are relevant factors explaining o

Kingman Cheung, C. J. Ouseph

We interpret the recent excess in a rare decay of the Higgs boson, $H\to Z\gamma$, using a light axion-like particle (ALP) in the massrange $0.05 - 0.1$ GeV.The dominant decay of such a light ALP is into a pair of collimated photons, whose decay is required to happen before reaching the ECAL detector, such that it mimics a single photon in the detector. It c

Nurdagül Anbar, Sadmir Kudin, Wilfried Meidl, Enes Pasalic

In Pasalic et al., IEEE Trans. Inform. Theory 69 (2023), 2702--2712, and in Anbar, Meidl, Cryptogr. Commun. 10 (2018), 235--249, two different vectorial negabent and vectorial bent-negabent concepts are introduced, which leads to seemingly contradictory results. One of the main motivations for this article is to clarify the differences and similarities betwe

V. Garcia-Marina, I. Fernandez de Bustos, G. Urkullu, M. Abasolo

The method of the lower deformation energy has been successfully used for the synthesis of mechanisms for quite a while. It has shown to be a versatile, yet powerful method for assisting in the design of mechanisms. Until now, most of the implementations of this method used the dimensions of the mechanism as the synthesis variables, which has some advantages

Tong Chen, Raghavendra Selvan

Dataset Condensation (DC) refers to the recent class of dataset compression methods that generate a smaller, synthetic, dataset from a larger dataset. This synthetic dataset aims to retain the essential information of the original dataset, enabling models trained on it to achieve performance levels comparable to those trained on the full dataset. Most curren

Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro, Florent Krzakala

This work investigates adversarial training in the context of margin-based linear classifiers in the high-dimensional regime where the dimension $d$ and the number of data points $n$ diverge with a fixed ratio $\alpha = n / d$. We introduce a tractable mathematical model where the interplay between the data and adversarial attacker geometries can be studied,

Jeffrey Redondo, Zhenhui Yuan, Nauman Aslam

High-definition (HD) Map systems will play a pivotal role in advancing autonomous driving to a higher level, thanks to the significant improvement over traditional two-dimensional (2D) maps. Creating an HD Map requires a huge amount of on-road and off-road data. Typically, these raw datasets are collected and uploaded to cloud-based HD map service providers

Julio I. de Vicente

Entanglement is a resource under local operations assisted by classical communication (LOCC). Given a set of states $S$, if there is one state in $S$ that can be transformed by LOCC into all other states in $S$, then this state is maximally entangled in $S$. It is a well-known result that the $d$-dimensional Bell state is the maximally entangled state in the

Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang

This technical report presents the training methodology and evaluation results of the open-source multilingual E5 text embedding models, released in mid-2023. Three embedding models of different sizes (small / base / large) are provided, offering a balance between the inference efficiency and embedding quality. The training procedure adheres to the English E

Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones

Improvements in the representation of the land carbon cycle in Earth system models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) include interactive treatment of both the carbon and nitrogen cycles, improved photosynthesis, and soil hydrology. To assess the impact of these model developments on aspects of the global carbon cycle,

William Gryc, Loredana Lanzani, Jue Xiong, Yuan Zhang

We give new characterizations of the optimal data space for the $L^p(bD,\sigma)$-Neumann boundary value problem for the $\bar{\partial}$ operator associated to a bounded, Lipschitz domain $D\subset\mathbb{C}$. We show that the solution space is embedded (as a Banach space) in the Dirichlet space and that for $p=2$, the solution space is a reproducing kernel

Bertram Tschiderer

An intriguing question in martingale optimal transport is to characterize the martingale with prescribed initial and terminal marginals whose transition kernel is as Gaussian as possible. In this work we address an extension of this question, in which the role of the Gaussian distribution is replaced by an arbitrary reference measure $q$. Our first main resu

Junjie Chu, Yugeng Liu, Ziqing Yang, Xinyue Shen

Jailbreak attacks aim to bypass the LLMs' safeguards. While researchers have proposed different jailbreak attacks in depth, they have done so in isolation -- either with unaligned settings or comparing a limited range of methods. To fill this gap, we present a large-scale evaluation of various jailbreak attacks. We collect 17 representative jailbreak attacks

Mustapha Bounoua, Giulio Franzese, Pietro Michiardi

The analysis of scientific data and complex multivariate systems requires information quantities that capture relationships among multiple random variables. Recently, new information-theoretic measures have been developed to overcome the shortcomings of classical ones, such as mutual information, that are restricted to considering pairwise interactions. Amon

Bart De Bruyn, Geertrui Van de Voorde

In this paper, we characterise ovoidal cones by their intersection numbers. We first show that a set of points of $\mathrm{PG}(4,q)$ which intersects planes in $1$, $q+1$ or $2q+1$ points is either an ovoidal cone or a parabolic quadric, unless $q=3$, in which case also a sporadic example with automorphism group $M_{11}$ exists. We then show that a set of po

A. Dastbaravarde, A. Dolati

A popular measure of association is the tail dependence coefficient which measures the strength of dependence in either the lower-left or upper-right tail of a bivariate distribution. In this paper, we develop the idea of quantile dependence, which generalizes the notion of tail dependence and could be used to detect dependence in specific regions of the dom

David J. Setton, Gourav Khullar, Tim B. Miller, Rachel Bezanson

We report the spectroscopic confirmation of a massive ($\log(M_\star/M_\odot)=10.34 \pm_{0.07}^{0.06}$), HST-dark ($m_\mathrm{F150W} - m_\mathrm{F444W} = 3.6$) quiescent galaxy at $z_{spec}=3.97$ in the UNCOVER survey. NIRSpec/PRISM spectroscopy and a non-detection in deep ALMA imaging surprisingly reveals that the galaxy is consistent with a low ($<$10 $M_\

Raphael Chekroun, Han Wang, Jonathan Lee, Marin Toromanoff

Accurate real-time traffic state forecasting plays a pivotal role in traffic control research. In particular, the CIRCLES consortium project necessitates predictive techniques to mitigate the impact of data source delays. After the success of the MegaVanderTest experiment, this paper aims at overcoming the current system limitations and develop a more suited

Peter Nicholas Hansen, Dimitrios Papageorgiou, Roberto Galeazzi, Mogens Blanke

The encounter situation between marine vessels determines how they should navigate to obey COLREGs, but time-varying and stochastic uncertainty in estimation of angles of encounter, and of closest point of approach, easily give rise to different assessment of situation at two approaching vessels. This may lead to high-risk conditions and could cause collisio

Raoni Arroyo, Jonas R. Becker Arenhart

Philosophers of science commonly connect ontology and science, stating that these disciplines maintain a two-way relationship: on the one hand, we can extract ontology from scientific theories; on the other hand, ontology provides the realistic content of our scientific theories. In this article, we will critically examine the process of naturalizing ontolog

Meihan Liu, Zeyu Fang, Zhen Zhang, Ming Gu

Unsupervised Graph Domain Adaptation (UGDA) aims to transfer knowledge from a labelled source graph to an unlabelled target graph in order to address the distribution shifts between graph domains. Previous works have primarily focused on aligning data from the source and target graph in the representation space learned by graph neural networks (GNNs). Howeve

Eden Arbel, Luco L. K. M. Buise, Charlotte C. R. M. M. van Waes, Naomi Oppenheimer

Cooperative transport is a striking phenomenon where multiple agents join forces to transit a payload too heavy for the individual. While social animals such as ants are routinely observed to coordinate transport at scale, reproducing the effect in artificial swarms remains challenging, as it requires synchronization in a noisy many-body system. Here we show

Hye Jin Kim, Nicolas Lell, Ansgar Scherp

Text role classification involves classifying the semantic role of textual elements within scientific charts. For this task, we propose to finetune two pretrained multimodal document layout analysis models, LayoutLMv3 and UDOP, on chart datasets. The transformers utilize the three modalities of text, image, and layout as input. We further investigate whether

W. E. Celnik, I. Karachentsev, P. Köchling, S. Kotov

Planetary nebulae are one of the final stages in the evolution of low and intermediate mass stars. They occur in a variety of shapes. Older and fainter ones are generally more difficult to identify because of the lower surface brightness. This paper reports the serendipitous discovery of a new faint Galactic planetary nebula (PN), during a campaign to identi

Antoine Renard, Michel Rigo, Markus A. Whiteland

We have introduced a q-deformation, i.e., a polynomial in q with natural coefficients, of the binomial coefficient of two finite words u and v counting the number of occurrences of v as a subword of u. In this paper, we examine the q-deformation of Parikh matrices as introduced by E\u{g}ecio\u{g}lu in 2004. Many classical results concerning Parikh matrices g

Annoy Sengupta, Amit Kuber

Generalising a recent work of Dequ\^ene et al. on the connection between perfectly clustering words and band bricks over a particular family of gentle algebras, we characterise band bricks over string algebras whose underlying quiver is acyclic in terms of weakly perfectly clustering pairs of words -- a variant of perfectly clustering words. As a consequence

Shikun Ban, Juling Fan, Xiaoxuan Ma, Wentao Zhu

Estimating robot pose from RGB images is a crucial problem in computer vision and robotics. While previous methods have achieved promising performance, most of them presume full knowledge of robot internal states, e.g. ground-truth robot joint angles. However, this assumption is not always valid in practical situations. In real-world applications such as mul

Moumita Mondal, Santanu K. Maiti

In this work, we put forward, for the first time, the interplay between correlated disorder and hopping dimerization on bias driven circular current in a loop conductor that is clamped between two electrodes. The correlated disorder is introduced in site energies of the ring in the form of Aubry-Andr\'e-Harper (AAH) model. Simulating the quantum system withi

Timur Shakirov

We provide analysis of the convergence properties and applicability extensions of flat-histogram algorithms, with a particular focus on the Wang-Landau algorithms (exemplified by converging stochastic approximation Monte Carlo (SAMC)) and multicanonical (MUCA) algorithms. Our investigation reveals that the optimal decay rate of the modification factor in SAM

Han Wang, Ana B. Villas Bôas, Jacques Vanneste, William R. Young

Ocean turbulence at meso- and submesocales affects the propagation of surface waves through refraction and scattering, inducing spatial modulations in significant wave height (SWH). We develop a theoretical framework that relates these modulations to the current that induces them. We exploit the asymptotic smallness of the ratio of typical current speed to w

D. A. Miranda, T. V. C. Antão, N. M. R Peres

In this paper we discussed the topological transition between trivial and nontrivial phases of a quasi-periodic (Aubry-Andr\'e like) mechanical Su-Schrieffer-Heeger (SSH) model. We find that there exists a nontrivial boundary separating the two topological phases and an analytical expression for this boundary is found. We discuss the localization of the vibr

Wei Wang, Huilong Ning, Gaowei Zhang, Libo Liu

Recently, large language models (LLM) based generative AI has been gaining momentum for their impressive high-quality performances in multiple domains, particularly after the release of the ChatGPT. Many believe that they have the potential to perform general-purpose problem-solving in software development and replace human software developers. Nevertheless,

Mohammad Cheraghinia, Adnan Shahid, Stijn Luchie, Gert-Jan Gordebeke

Due to their large bandwidth, relatively low cost, and robust performance, UWB radio chips can be used for a wide variety of applications, including localization, communication, and radar. This article offers an exhaustive survey of recent progress in UWB radar technology. The goal of this survey is to provide a comprehensive view of the technical fundamenta

Beniamin Bogosel

The convex shape contained in a disk having prescribed area and maximal perimeter is completely characterized in terms of the area fraction. The solution is always a polygon having all but one sides equal. The lengths of the sides are characterized through explicit equations. The case of more general containing shapes is also discussed from both theoretical

Nayoung Kim, Minsu Kim, Sungsoo Ahn, Jinkyoo Park

Recently, deep learning has made rapid progress in antibody design, which plays a key role in the advancement of therapeutics. A dominant paradigm is to train a model to jointly generate the antibody sequence and the structure as a candidate. However, the joint generation requires the model to generate both the discrete amino acid categories and the continuo

Wan-Jin Lu, Ping Zhou, Pei Wang, Yi-Xuan Shao

Magnetars and central compact objects (CCOs) are subgroups of neutron stars that show a number of properties distinguished from canonical radio pulsars. We performed radio observations of three magnetars SGR 0418+5729, 1E 2259+586, 4U 0142+61, and a CCO PSR J1852+0040 with the Fivehundred-meter Aperture Spherical radio Telescope (FAST) at 1.25 GHz, aiming to

François L. A. Visconti

In the present paper we study the low density Bose gas in the thermodynamic limit interacting via two-body and three-body interaction potentials. We prove that the leading order of the ground state energy is entirely characterised by both the scattering length of the two-body potential and the scattering energy of the three-body potential. The corresponding

Adil Mukhtar, Dietmar Jannach, Franz Wotawa

Over the past few years, deep learning methods have been applied for a wide range of Software Engineering (SE) tasks, including in particular for the important task of automatically predicting and localizing faults in software. With the rapid adoption of increasingly complex machine learning models, it however becomes more and more difficult for scholars to

Hanzhi Chen, Binbin Xu, Stefan Leutenegger

We present FuncGrasp, a framework that can infer dense yet reliable grasp configurations for unseen objects using one annotated object and single-view RGB-D observation via categorical priors. Unlike previous works that only transfer a set of grasp poses, FuncGrasp aims to transfer infinite configurations parameterized by an object-centric continuous grasp f

Lior Cohen, Kaixin Wang, Bingyi Kang, Shie Mannor

Motivated by the success of Transformers when applied to sequences of discrete symbols, token-based world models (TBWMs) were recently proposed as sample-efficient methods. In TBWMs, the world model consumes agent experience as a language-like sequence of tokens, where each observation constitutes a sub-sequence. However, during imagination, the sequential t

Minheng Chen, Tonglong Li, Zhirun Zhang, Youyong Kong

A robust and efficient optimization-based 2D/3D registration framework is crucial for the navigation system of orthopedic surgical robots. It can provide precise position information of surgical instruments and implants during surgery. While artificial intelligence technology has advanced rapidly in recent years, traditional optimization-based registration m

Eya Ben Amar, Nadhir Ben Rached, Raul Tempone, Mohamed-Slim Alouini

This paper addresses the difficulty of characterizing the time-varying nature of fading channels. The current time-invariant models often fall short of capturing and tracking these dynamic characteristics. To overcome this limitation, we explore using of stochastic differential equations (SDEs) and Markovian projection to model signal envelope variations, co

Jiaqi Zhu, Nikolaos Pappas, Howard H. Yang

We leverage the Multiplicative Weight Update (MWU) method to develop a decentralized algorithm that significantly improves the performance of dynamic time division duplexing (D-TDD) in small cell networks. The proposed algorithm adaptively adjusts the time portion allocated to uplink (UL) and downlink (DL) transmissions at every node during each scheduled ti

Jean C. Cortissoz

We discuss the behavior of harmonic functions on Riemannian cones as defined below and Lioville's theorem.

Benjamin Kiessling, Gennady Kurin, Matthew Thomas Miller, Kader Smail

This work presents an accuracy study of the open source OCR engine, Kraken, on the leading Arabic scholarly journal, al-Abhath. In contrast with other commercially available OCR engines, Kraken is shown to be capable of producing highly accurate Arabic-script OCR. The study also assesses the relative accuracy of typeface-specific and generalized models on th

Yuri Fonseca, Caio Peixoto, Yuri Saporito

Instrumental variables (IVs) provide a powerful strategy for identifying causal effects in the presence of unobservable confounders. Within the nonparametric setting (NPIV), recent methods have been based on nonlinear generalizations of Two-Stage Least Squares and on minimax formulations derived from moment conditions or duality. In a novel direction, we sho

Jozef Bobok, Jernej Činč, Piotr Oprocha, Serge Troubetzkoy

We consider the class of interval maps with dense set of periodic points CP and its closure Cl(CP) equipped with the metric of uniform convergence. Besides studying basic topological properties and density results in the spaces CP and Cl(CP) we prove that Cl(CP) is dynamically characterized as the set of interval maps for which every point is chain-recurrent

Deliang Wei, Peng Chen, Fang Li

Deep denoisers have shown excellent performance in solving inverse problems in signal and image processing. In order to guarantee the convergence, the denoiser needs to satisfy some Lipschitz conditions like non-expansiveness. However, enforcing such constraints inevitably compromises recovery performance. This paper introduces a novel training strategy that

Sayan Chatterjee, Ching Louis Liu, Gareth Rowland, Tim Hogarth

The increasing popularity of AI, particularly Large Language Models (LLMs), has significantly impacted various domains, including Software Engineering. This study explores the integration of AI tools in software engineering practices within a large organization. We focus on ANZ Bank, which employs over 5000 engineers covering all aspects of the software deve

Charles Bertucci, Charles Meynard

This paper provides a mathematical study of the well-posedness of master equation on finite state space involving terms modelling common noise. In this setting, the solution of the master equation depends on an additional variable modelling the value of a stochastic process impacting all players. Using technique from viscosity solutions, we give sufficient c

Kento Nishio, Kiyou Shibata, Teruyasu Mizoguchi

A Model capable of handling various elemental species and substances is essential for discovering new materials in the vast phase and compound space. Message-passing neural networks (MPNNs) are promising as such models, in which various vector operations model the atomic interaction with its neighbors. However, conventional MPNNs tend to overlook the importa

Santtu Tikka, Juha Karvanen

Missing data may be disastrous for the identifiability of causal and statistical estimands. In graphical missing data models, colluders are dependence structures that have a special importance for identification considerations. It has been shown that the presence of a colluder makes the full law, i.e., the joint distribution of variables and response indicat

J Dedecker, F Merlevède, M Peligrad

In this paper, we consider partial sums of martingale differences weighted by random variables drawn uniformly on the sphere, and globally independent of the martingale differences. Combining Lindeberg's method and a series of arguments due to Bobkov, Chistyakov and G{\"o}tze, we show that the Kolmogorov distance between the distribution of these weighted su

Lucas Foulon, Ilyes Korichi, Xavier Millot

The elasticity of the DTW metric provides a more flexible comparison between time series and is used in numerous machine learning domains such as classification or clustering. However, it does not align the measurements at the beginning and end of time series if they have a shift occurring right at the start of one series, with the omitted part appearing at

Jean-Guillaume Dumas, Clément Pernet, Alexandre Sedoglavic

We propose a non-commutative algorithm for multiplying 2x2 matrices using 7 coefficient products. This algorithm reaches simultaneously a better accuracy in practice compared to previously known such fast algorithms, and a time complexity bound with the best currently known leading term (obtained via alternate basis sparsification). To build this algorithm,

Cheng-Han Chiang, Hung-yi Lee

Long-form generations from large language models (LLMs) contain a mix of factual and non-factual claims, making evaluating factuality difficult. Prior works evaluate the factuality of a long paragraph by decomposing it into multiple facts, verifying those facts independently, and aggregating the results. Such methods assume that combining factual claims form

Zhikai Li, Xuewen Liu, Jing Zhang, Qingyi Gu

Large transformer models have demonstrated remarkable success. Post-training quantization (PTQ), which requires only a small dataset for calibration and avoids end-to-end retraining, is a promising solution for compressing these large models. Regrettably, existing PTQ methods typically exhibit non-trivial performance loss. We find that the performance bottle

Sindy Löwe, Francesco Locatello, Max Welling

In human cognition, the binding problem describes the open question of how the brain flexibly integrates diverse information into cohesive object representations. Analogously, in machine learning, there is a pursuit for models capable of strong generalization and reasoning by learning object-centric representations in an unsupervised manner. Drawing from neu

Frank Zhengqing Wu, Berfin Simsek, Francois Gaston Ged

In this paper, we study the loss landscape of one-hidden-layer neural networks with ReLU-like activation functions trained with the empirical squared loss using gradient descent (GD). We identify the stationary points of such networks, which significantly slow down loss decrease during training. To capture such points while accounting for the non-differentia

Xiaoqi Liu, Kuan Hsieh, Ramji Venkataramanan

We consider communication over the Gaussian multiple-access channel in the regime where the number of users grows linearly with the codelength. In this regime, schemes based on sparse superposition coding can achieve a near-optimal tradeoff between spectral efficiency and signal-to-noise ratio. However, these schemes are feasible only for small values of use

Lou Salaun, Hong Yang, Shashwat Mishra, Chung Shue Chen

Beyond 5G wireless technology Cell-Free Massive MIMO (CFmMIMO) downlink relies on carefully designed precoders and power control to attain uniformly high rate coverage. Many such power control problems can be calculated via second order cone programming (SOCP). In practice, several order of magnitude faster numerical procedure is required because power contr

Christoph Tillmann, Aashka Trivedi, Bishwaranjan Bhattacharjee

Large Language Models (LLMs) are the cornerstone for many Natural Language Processing (NLP) tasks like sentiment analysis, document classification, named entity recognition, question answering, summarization, etc. LLMs are often trained on data which originates from the web. This data is prone to having content with Hate, Abuse and Profanity (HAP). For a det

Cheng-Yang Lee, Haomin Rao, Wenqi Yu, Siyi Zhou

Cosmelkology is the study of Elko in cosmology. Elko is a massive spin-half field of mass dimension one. Elko differs from the Dirac and Majorana fermions because it furnishes the irreducible representation of the extended Poincare group with a two-fold Wigner degeneracy where the particle and anti-particle states both have four degrees of freedom. Elko has

Roberto Taverna, Roberto Turolla

The launch of IXPE telescope in late 2021 finally made polarization measurements in the 2-8 keV band a reality, more than 40 years after the pioneering observations of the OSO-8 satellite. In the first two years of operations IXPE targeted more than 60 sources, including four magnetars, neutron stars with magnetic fields in the petaGauss range. In this paper

Kayn A. Forbes

The optical chirality and spin angular momentum of structured scalar vortex beams has been intensively studied in recent years. The pseudoscalar topological charge $\ell$ of these beams is responsible for their unique properties. Constructed from a superposition of scalar vortex beams with topological charges $\ell_\text{A}$ and $\ell_\text{B}$, cylindrical