March 2024 arXiv papers — page 131

Menno Door, Chih-Han Yeh, Matthias Heinz, Fiona Kirk

In this Letter, we present mass-ratio measurements on highly charged Yb$^{42+}$ ions with a precision of $4\times 10^{-12}$ and isotope-shift measurements on Yb$^{+}$ on the $^{2}$S$_{1/2}$ $\to$ $^{2}$D$_{5/2}$ and $^{2}$S$_{1/2}$ $\to$ $^{2}$F$_{7/2}$ transitions with a precision of $4\times 10^{-9}$ for the isotopes $^{168,170,172,174,176}$Yb. We present

Sameer Iyer

The (favorable) Falkner-Skan boundary layer profiles are a one parameter ($\beta \in [0,2]$) family of self-similar solutions to the stationary Prandtl system which describes the flow over a wedge with angle $\beta \frac{\pi}{2}$. The most famous member of this family is the endpoint Blasius profile, $\beta = 0$, which exhibits pressureless flow over a flat

S. Ahyoune, A. Álvarez Melcón, S. Arguedas Cuendis, S. Calatroni

We describe the results of a haloscope axion search performed with an 11.7 T dipole magnet at CERN. The search used a custom-made radio-frequency cavity coated with high-temperature superconducting tape. A set of 27 h of data at a resonant frequency of around 8.84 GHz was analysed. In the range of axion mass 36.5676 $\mu$eV to 36.5699 $\mu$eV, corresponding

Efimia Panagiotaki, Tyler Reinmund, Stephan Mouton, Luke Pitt

This paper introduces RobotCycle, a novel ongoing project that leverages Autonomous Vehicle (AV) research to investigate how road infrastructure influences cyclist behaviour and safety during real-world journeys. The project's requirements were defined in collaboration with key stakeholders, including city planners, cyclists, and policymakers, informing the

Chaoyi Zhu, Jeroen Galjaard, Pin-Yu Chen, Lydia Y. Chen

As large language models (LLM) are increasingly used for text generation tasks, it is critical to audit their usages, govern their applications, and mitigate their potential harms. Existing watermark techniques are shown effective in embedding single human-imperceptible and machine-detectable patterns without significantly affecting generated text quality an

Chen Wang, Haochen Shi, Weizhuo Wang, Ruohan Zhang

Imitation learning from human hand motion data presents a promising avenue for imbuing robots with human-like dexterity in real-world manipulation tasks. Despite this potential, substantial challenges persist, particularly with the portability of existing hand motion capture (mocap) systems and the complexity of translating mocap data into effective robotic

Samardhi Yadav, Vishal Vaibhav

The transparent boundary condition for the free Schr\"{o}dinger equation on a rectangular computational domain requires implementation of an operator of the form $\sqrt{\partial_t-i\triangle_{\Gamma}}$ where $\triangle_{\Gamma}$ is the Laplace-Beltrami operator. It is known that this operator is nonlocal in time as well as space which poses a significant cha

Ronald B. Liu, Zhe Liu, Max G. A. Wolf, Krishna P. Purohit

Advancements in high-throughput biomedical applications require real-time, large field-of-view (FOV) imaging. While current 2D lens-free imaging (LFI) systems improve FOV, they are often hindered by time-consuming multi-position measurements, extensive data pre-processing, and strict optical parameterization, limiting their application to static, thin sample

Alfredo Marín, Luisa I. Martínez-Merino, Antonio M. Rodríguez-Chía, Francisco Saldanha-da-Gama

This paper introduces a very general discrete covering location model that accounts for uncertainty and time-dependent aspects. A MILP formulation is proposed for the problem. Afterwards, it is observed that most of the models existing in the literature related with covering location can be considered as particular cases of this formulation. In order to tack

N. Astrakhantsev, V. V. Braguta, A. Yu. Kotov, A. A. Roenko

This paper is devoted to the study of QCD equation of state in external magnetic field and nonzero baryon density. Our study is carried out by means of lattice simulation with 2+1 dynamical staggered quarks at the physical masses. The simulation is conducted at imaginary baryon chemical potential what allowed us to overcome the sign problem. We expand the pr

Leonardo García-Heveling

In 1972, Geroch, Kronheimer, and Penrose introduced what is now called the causal boundary of a spacetime. This boundary is constructed out of Terminal Indecomposable Past sets (TIPs) and their future analogues (TIFs), which are the pasts and futures of inextendible causal curves. The causal boundary is a key tool to understand the global structure of a spac

Mathias Driesse, Gustav Uhre Jakobsen, Gustav Mogull, Jan Plefka

We compute the 5PM order contributions to the scattering angle and impulse of classical black hole scattering in the conservative sector at first self-force order (1SF) using the worldline quantum field theory formalism. This challenging four-loop computation required the use of advanced integration-by-parts and differential equation technology implemented o

Xianli Zeng, Joshua Ward, Guang Cheng

The increasing usage of machine learning models in consequential decision-making processes has spurred research into the fairness of these systems. While significant work has been done to study group fairness in the in-processing and post-processing setting, there has been little that theoretically connects these results to the pre-processing domain. This pa

Parikshit Boregowda, G R Liu

Algorithms for initializing particle distribution in SPH simulations are important for improving simulation accuracy. However, no such algorithms exist for boundary integral SPH models, which can model complex geometries without requiring layers of virtual particles. This study introduces the Boundary Integral based Particle Initialization (BIPI) algorithm.

Taban Baghfalaki, Mojtaba Ganjali, Antoine Barbieri, Reza Hashemi

The objective of this paper is to provide an introduction to the principles of Bayesian joint modeling of longitudinal measurements and time-to-event outcomes, as well as model implementation using the BUGS language syntax. This syntax can be executed directly using OpenBUGS or by utilizing convenient functions to invoke OpenBUGS and JAGS from R software. In

Yisheng Tu, Zhi-Yun Li, Zhaohuan Zhu, Chun-Yen Hsu

The majority of stars are in binary/multiple systems. How such systems form in turbulent, magnetized cores of molecular clouds in the presence of non-ideal MHD effects remains relatively under-explored. Through ATHENA++-based non-ideal MHD AMR simulations with ambipolar diffusion, we show that the collapsing protostellar envelope is dominated by dense gravo-

Johannes Carmesin, George Kontogeorgiou, Jan Kurkofka, Will J. Turner

A recent development in graph-minor theory is to study local separators, vertex-sets that separate graphs locally but not necessarily globally. The local separators of a graph roughly correspond to the genuine separators of its local covering: a usually infinite graph obtained by keeping all local structure of the original graph while unfolding all other str

Luisa I. Martínez-Merino, Maria Albareda-Sambola, Antonio M. Rodríguez-Chía

This work deals with the probabilistic p-center problem, which aims at minimizing the expected maximum distance between any site with demand and its center, considering that each site has demand with a specific probability. The problem is of interest when emergencies may occur at predefined sites with known probabilities. For this problem we propose and anal

Yasser Saleem, Torben Steenbock, Emha Riyadhul Jinan Alhadi, Weronika Pasek

We show that the origin of the antiferromagnetic coupling in spin-1 triangulene chains, which were recently synthesized and measured by Mishra et al. Nature 598, 287-292 (2021) originates from a superexchange mechanism. This process, mediated by inter-triangulene states, opens the possibility to control parameters in the effective bilinear-biquadratic spin m

Jumin Lee, Sebin Lee, Changho Jo, Woobin Im

We present "SemCity," a 3D diffusion model for semantic scene generation in real-world outdoor environments. Most 3D diffusion models focus on generating a single object, synthetic indoor scenes, or synthetic outdoor scenes, while the generation of real-world outdoor scenes is rarely addressed. In this paper, we concentrate on generating a real-outdoor scene

Shenggang Hu, Louis Aslett, Hongsheng Dai, Murray Pollock

In recent years, differential privacy has been adopted by tech-companies and governmental agencies as the standard for measuring privacy in algorithms. In this article, we study differential privacy in Bayesian posterior sampling settings. We begin by considering differential privacy in the most common privatisation setting in which Laplace or Gaussian noise

Louis Alaerts, Yihuang Xiong, Sinéad Griffin, Geoffroy Hautier

Point defects in semiconductors are attractive candidates for quantum information science applications owing to their ability to act as spin-photon interface or single-photon emitters. However, the coupling between the change of dipole moment upon electronic excitation and stray electric fields in the vicinity of the defect, an effect known as Stark shift, c

Félix Ingrand

Acting is an important decisional function for autonomous robots. Acting relies on skills to implement and to model the activities it oversees: refinement, local recovery, temporal dispatching, external asynchronous events, and commands execution, all done online. While sitting between planning and the robotic platform, acting often relies on programming pri

Carlos Jose Xavier Cruz

This article explores the dynamic influence of computational entities based on multi-agent systems theory (SMA) combined with large language models (LLM), which are characterized by their ability to simulate complex human interactions, as a possibility to revolutionize human user interaction from the use of specialized artificial agents to support everything

Hao Xu

In this article, we investigate monoidal, braided, sylleptic centralizers of monoidal, braided, sylleptic 2-functors. We specifically focus on multifusion 2-categories and show that monoidal, braided, sylleptic centralizers are multifusion again, via studying the corresponding enveloping algebras. We provide a characterization of the non-degeneracy condition

Jan Pešán, Santosh Kesiraju, Lukáš Burget, Jan ''Honza'' Černocký

Paralinguistic traits like cognitive load and emotion are increasingly recognized as pivotal areas in speech recognition research, often examined through specialized datasets like CLSE and IEMOCAP. However, the integrity of these datasets is seldom scrutinized for text-dependency. This paper critically evaluates the prevalent assumption that machine learning

Alejandro Calleja

In this paper, we study the configuration space of orbits, a generalization of the configuration space of points but for algebraic varieties that are acted by an algebraic reductive group. The main objective of this work is to study the $E$-polynomials of these spaces and their quotients by $S_n$. For this purpose, we develop a novel method for computing the

Yuxuan Zhang, Yirui Yuan, Yiren Song, Jiaming Liu

Current makeup transfer methods are limited to simple makeup styles, making them difficult to apply in real-world scenarios. In this paper, we introduce Stable-Makeup, a novel diffusion-based makeup transfer method capable of robustly transferring a wide range of real-world makeup, onto user-provided faces. Stable-Makeup is based on a pre-trained diffusion m

Cong T. Nguyen, Yuris Mulya Saputra, Nguyen Van Huynh, Tan N. Nguyen

Terrestrial networks form the fundamental infrastructure of modern communication systems, serving more than 4 billion users globally. However, terrestrial networks are facing a wide range of challenges, from coverage and reliability to interference and congestion. As the demands of the 6G era are expected to be much higher, it is crucial to address these cha

Austin Z. Henley, David Piorkowski

Without well-labeled ground truth data, machine learning-based systems would not be as ubiquitous as they are today, but these systems rely on substantial amounts of correctly labeled data. Unfortunately, crowdsourced labeling is time consuming and expensive. To address the concerns of effort and tedium, we designed CAL, a novel interface to aid in data labe

Fernando Galve, Eduardo Pallás, Teresa Guallart-Naval, Pablo García-Cristóbal

Objective. To develop methods to design the complete magnetic system for a truly portable MRI scanner for neurological and musculoskeletal (MSK) applications, optimized for field homogeneity, field of view (FoV) and gradient performance compared to existing low-weight configurations. Approach. We explore optimal elliptic-bore Halbach configurations based on

Dmitry Kosolobov

Given an increasing sequence of integers $x_1,\ldots,x_n$ from a universe $\{0,\ldots,u-1\}$, the monotone minimal perfect hash function (MMPHF) for this sequence is a data structure that answers the following rank queries: $rank(x) = i$ if $x = x_i$, for $i\in \{1,\ldots,n\}$, and $rank(x)$ is arbitrary otherwise. Assadi, Farach-Colton, and Kuszmaul recentl

Stefano Palmisano, Francesco Rescigno, Federica Troni

We consider models of accidental dark matter, namely models in which the dark matter is a composite state that is stable thanks to an accidental symmetry of the theory. The fundamental constituents are vectorlike fermions, taken to be fragments of representations of the grand unifying gauge group $SU(5)$, as well as a scalar singlet. All the new fields are c

Akwasi Akwaboah, Ralph Etienne-Cummings

The promise of increasing channel counts in high density ($> 10^4$) neural Microelectrode Arrays (MEAs) for high resolution recording comes with the curse of developing faster characterization strategies for concurrent acquisition of multichannel electrode integrities over a wide frequency spectrum. To circumvent the latency associated with the current multi

C. Vastel, T. Sakai, C. Ceccarelli, I. Jiménez-Serra

iCOMs are species commonly found in the interstellar medium. They are believed to be crucial seed species for the build-up of chemical complexity in star forming regions as well as our own Solar System. Thus, understanding how their abundances evolve during the star formation process and whether it enriches the emerging planetary system is of paramount impor

Jonathan Kriewald, Miha Nemevšek, Fabrizio Nesti

We investigate the structure of the minimal Left-Right symmetric model that enables precise predictions in the gauge, scalar and neutrino sector. We revisit the complete set of mass spectra and mixings for the charged and neutral gauge bosons, would-be-Goldstones and gauge fixing, together with the ghost Lagrangian. In the scalar sector, we analytically re-d

Nicholas Uhorchak, Ruben A. Proano, Sandra Eksioglu, Fatih Cengil

Effective and efficient scheduling of vaccine distribution can significantly impact vaccine uptake, which is critical to controlling the spread of infectious diseases. Ineffective scheduling can lead to waste, delays, and low vaccine coverage, potentially weakening the efforts to protect the public. Organizations such as UNICEF (United Nations Children's Fun

Shubhransh Singhvi, Roni Con, Han Mao Kiah, Eitan Yaakobi

The sequence reconstruction problem, introduced by Levenshtein in 2001, considers a scenario where the sender transmits a codeword from some codebook, and the receiver obtains $N$ noisy outputs of the codeword. We study the problem of efficient reconstruction using $N$ outputs that are each corrupted by at most $t$ substitutions. Specifically, for the ubiqui

Marta Baldomero-Naranjo, Luisa I. Martínez-Merino, Antonio M. Rodríguez-Chía

This paper proposes a robust classification model, based on support vector machine (SVM), which simultaneously deals with outliers detection and feature selection. The classifier is built considering the ramp loss margin error and it includes a budget constraint to limit the number of selected features. The search of this classifier is modeled using a mixed-

Chunfeng Zhang, Ping Wang

Due to the needs of road traffic flow monitoring and public safety management, video surveillance cameras are widely distributed in urban roads. However, the information captured directly by each camera is siloed, making it difficult to use it effectively. Vehicle re-identification refers to finding a vehicle that appears under one camera in another camera,

Marie-Charlotte Brandenburg, Georg Loho, Ben Smith

We unify the study of quotients of matroids, polymatroids, valuated matroids and strong maps of submodular functions in the framework of Murota's discrete convex analysis. As a main result, we compile a list of ten equivalent characterizations of quotients for M-convex sets, generalizing existing formulations for (poly)matroids and submodular functions. We a

Sahand Sharifzadeh, Christos Kaplanis, Shreya Pathak, Dharshan Kumaran

The creation of high-quality human-labeled image-caption datasets presents a significant bottleneck in the development of Visual-Language Models (VLMs). In this work, we investigate an approach that leverages the strengths of Large Language Models (LLMs) and image generation models to create synthetic image-text pairs for efficient and effective VLM training

Aneesh Raghavan, Karl Henrik Johansson

We consider the problem of estimation of a function by a system consisting of two agents and a fusion center. The two agents collect data comprising of samples of an independent variable and the corresponding value of a dependent variable. The objective of the system is to collaboratively estimate the function without any exchange of data among the members o

Romain Cosson

We investigate two fundamental problems in mobile computing: exploration and rendezvous, with two distinct mobile agents in an unknown graph. The agents may communicate by reading and writing information on whiteboards that are located at all nodes. They both move along one adjacent edge at every time-step. In the exploration problem, the agents start from t

Yan Liu, Renren Jin, Ling Shi, Zheng Yao

To thoroughly assess the mathematical reasoning abilities of Large Language Models (LLMs), we need to carefully curate evaluation datasets covering diverse mathematical concepts and mathematical problems at different difficulty levels. In pursuit of this objective, we propose FineMath in this paper, a fine-grained mathematical evaluation benchmark dataset fo

Davide Maltoni, Lorenzo Pellegrini

TPC (Three-Phase Consolidation) is here introduced as a simple but effective approach to continually learn new classes (and/or instances of known classes) while controlling forgetting of previous knowledge. Each experience (a.k.a. task) is learned in three phases characterized by different rules and learning dynamics, aimed at removing the class-bias problem

Philipp Wolters, Johannes Gilg, Torben Teepe, Fabian Herzog

Low-cost, vision-centric 3D perception systems for autonomous driving have made significant progress in recent years, narrowing the gap to expensive LiDAR-based methods. The primary challenge in becoming a fully reliable alternative lies in robust depth prediction capabilities, as camera-based systems struggle with long detection ranges and adverse lighting

Usef Faghihi, Amir Saki

Let $X$ and $Z$ be random vectors, and $Y=g(X,Z)$. In this paper, on the one hand, for the case that $X$ and $Z$ are continuous, by using the ideas from the total variation and the flux of $g$, we develop a point of view in causal inference capable of dealing with a broad domain of causal problems. Indeed, we focus on a function, called Probabilistic Easy Va

Antoine Marquet, Simon Dupouy, Ulysse Réglade, Antoine Essig

Dissipation engineering offers a powerful tool for quantum technologies. Recently, new superconducting devices have achieved an engineered two-photon dissipation rate exceeding all other relevant timescales. In particular, they have proven most useful in preventing transitions between the logical states $|\pm\alpha\rangle$ of a cat qubit. Here, we present th

Neel Kanwal, Farbod Khoraminia, Umay Kiraz, Andres Mosquera-Zamudio

Histopathology is a gold standard for cancer diagnosis under a microscopic examination. However, histological tissue processing procedures result in artifacts, which are ultimately transferred to the digitized version of glass slides, known as whole slide images (WSIs). Artifacts are diagnostically irrelevant areas and may result in wrong deep learning (DL)

M. Oxland, L. C. Parker, R. R. de Carvalho, V. M. Sampaio

We investigate the role that dense environments have on the quenching of star formation and the transformation of morphology for a sample of galaxies selected from the Sloan Digital Sky Survey. We make a distinction between galaxies falling into groups $(13 \leq \log{(M_{\text{halo}}/M_{\odot})} < 14)$ and clusters $(\log{(M_{\text{halo}}/M_{\odot})} \geq 14

Kira Wursthorn, Markus Hillemann, Markus Ulrich

The estimation of 6D object poses is a fundamental task in many computer vision applications. Particularly, in high risk scenarios such as human-robot interaction, industrial inspection, and automation, reliable pose estimates are crucial. In the last years, increasingly accurate and robust deep-learning-based approaches for 6D object pose estimation have be

Xavier Crean, Jeffrey Giansiracusa, Biagio Lucini

In $4$-dimensional pure compact $U(1)$ lattice gauge theory, we analyse topological aspects of the dynamics of monopoles across the deconfinement phase transition. We do this using tools from Topological Data Analysis (TDA). We demonstrate that observables constructed from the zeroth and first homology groups of monopole current networks may be used to quant

Hieu Bui, Sandra Eksioglu, Ruben Proano

The COVID-19 pandemic highlighted significant challenges in the allocation of vital healthcare resources. Existing epidemiological models, specifically compartmental models, aimed to predict the spread of the COVID-19 virus and its impact on the population, but they overlooked the influence of \ac{VH} on disease dynamics, including the expected number of hos

Andrés Darío Bermúdez Manjarres, Marcel Reginatto, Sebastian Ulbricht

We present three statistical descriptions for systems of classical particles and consider their extension to hybrid quantum-classical systems. The classical descriptions are ensembles on configuration space, ensembles on phase space, and a Hilbert space approach using van Hove operators which provides an alternative to the Koopman-von Neumann formulation. In

Sujay Ray, Philipp Werner

The search for hidden orders in photoexcited lattice systems is an active research field driven by experimental reports of light-induced or light-stabilized phases. In this study, we investigate hidden electronic orders in strongly correlated two-orbital Hubbard models with orbital-dependent bandwidths. In equilibrium, the half-filled systems are antiferroma

Marta Baldomero-Naranjo, Luisa I. Martínez-Merino, Antonio M. Rodríguez-Chía

This paper considers various models of support vector machines with ramp loss, these being an efficient and robust tool in supervised classification for the detection of outliers. The exact solution approaches for the resulting optimization problem are of high demand for large datasets. Hence, the goal of this paper is to develop algorithms that provide effi

Florian Kalinke, Zoltan Szabo

Kernel techniques are among the most influential approaches in data science and statistics. Under mild conditions, the reproducing kernel Hilbert space associated to a kernel is capable of encoding the independence of $M\ge 2$ random variables. Probably the most widespread independence measure relying on kernels is the so-called Hilbert-Schmidt independence

Jorge Yanez, Leonid Kagan, Mike Kuznetsov, Gregory Sivashinsky

The disintegration of near limit flames propagating through the gap of Hele-Shaw cells has recently become a subject of active research. In this paper, the flamelets resulting from the disintegration of the continuous front are interpreted in terms of the Zeldovich flame-balls stabilized by volumetric heat losses. A complicated free-boundary problem for 2D s

Patrick Knab, Sascha Marton, Christian Bartelt

LIME (Local Interpretable Model-agnostic Explanations) is a popular XAI framework for unraveling decision-making processes in vision machine-learning models. The technique utilizes image segmentation methods to identify fixed regions for calculating feature importance scores as explanations. Therefore, poor segmentation can weaken the explanation and reduce

Mohamed Ragab, Yury Savateev, Wenjie Wang, Reza Moosaei

The DESERE Workshop, our First Workshop on Decentralised Search and Recommendation, offers a platform for researchers to explore and share innovative ideas on decentralised web services, mainly focusing on three major topics: (i) societal impact of decentralised systems: their effect on privacy, policy, and regulation; (ii) decentralising applications: algor

Cristian Ramírez, Adrián Castelló, Héctor Martínez, Enrique S. Quintana-Ortí

The devices designed for the Internet-of-Things encompass a large variety of distinct processor architectures, forming a highly heterogeneous zoo. In order to tackle this, we employ a simulator to estimate the performance of the matrix-matrix multiplication (GEMM) kernel on processors designed to operate at the edge. Our simulator adheres to the modern imple

Samuel R. Rogers, David Stewart, Paul Taplin, David Dye

The galling mechanism of Tristelle 5183, an Fe-based hardfacing alloy, was investigated at elevated temperature. The test was performed using a bespoke galling rig. Adhesive transfer and galling were found to occur, as a result of shear at the adhesion boundary and the activation of an internal shear plane within one of the tribosurfaces. During deformation,

Jean-Marcel Rax

Neutral kaons oscillations in a Schwarzschild spacetime are analyzed. The interplay between two oscillations: (i) mixing associated with second order weak coupling and (ii) strange quark's zitterbewegung, introduces a coupling responsible for the observed CP violation. This curvature induced violation is a CPT violation with T conservation rather than a T vi

Meiqi Li, Zhibing Li, Huanjun Chen, Weiliang Wang

In recent studies, it has been discovered that phonons can carry angular momentum, leading to a series of investigations into systems with 3-fold rotation symmetry. However, for systems with 2-fold screw rotational symmetry, such as $\alpha$-MoO$_3$, there has been no relevant discussion. In this paper, we investigated the pseudoangular momentum of phonons i

Yajie Bao, Yuyang Huo, Haojie Ren, Changliang Zou

We study the problem of post-selection predictive inference in an online fashion. To avoid devoting resources to unimportant units, a preliminary selection of the current individual before reporting its prediction interval is common and meaningful in online predictive tasks. Since the online selection causes a temporal multiplicity in the selected prediction

Laurent Pou, Francis Nimmo

Tidal dissipation in a celestial body can be used to probe its internal structure. Tides govern the orbital evolution of binary systems and therefore constraints on the interior of binary system members can be derived by knowing the age and tidal state of the binary system. For asteroids, age estimates are challenging due to a lack of direct observation of t

Timothee Mickus, Elaine Zosa, Raúl Vázquez, Teemu Vahtola

This paper presents the results of the SHROOM, a shared task focused on detecting hallucinations: outputs from natural language generation (NLG) systems that are fluent, yet inaccurate. Such cases of overgeneration put in jeopardy many NLG applications, where correctness is often mission-critical. The shared task was conducted with a newly constructed datase

Torgeir Aambø

Using Patchkoria--Pstr\k{a}gowski's version of Franke's algebraicity theorem, we prove that the category of $K_p(n)$-local spectra is exotically equivalent to the category of derived $I_n$-complete periodic comodules over the Adams Hopf algebroid $(E_*, E_*E)$ for large primes. This gives a finite prime result analogous to the asymptotic algebraicity for $\m

Zachary McBride Lazri, Danial Dervovic, Antigoni Polychroniadou, Ivan Brugere

Applications that deal with sensitive information may have restrictions placed on the data available to a machine learning (ML) classifier. For example, in some applications, a classifier may not have direct access to sensitive attributes, affecting its ability to produce accurate and fair decisions. This paper proposes a framework that models the trade-off

Zijian Liu, Zhengyuan Zhou

Shuffling gradient methods are widely used in modern machine learning tasks and include three popular implementations: Random Reshuffle (RR), Shuffle Once (SO), and Incremental Gradient (IG). Compared to the empirical success, the theoretical guarantee of shuffling gradient methods was not well-understood for a long time. Until recently, the convergence rate

B. Ait Ouazghour, M. Chabab, K. Goure

We study the one-loop prediction for the single production of a SM-like Higgs boson in association with a photon in electron-positron collisions in the context of the two Higgs doublet type-II seesaw model ($2HDMcT$). We explore to what extent the new scalars in the $2HDMcT$ spectrum affect its production cross-section, the ratio $R_{\gamma h_1}$ as well as

Dongyang Li, Chen Wei, Shiying Li, Jiachen Zou

How to decode human vision through neural signals has attracted a long-standing interest in neuroscience and machine learning. Modern contrastive learning and generative models improved the performance of visual decoding and reconstruction based on functional Magnetic Resonance Imaging (fMRI). However, the high cost and low temporal resolution of fMRI limit

Tianshuo Peng, Zuchao Li, Lefei Zhang, Hai Zhao

Large Language Models (LLMs), benefiting from the auto-regressive modelling approach performed on massive unannotated texts corpora, demonstrates powerful perceptual and reasoning capabilities. However, as for extending auto-regressive modelling to multi-modal scenarios to build Large Multi-modal Models (LMMs), there lies a great difficulty that the image in

Jiawen Li, Yuxuan Chen, Hongbo Chu, Qiehe Sun

Histopathological whole slide images (WSIs) classification has become a foundation task in medical microscopic imaging processing. Prevailing approaches involve learning WSIs as instance-bag representations, emphasizing significant instances but struggling to capture the interactions between instances. Additionally, conventional graph representation methods

Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji

We study the use of large language model-based agents for interacting with software via web browsers. Unlike prior work, we focus on measuring the agents' ability to perform tasks that span the typical daily work of knowledge workers utilizing enterprise software systems. To this end, we propose WorkArena, a remote-hosted benchmark of 33 tasks based on the w

Anna Trindade Falcao, T. J. Turner, S. B. Kraemer, V. Braito

We report the serendipitous multiwavelength discovery of a candidate dual black hole system with a separation of ~100 pc, in the gas-rich luminous infrared galaxy MCG-03-34-64 (z=0.016). Hubble Space Telescope/ACS observations show three distinct optical centroids in the [O III] narrow-band and F814W images. Subsequent analysis of Chandra/ACIS data shows two

Kaloyan Penev

The easiest exoplanets to detect are those that orbit very close to their hoststars. As a result, even though these planets are quite rare, they represent amajor fraction of the current exoplanet population. A side-effect of theproximity between the planet and the star is that the two have strong mutualinteractions through a number of physical processes. One

Blake VanBerlo, Alexander Wong, Jesse Hoey, Robert Arntfield

Self-supervised learning (SSL) is one strategy for addressing the paucity of labelled data in medical imaging by learning representations from unlabelled images. Contrastive and non-contrastive SSL methods produce learned representations that are similar for pairs of related images. Such pairs are commonly constructed by randomly distorting the same image tw

Zhicheng Guo, Sijie Cheng, Hao Wang, Shihao Liang

Large Language Models (LLMs) have witnessed remarkable advancements in recent years, prompting the exploration of tool learning, which integrates LLMs with external tools to address diverse real-world challenges. Assessing the capability of LLMs to utilise tools necessitates large-scale and stable benchmarks. However, previous works relied on either hand-cra

Caitlyn Flexer, Alexander A. Mushtukov

The accretion flow within the magnetospheric radius of bright X-ray pulsars can form an optically thick envelope, concealing the central neutron star from the distant observer. Most photons are emitted at the surface of a neutron star and leave the system after multiple reflections by the accretion material covering the magnetosphere. Reflections cause momen

Zixuan Li, Yutao Zeng, Yuxin Zuo, Weicheng Ren

In this paper, we propose KnowCoder, a Large Language Model (LLM) to conduct Universal Information Extraction (UIE) via code generation. KnowCoder aims to develop a kind of unified schema representation that LLMs can easily understand and an effective learning framework that encourages LLMs to follow schemas and extract structured knowledge accurately. To ac

Yajie Zhang, Qiang Du, Zuoqiang Shi

In this paper, we consider a new nonlocal approximation to the linear Stokes system with periodic boundary conditions in two and three dimensional spaces . A relaxation term is added to the equation of nonlocal divergence free equation, which is reminiscent to the relaxation of local Stokes equation with small artificial compressibility. Our analysis shows t

Hilario D. Boggiano, Lin Nan, Gustavo Grinblat, Stefan A. Maier

Plasmonic nanoantennas have proven to be efficient transducers of electromagnetic to mechanical energy and vice versa. The sudden thermal expansion of these structures after an ultrafast optical pulsed excitation leads to the emission of hypersonic acoustic waves to the supporting substrate, which can be detected by another antenna that acts as a high-sensit

Vincenzo Mottola, Antonio Corbo Esposito, Gianpaolo Piscitelli, Antonello Tamburrino

In this paper we present a first non-iterative imaging method for nonlinear materials, based on Monotonicity Principle. Specifically, we deal with the inverse obstacle problem, where the aim is to retrieve a nonlinear anomaly embedded in linear known background. The Monotonicity Principle (MP) is a general property for various class of PDEs, that has recentl

Wei Shen, Xiaoying Zhang, Yuanshun Yao, Rui Zheng

Reinforcement learning from human feedback (RLHF) is the mainstream paradigm used to align large language models (LLMs) with human preferences. Yet existing RLHF heavily relies on accurate and informative reward models, which are vulnerable and sensitive to noise from various sources, e.g. human labeling errors, making the pipeline fragile. In this work, we

Eduardo M. G. Vila, Eric C. Kerrigan, Paul Bruce

This paper presents a pseudo-spectral method for Dynamic Optimization Problems (DOPs) that allows for tight polynomial bounds to be achieved via flexible sub-intervals. The proposed method not only rigorously enforces inequality constraints, but also allows for a lower cost in comparison with non-flexible discretizations. Two examples are provided to demonst

Meir Yossef Levi, Guy Gilboa

We propose a fast and simple explainable AI (XAI) method for point cloud data. It computes pointwise importance with respect to a trained network downstream task. This allows better understanding of the network properties, which is imperative for safety-critical applications. In addition to debugging and visualization, our low computational complexity facili

Jiawei Zhang, Jiahe Li, Lei Huang, Xiaohan Yu

With advancements in domain generalized stereo matching networks, models pre-trained on synthetic data demonstrate strong robustness to unseen domains. However, few studies have investigated the robustness after fine-tuning them in real-world scenarios, during which the domain generalization ability can be seriously degraded. In this paper, we explore fine-t

Motoki Omura, Takayuki Osa, Yusuke Mukuta, Tatsuya Harada

In deep reinforcement learning, estimating the value function to evaluate the quality of states and actions is essential. The value function is often trained using the least squares method, which implicitly assumes a Gaussian error distribution. However, a recent study suggested that the error distribution for training the value function is often skewed beca

Jean-Marcel Rax

The observed CP violation in neutral kaons experiments is explained as an interplay between two oscillations in the earth's Schwarzschild geometry: (i) mixing associated with second order weak coupling and (ii) quark's zitterbewegung. This violation is in fact a CPT violation with T conservation rather than a T violation with CPT conservation. The Hermitian

Aidan Backus, Ng Ze-An

Let $\Gamma$ be a closed subset of a complete Riemannian manifold $M$ of dimension $\geq 2$, let $f: M \to N$ be a Lipschitz map to a complete Riemannian manifold $N$, and let $\psi$ be a continuous function which dominates the local Lipschitz constant of $f$. We construct a Lipschitz map which agress with $f$ on $\Gamma$ and whose local Lipschitz constant i

Chao-Qiang Geng, Chia-Wei Liu, Xiao Yu, Ao-Wen Zhou

The scalar mesons are established for a long time, but their nature is still an open question. In this paper, we investigate the potential of categorizing their $SU(3)_f$ representations via $J/\psi\to SV$ and $\gamma S$, offering a criterion that may illuminate this issue. Here, $S$ ($V$) denotes scalar (vector) mesons. Using the $SU(3)_f$ symmetry with the

Shahaf Arica, Or Rubin, Sapir Gershov, Shlomi Laufer

In this paper, we introduce VoteCut, an innovative method for unsupervised object discovery that leverages feature representations from multiple self-supervised models. VoteCut employs normalized-cut based graph partitioning, clustering and a pixel voting approach. Additionally, We present CuVLER (Cut-Vote-and-LEaRn), a zero-shot model, trained using pseudo-

P. Liu, D. Wu, T. X. Hu, D. W. Yuan

Electromagnetic turbulence and ion kinetics in counter-streaming plasmas hold great significance in laboratory astrophysics, such as turbulence field amplification and particle energization. Here, we quantitatively demonstrate for the first time how electromagnetic turbulence affects ion kinetics under achievable laboratory conditions (millimeter-scale inter

Weike Yu

In this paper, we investigate a Kazdan-Warner problem on compact K\"ahler surfaces, which corresponds to prescribing sign-changing Chern scalar curvatures, and establish a Chen-Li type existence theorem on compact K\"ahler surfaces when the candidate curvature function is of negative average. Moreover, we give an alternative proof of Ding-Liu's theorem [Tran

Jacob Golomb, Isaac Legred, Katerina Chatziioannou, Adrian Abac

Compact objects observed via gravitational waves are classified as black holes or neutron stars primarily based on their inferred mass with respect to stellar evolution expectations. However, astrophysical expectations for the lowest mass range, $\lesssim 1.2 \,M_\odot$, are uncertain. If such low-mass compact objects exist, ground-based gravitational wave d

Abraham Loeb

In a recent preprint, Fernando et al. (2024) used public data from infrasound stations to constrain the localization of the fireball of the CNEOS 2014-01-08 (IM1) bolide. The analysis inferred a 90-percent-confidence ellipse with semi-minor and semi-major axes of 186 and 388 km, respectively. This large error ellipse includes the much better localization box

Gabriel Santana, Maira Valera-López, Nelson Merentes

This research aimed to introduce the concept of harmonically m-concave set-valued functions, which is obtained from the combination of two definitions: harmonically m-concave functions and set-valued functions. In this work some properties and characteristics are developed, as well as a Kuhn type theorem and Bernstein-Doetcsh type result for such functions.

Frédéric Marcadon, Andrej Prša

Several hundreds of thousands of eclipsing binaries (EBs) are expected to be detected in the Transiting Exoplanet Survey Satellite (TESS) full frame images (FFIs). This represents a significant increase in the number of EBs available for eclipse timing variation studies. In this paper, we investigate the feasibility of performing precise eclipse timing of TE