February 2024 arXiv papers — page 30

Zhi-Lei She, An-Ke Lei, Yu-Liang Yan, Dai-Mei Zhou

The production of exotic hadron $\rm X(3872)$ in $pp$ collisions at $\sqrt{s}=2.76\,\mathrm{TeV}$ is investigated by the parton and hadron cascade model PACIAE in this work. In the simulation the final partonic state (quark matter, QM) and the final hadronic state (hadron matter, HM) are continuously processed and recorded. The $\rm X(3872)$ compact tetraqua

Oleksandr Kurbatov, Dmytro Zakharov, Anton Levochko, Kyrylo Riabov

Taprootized Atomic Swaps is an extension for Atomic Swaps that enables the untraceability of transactions in a particular swap. Based on Schnorr signatures, Taproot technology, and zero-knowledge proofs, the taprootized atomic swaps hide swap transactions between regular payments. We propose several implementation options: single-transaction protocol, multip

Bidur Khanal, Prashant Shrestha, Sanskar Amgain, Bishesh Khanal

Label noise in medical image classification datasets significantly hampers the training of supervised deep learning methods, undermining their generalizability. The test performance of a model tends to decrease as the label noise rate increases. Over recent years, several methods have been proposed to mitigate the impact of label noise in medical image class

Tzu-Hsuan Hsu, Joshua Campbell, Jack Kramer, Sinwoo Cho

In this work, we demonstrate a C-band shear-horizontal surface acoustic wave (SH-SAW) resonator with high electromechanical coupling (kt2) of 22% and a quality factor (Q) of 565 based on a thin-film lithium niobate (LN) on silicon carbide (SiC) platform, featuring an excellent figure-of-merit (FoM = kt2*Q ) of 124 at 6.5 GHz, the highest FoM reported in this

Christina Giannoula, Peiming Yang, Ivan Fernandez, Jiacheng Yang

Graph Neural Networks (GNNs) are emerging ML models to analyze graph-structure data. Graph Neural Network (GNN) execution involves both compute-intensive and memory-intensive kernels, the latter dominates the total time, being significantly bottlenecked by data movement between memory and processors. Processing-In-Memory (PIM) systems can alleviate this data

Sumin Huang

Let $\mathcal F\subseteq\binom{[n]}{k}$ be a $k$-uniform family, and let $P_m(\mathcal F)$ denote the number of ordered pairs $(A,B)\in\mathcal F\times\mathcal F$ with $|A\cap B|=m$. We study the pairwise intersection profile $(P_0(\mathcal F),P_1(\mathcal F),\ldots,P_k(\mathcal F))$ of intersecting families. We prove that for every $1\leq m\leq k$, if $n\ge

Hong Chen, Fang Fang, Xianbin Wang

Semantic communications offer the potential to alleviate communication loads by exchanging meaningful information. However, semantic extraction (SE) is computationally intensive, posing challenges for resource-constrained Internet of Things (IoT) devices. To address this, leveraging computing resources at the edge servers (ESs) is essential. ESs can support

Felipe H. S. da Silva, João B. Fernandes, Idalmis M. Sardina, Tiago Barros

Full Waveform Inversion (FWI) is a widely used method in seismic data processing, capable of estimating models that represent the characteristics of the geological layers of the subsurface. Because it works with a massive amount of data, the execution of this method requires much time and computational resources. Techniques such as FWI adapt well to parallel

Zohar Schwartzman-Nowik, Liran Shirizly, Haggai Landa

We analyze the performance of a quantum error correction code subject to physically motivated noise modeled by a Lindblad master equation. We consider dissipative and coherent single-qubit terms and two-qubit crosstalk, studying how different approximations of the noise capture the success rate of a code. Focusing on the five-qubit code and adapting it to pa

Hiroki Furuta, Gouki Minegishi, Yusuke Iwasawa, Yutaka Matsuo

Grokking has been actively explored to reveal the mystery of delayed generalization and identifying interpretable representations and algorithms inside the grokked models is a suggestive hint to understanding its mechanism. Grokking on modular addition has been known to implement Fourier representation and its calculation circuits with trigonometric identiti

Ronan Perry, Snigdha Panigrahi, Jacob Bien, Daniela Witten

Principal component analysis (PCA) is a longstanding and well-studied approach for dimension reduction. It rests upon the assumption that the underlying signal in the data has low rank, and thus can be well-summarized using a small number of dimensions. The output of PCA is typically represented using a scree plot, which displays the proportion of variance e

Svetlana Boyarchenko, Sergei Levendorskiĭ

This paper is a supplement to our recent paper ``Alternative models for FX, arbitrage opportunities and efficient pricing of double barrier options in L\'evy models". We introduce the class of regime-switching L\'evy models with memory, which take into account the evolution of the stochastic parameters in the past. This generalization of the class of L\'evy

Chenyang Huang, Yang Yu, Peter R. King, Bin Cheng

The impact response of rubble-pile asteroids is essential for both elucidating their formation and evolution history and evaluating the efficacy of impact defense strategies. Although state-of-the-art numerical simulations have allowed for the replication of many macroscopic impact characteristics consistent with observations, the understanding of dynamics a

Yuanjie Yu, Shiyun Dai, Qiang Wu, Yu Long

Optical-fiber-based polarization scramblers can reduce the impact of polarization sensitive performance of various optical fiber systems. Here, we propose a simple and efficient polarization scrambler based on an all optical Mach-Zehnder structure by combining polarization beam splitter and amplified fiber ring. To totally decoherence one polarization splitt

André H. A. Malavazi, Borhan Ahmadi, Paweł Mazurek, Antonio Mandarino

Navigating the intricacies of thermal management at the quantum scale is a challenge in the pursuit of advanced nanoscale technologies. To this extent, theoretical frameworks introducing minimal models mirroring the functionality of electronic current amplifiers and transistors, for instance, have been proposed. Different architectures of the subsystems comp

Qifeng Li, Xiaosong Jia, Shaobo Wang, Junchi Yan

Real-world autonomous driving (AD) especially urban driving involves many corner cases. The lately released AD simulator CARLA v2 adds 39 common events in the driving scene, and provide more quasi-realistic testbed compared to CARLA v1. It poses new challenge to the community and so far no literature has reported any success on the new scenarios in V2 as exi

Guilhem Semerjian

We consider the additive version of the matrix denoising problem, where a random symmetric matrix $S$ of size $n$ has to be inferred from the observation of $Y=S+Z$, with $Z$ an independent random matrix modeling a noise. For prior distributions of $S$ and $Z$ that are invariant under conjugation by orthogonal matrices we determine, using results from first

Yanqi Zong, Zhengrong Cui, Luqi Lin, Sihao Wang

Stereotactic body radiation therapy (SBRT) refers to focusing high-energy rays in three-dimensional space on the tumor lesion area, reducing the dose received by surrounding normal tissues, which can effectively improve the local control rate of the tumor and reduce the probability of complications. With the comprehensive development of medical imaging, radi

Huijie Lv, Xiao Wang, Yuansen Zhang, Caishuang Huang

Adversarial misuse, particularly through `jailbreaking' that circumvents a model's safety and ethical protocols, poses a significant challenge for Large Language Models (LLMs). This paper delves into the mechanisms behind such successful attacks, introducing a hypothesis for the safety mechanism of aligned LLMs: intent security recognition followed by respon

T. W. Morris, M. Rakitin, A. Islegen-Wojdyla, Y. Du

Autonomous methods to align beamlines can decrease the amount of time spent on diagnostics, and also uncover better global optima leading to better beam quality. The alignment of these beamlines is a high-dimensional, expensive-to-sample optimization problem involving the simultaneous treatment of many optical elements with correlated and nonlinear dynamics.

Kaiser Pister, Dhruba Jyoti Paul, Patrick Brophy, Ishan Joshi

The rise of capabilities expressed by large language models has been quickly followed by the integration of the same complex systems into application level logic. Algorithms, programs, systems, and companies are built around structured prompting to black box models where the majority of the design and implementation lies in capturing and quantifying the `age

Yuichi Ito, Tatsuya Yoshida, Akifumi Nakayama

Atmospheric escape is crucial to understand the evolution of planets in and out of the Solar system and to interpret atmospheric observations. While hydrodynamic escape simulations have been actively developed incorporating detailed processes such as UV heating, chemical reactions, and radiative cooling, the radiative cooling by molecules has been treated as

Naixu Guo, Zhan Yu, Matthew Choi, Yizhan Han

Powerful generative artificial intelligence from large language models (LLMs) harnesses extensive computational resources for inference. In this work, we investigate the transformer architecture, a key component of these models, under the lens of fault-tolerant quantum computing. We develop quantum subroutines to construct the building blocks in the transfor

Sumedh Rasal, E. J. Hauer

Large Language Models (LLMs) have demonstrated remarkable capabilities in solving various tasks, yet they often struggle with comprehensively addressing complex and vague problems. Existing approaches, including multi-agent LLM systems, offer solutions to certain challenges but still require manual setup and lack scalability. To address this gap, we propose

Xiao Ling, Paul Brooks

In this work, we propose an optimization framework for estimating a sparse robust one-dimensional subspace. Our objective is to minimize both the representation error and the penalty, in terms of the l1-norm criterion. Given that the problem is NP-hard, we introduce a linear relaxation-based approach. Additionally, we present a novel fitting procedure, utili

Lízia Branco, Rui Dilão

We explore the relationship between sodium (Na$^+$) and potassium (K$^+$) gating variables in the 4-dimensional (4D) Hodgkin-Huxley (HH) electrophysiology model, and reducing its complexity by deriving new 3D and 2D models that maintain the dynamic properties of the original model. The new 3D and 2D models are grounded in the relationship $h \simeq c(I) - n$

Kellen Kanarios, Qining Zhang, Lei Ying

In this paper, we study a best arm identification problem with dual objects. In addition to the classic reward, each arm is associated with a cost distribution and the goal is to identify the largest reward arm using the minimum expected cost. We call it \emph{Cost Aware Best Arm Identification} (CABAI), which captures the separation of testing and implement

M. Atzori Corona, M. Cadeddu, N. Cargioli, F. Dordei

Despite being neutral particles, neutrinos can have a non-zero charge radius, which represents the only non-null neutrino electromagnetic property in the standard model theory. Its value can be predicted with high accuracy and its effect is usually accounted for through the definition of a radiative correction affecting the neutrino couplings to electrons an

Shao-Ping Li

Even after dark matter chemically freezes out in the early universe, electromagnetic cascades from dark matter annihilation can still perturb the background photon spectrum when the universe temperature cools down to 0.5 keV. We revisit the CMB spectrum distortions caused by $s$-wave dark matter annihilation under the updated Planck data and the future CMB s

Orhan Donmez

Modeling of the shock cone formed around a static, hairy Horndeski black hole with Bondi-Hoyle-Lyttleton (BHL) accretion has been conducted. We model the dynamical changes of the shock cone resulting from the interaction of matter with the Horndeski black hole. The effects of the scalar hair, the black hole rotation parameter, and the impacts of the asymptot

G. Leidi, R. Andrassy, W. Barsukow, J. Higl

High-order Godunov methods for gas dynamics have become a standard tool for simulating different classes of astrophysical flows. Their accuracy is mostly determined by the spatial interpolant used to reconstruct the pair of Riemann states at cell interfaces and by the Riemann solver that computes the interface fluxes. In most Godunov-type methods, these two

Liangxin Liu, Xuebo Liu, Derek F. Wong, Dongfang Li

Instruction tuning (IT) is crucial to tailoring large language models (LLMs) towards human-centric interactions. Recent advancements have shown that the careful selection of a small, high-quality subset of IT data can significantly enhance the performance of LLMs. Despite this, common approaches often rely on additional models or data, which increases costs

José Manuel Fernández Vilaboa, Ramón González Rodríguez, Brais Ramos Pérez

The present article is devoted to studying the categorical relationships between the categories of Hopf trusses, weak twisted post-Hopf algebras, introduced by Wang (2023), and weak twisted relative Rota-Baxter operators. The latter objects are a generalisation of the relative Rota-Baxter operators defined by Li-Sheng-Tang (2024), where the Rota-Baxter condi

Seibi Kobara, Alireza Rafiei, Masoud Nateghi, Selen Bozkurt

Breast cancer is a significant public health concern and is the leading cause of cancer-related deaths among women. Despite advances in breast cancer treatments, medication non-adherence remains a major problem. As electronic health records do not typically capture patient-reported outcomes that may reveal information about medication-related experiences, so

Fernando De Terán, Froilán M. Dopico, Vadym Koval, Patryk Pagacz

Bundles of matrix polynomials are sets of matrix polynomials with the same size and grade and the same eigenstructure up to the specific values of the eigenvalues. It is known that the closure of the bundle of a pencil $L$ (namely, a matrix polynomial of grade $1$), denoted by $\mathcal{B}(L)$, is the union of $\mathcal{B}(L)$ itself with a finite number of

Nikolai Leonenko, Leonardo Maini, Ivan Nourdin, Francesca Pistolato

Fix an integer $p\geq 1$ and refer to it as the number of growing domains. For each $i\in\{1,\ldots,p\}$, fix a compact subset $D_i\subseteq\mathbb R^{d_i}$ where $d_1,\ldots,d_p\ge 1$. Let $d= d_1+\dots+d_{p}$ be the total underlying dimension. Consider a continuous, stationary, centered Gaussian field $B=(B_x)_{x\in \mathbb R^d}$ with unit variance. Finall

Itay Etelis, Avi Rosenfeld, Abraham Itzhak Weinberg, David Sarne

In recent years, transformer models have revolutionized Natural Language Processing (NLP), achieving exceptional results across various tasks, including Sentiment Analysis (SA). As such, current state-of-the-art approaches for SA predominantly rely on transformer models alone, achieving impressive accuracy levels on benchmark datasets. In this paper, we show

Yunze Hu, Xuru Yang, Kangjie Zhou, Qinghang Liu

Large-scale swarm robotic systems consisting of numerous cooperative agents show considerable promise for performing autonomous tasks across various sectors. Nonetheless, traditional motion planning approaches often face a trade-off between scalability and solution quality due to the exponential growth of the joint state space of robots. In response, this wo

Huisheng Zhong, Bin B. Ren, Bo Ma, Chen Xie

Context.Spatially-resoved cicrumstellar disk spectrum and composition can provide valuable insights into the bulk composition of forming planets, as well as the mineralogical signatures that emerge during and after planet formation. Aims. We aim to systemically extract the RX~J1604.3-213010 (J1604 hereafter) protoplanetary disk in high-contrast imaging obser

Yue Tan, Xuejie Liu, Xiaoyun Chen, Yuheng Wu

Since the quark model was put forward, theoretical researchers have always attached great importance to the study of hidden color channels (including color octets and diquark structure). Because of the influence of color Van der waals forces, the hidden color channel itself has strong attraction, which provides a dynamic mechanism for the formation of resona

Anchun Gui, Jian Li, Yong Dai, Nan Du

Tool-augmented large language models (LLMs) are attracting widespread attention when accessing up-to-date knowledge and alleviating hallucination issues. Nowadays, advanced closed-source LLMs (e.g., ChatGPT) have demonstrated surprising tool-usage capabilities through prompting and in-context learning techniques. To empower the capabilities of open-source LL

J. D. Zipfel, P. Bevington, L. Wright, W. Chalupczak

Atom spin sensors occupy a prominent position in the scenario of quantum technology, as they can combine precise measurements with appealing miniature packages which are crucial for many applications. In this work, we report on the design and realization of miniature silicon-wafer cells, with a double-chamber configuration and integrated heaters. The cells a

Qiwei Peng, Yekun Chai, Xuhong Li

Large language models (LLMs) have made significant progress in generating codes from textual prompts. However, existing benchmarks have mainly concentrated on translating English prompts to multilingual codes or have been constrained to very limited natural languages (NLs). These benchmarks have overlooked the vast landscape of massively multilingual NL to m

Santiago Pereda-Fernández

This paper addresses computational challenges in estimating Quantile Regression with Selection (QRS). The estimation of the parameters that model self-selection requires the estimation of the entire quantile process several times. Moreover, closed-form expressions of the asymptotic variance are too cumbersome, making the bootstrap more convenient to perform

Alisa Haukisalmi, Daniel Paz Ramos, Matti Raasakka, Andrea Marchesin

Fault-tolerant quantum computers promise the simulation of complex quantum systems beyond the reach of classical computation. In contrast, current noisy intermediate-scale quantum (NISQ) devices are constrained by hardware noise. Consequently, quantum simulation methods remain limited in their near-term applicability. Two prominent techniques addressing thes

Luca Banszerus, Katrin Hecker, Lin Wang, Samuel Möller

The valley degree of freedom in 2D semiconductors, such as gapped bilayer graphene (BLG) and transition metal dichalcogenides, is a promising carrier of quantum information in the emerging field of valleytronics. While valley dynamics have been extensively studied for moderate band gap 2D~semiconductors using optical spectroscopy techniques, very little is k

Xuru Yang, Yunze Hu, Han Gao, Kang Ding

Swarm robotics has garnered significant attention due to its ability to accomplish elaborate and synchronized tasks. Existing methodologies for motion planning of swarm robotic systems mainly encounter difficulties in scalability and safety guarantee. To address these limitations, we propose a Risk-aware swarm mOtion planner using conditional ValuE at Risk (

Adrien Bazoge, Emmanuel Morin, Beatrice Daille, Pierre-Antoine Gourraud

Recently, pretrained language models based on BERT have been introduced for the French biomedical domain. Although these models have achieved state-of-the-art results on biomedical and clinical NLP tasks, they are constrained by a limited input sequence length of 512 tokens, which poses challenges when applied to clinical notes. In this paper, we present a c

Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten

Noise-contrastive estimation (NCE) is a popular method for estimating unnormalised probabilistic models, such as energy-based models, which are effective for modelling complex data distributions. Unlike classical maximum likelihood (ML) estimation that relies on importance sampling (resulting in ML-IS) or MCMC (resulting in contrastive divergence, CD), NCE u

Valeria Garcia, Cole M. Smith, Daniel R. Chavas, Thaddeus D. Komacek

Tropical cyclones occur over the Earth's tropical oceans, with characteristic genesis regions and tracks tied to the warm ocean surface that provides energy to sustain these storms. The study of tropical cyclogenesis and evolution on Earth has led to the development of environmental favorability metrics that predict the strength of potential storms from the

Sauro Succi, Claudio Sanavio, Riccardo Scatamacchia, Carlo De Falco

We discuss the Carleman approach to the quantum simulation of classical fluids, as applied to i) Lattice Boltzmann (CLB), ii) Navier-Stokes (CNS) and iii) Grad (CG) formulations of fluid dynamics. CLB shows excellent convergence properties, but it is plagued by nonlocality which results in an exponential depth of the corresponding circuit with the number of

Zijun Zhao, Maria-Andreea Filip, Alex J W Thom

The multi-reference coupled-cluster Monte Carlo (MR-CCMC) algorithm is a determinant-based quantum Monte Carlo (QMC) algorithm that is conceptually similar to Full Configuration Interaction QMC (FCIQMC). It has been shown to offer a balanced treatment of both static and dynamic correlation while retaining polynomial scaling, although application to large sys

Temitope Akinboyewa, Huan Ning, M. Naser Lessani, Zhenlong Li

Information on the depth of floodwater is crucial for rapid mapping of areas affected by floods. However, previous approaches for estimating floodwater depth, including field surveys, remote sensing, and machine learning techniques, can be time-consuming and resource-intensive. This paper presents an automated and fast approach for estimating floodwater dept

Gordian Edenhofer, Philipp Frank, Jakob Roth, Reimar H. Leike

Imaging is the process of transforming noisy, incomplete data into a space that humans can interpret. NIFTy is a Bayesian framework for imaging and has already successfully been applied to many fields in astrophysics. Previous design decisions held the performance and the development of methods in NIFTy back. We present a rewrite of NIFTy, coined NIFTy.re, w

Philipp Korablev

The main subject of the paper is the pentagon relation. This relation can be expressed in different ways. We start with the natural geometric form of the pentagon relation. Then we express it in algebraic form as a family of equations with a set of linear maps as variables. Next, we derive several equivalent forms of the algebraic pentagon relation. These fo

Hanbing Liu, Jingge Wang, Xuan Zhang, Ye Guo

Addressing the large distribution gap between training and testing data has long been a challenge in machine learning, giving rise to fields such as transfer learning and domain adaptation. Recently, Continuous Domain Adaptation (CDA) has emerged as an effective technique, closing this gap by utilizing a series of intermediate domains. This paper contributes

Pablo Banon Perez, Bjoern Malte Schaefer, Maarten DeKieviet

The intention of our paper is to provide a pedagogical application of geometric algebra to a particularly well-investigated system: We formulate the geometric and dynamical properties of Friedmann-Robertson-Walker spacetimes within the language of geometric algebra and re-derive the Friedmann-equations as the central cosmological equations. Through the geome

Chen Xing, Guillaume Aulanier, Xin Cheng, Chun Xia

Understanding the early evolution of coronal mass ejections (CMEs), in particular their initiation, is the key to forecasting solar eruptions and induced disastrous space weather. Although many initiation mechanisms have been proposed, a full understanding of CME initiation, which is identified as a slow rise of CME progenitors in kinematics before the impul

Jelle J. Oostveen, Daniël Paulusma, Erik Jan van Leeuwen

The intensively studied Diameter problem is to find the diameter of a given connected graph. We investigate, for the first time in a structured manner, the complexity of Diameter for H-free graphs, that is, graphs that do not contain a fixed graph H as an induced subgraph. We first show that if H is not a linear forest with small components, then Diameter ca

J. Bishop, G. V. Rogachev, S. Ahn, M. Barbui

Background: Cluster states in $^{13}$N are extremely difficult to measure due to the unavailability of $^{9}$B+$\alpha$ elastic scattering data. Purpose: Using $\beta$-delayed charged-particle spectroscopy of $^{13}$O, clustered states in $^{13}$N can be populated and measured in the 3$\alpha$+p decay channel. Method: One-at-a-time implantation/decay of $^{1

Andrea Appel, Bart Vlaar

Let $\mathfrak{g}$ be a symmetrizable Kac-Moody algebra, $U_q(\mathfrak{g})$ its quantum group, and $U_q(\mathfrak{k}) \subset U_q(\mathfrak{g})$ a quantum symmetric pair subalgebra determined by a Lie algebra automorphism $\theta$. We introduce a category $W_\theta$ of weight $U_q(\mathfrak{k})$-modules, which is acted on by the category of weight $U_q(\mat

Amir Zaimbashi, Maria Sabrina Greco, Fulvio Gini

Integrated passive radar (IPR) can be regarded as next generation passive radar technology, which aims to integrate communication and radar systems. Unlike conventional passive radar, which does not prioritize communication-centric radar technology, IPR technology places a higher priority on incorporating specific radar constraints to develop waveforms that

Bowen Dong, Guanglei Yang, Wangmeng Zuo, Lei Zhang

In this paper, we delve into the realm of vision transformers for continual semantic segmentation, a problem that has not been sufficiently explored in previous literature. Empirical investigations on the adaptation of existing frameworks to vanilla ViT reveal that incorporating visual adapters into ViTs or fine-tuning ViTs with distillation terms is advanta

M. Wiśniewski, J. Łuczka, J. Spiechowicz

Recent pioneering experiments on non-Markovian dynamics done e.g. for active matter have demonstrated that our theoretical understanding of this challenging yet hot topic is rather incomplete and there is a wealth of phenomena still awaiting discovery. It is related to the fact that typically for simplification the Markovian approximation is employed and as

Peter Burton, Christopher J. Eagle, Alec Fox, Isaac Goldbring

We establish a computable version of Gelfand Duality. Under this computable duality, computably compact presentations of metrizable spaces uniformly effectively correspond to computable presentations of unital commutative $C^*$ algebras.

Alex Zhuang, Ge Zhang, Tianyu Zheng, Xinrun Du

Structured data sources, such as tables, graphs, and databases, are ubiquitous knowledge sources. Despite the demonstrated capabilities of large language models (LLMs) on plain text, their proficiency in interpreting and utilizing structured data remains limited. Our investigation reveals a notable deficiency in LLMs' ability to process structured data, e.g.

Franck Michel, Fabien Gandon

Over the last 70 years, we, humans, have created an economic market where attention is being captured and turned into money thanks to advertising. During the last two decades, leveraging research in psychology, sociology, neuroscience and other domains, Web platforms have brought the process of capturing attention to an unprecedented scale. With the initial

Joshua Lampert, Hendrik Ranocha

We use the general framework of summation-by-parts operators to construct conservative, energy-stable, and well-balanced semidiscretizations of two different nonlinear systems of dispersive shallow water equations with varying bathymetry: (i) a variant of the coupled Benjamin-Bona-Mahony (BBM) equations and (ii) a recently proposed model by Sv\"ard and Kalis

Carlos G. Correa, Thomas L. Griffiths, Nathaniel D. Daw

Typical models of learning assume incremental estimation of continuously-varying decision variables like expected rewards. However, this class of models fails to capture more idiosyncratic, discrete heuristics and strategies that people and animals appear to exhibit. Despite recent advances in strategy discovery using tools like recurrent networks that gener

Qinyu Luo, Yining Ye, Shihao Liang, Zhong Zhang

Generative models have demonstrated considerable potential in software engineering, particularly in tasks such as code generation and debugging. However, their utilization in the domain of code documentation generation remains underexplored. To this end, we introduce RepoAgent, a large language model powered open-source framework aimed at proactively generat

Álvaro Buendía, Jose A. Sánchez-Gil, Vincenzo Giannini, William L. Barnes

Strong coupling between light and molecular matter is currently attracting interest both in chemistry and physics, in the fast-growing field of molecular polaritonics. The large near-field enhancement of the electric field of plasmonic surfaces and their high tunability make arrays of metallic nanoparticles an interesting platform to achieve and control stro

Michael Bonfert, Thomas Muender, Ryan P. McMahan, Frank Steinicke

Fidelity describes how closely a replication resembles the original. It can be helpful to analyze how faithful interactions in virtual reality (VR) are to a reference interaction. In prior research, fidelity has been restricted to the simulation of reality - also called realism. Our definition includes other reference interactions, such as superpowers or fic

Yuyang Du, Kexin Chen, Yue Zhan, Chang Han Low

Visual question answering (VQA) is crucial for promoting surgical education. In practice, the needs of trainees are constantly evolving, such as learning more surgical types, adapting to different robots, and learning new surgical instruments and techniques for various surgeries. However, patient data privacy often restricts the availability of old data when

Zhen Chen, Qing Xu, Xinyu Liu, Yixuan Yuan

In digital pathology, precise nuclei segmentation is pivotal yet challenged by the diversity of tissue types, staining protocols, and imaging conditions. Recently, the segment anything model (SAM) revealed overwhelming performance in natural scenarios and impressive adaptation to medical imaging. Despite these advantages, the reliance of labor-intensive manu

Åsa Hirvonen, Joni Puljujärvi

We define a version of the Ehrenfeucht-Fra\"iss\'e game in the setting of metric model theory and continuous first-order logic and show that the second player having a winning strategy in a game of length $n$ exactly corresponds to being elementarily equivalent up to quantifier rank $n$. We then demonstrate the usefulness of the game with some examples. Fina

Tong Wang, Jian Huang, Shuangge Ma

Deep networks are increasingly applied to a wide variety of data, including data with high-dimensional predictors. In such analysis, variable selection can be needed along with estimation/model building. Many of the existing deep network studies that incorporate variable selection have been limited to methodological and numerical developments. In this study,

Debopriyo Banerjee, Krothapalli Sreenivasa Rao, Shamik Sural, Niloy Ganguly

Over the past few years, automation of outfit composition has gained much attention from the research community. Most of the existing outfit recommendation systems focus on pairwise item compatibility prediction (using visual and text features) to score an outfit combination having several items, followed by recommendation of top-n outfits or a capsule wardr

Nikola Slepickova Kasalkovova, Veronika Juricova, Dominik Fajstavr, Bara Frydlova

We focused on polydimethylsiloxane (PDMS) as a substrate for replication, micropatterning, and construction of biologically active surfaces. The novelty of this study is based on the combina-tion of argon plasma exposure of micropatterned PDMS scaffold, where the plasma served as a strong tool for subsequent grafting of collagen coating and their application

Erika Magnusson, Aaron Fitzpatrick, Stefan Knecht, Martin Rahm

The near-term utility of quantum computers is hindered by hardware constraints in the form of noise. One path to achieving noise resilience in hybrid quantum algorithms is to decrease the required circuit depth -- the number of applied gates -- to solve a given problem. This work demonstrates how to reduce circuit depth by combining the transcorrelated (TC)

Riccardo Cominotti, Chiara Rogora, Alessandro Zenesini, Giacomo Lamporesi

Ultracold atomic spin mixtures develop rich and intriguing magnetic properties when an external radiation coherently couples different spin states. In particular, the coupled mixture may acquire a critical behavior when the spin interactions equal the coupling energy. However, atomic mixtures generally feature a relatively high sensitivity to magnetic fields

Luca Barbieri, Bernardo Camajori Tedeschini, Mattia Brambilla, Monica Nicoli

Accurate positioning is known to be a fundamental requirement for the deployment of Connected Automated Vehicles (CAVs). To meet this need, a new emerging trend is represented by cooperative methods where vehicles fuse information coming from navigation and imaging sensors via Vehicle-to-Everything (V2X) communications for joint positioning and environmental

Ephrance Eunice Namugenyi, David Tugume, Augustine Kigwana, Benjamin Rukundo

There is an immediate need for creative ways to improve resource ef iciency given the dynamic nature of robust sensor networks and their increasing reliance on data-driven approaches.One key challenge faced is ef iciently managing large data files collected from sensor networks for example optimal beehive image and video data files. We of er a revolutionary

Pavel Blinov, Konstantin Egorov, Ivan Sviridov, Nikolay Ivanov

Building an intelligent and efficient medical assistant is still a challenging AI problem. The major limitation comes from the data modality scarceness, which reduces comprehensive patient perception. This demo paper presents the GigaPevt, the first multimodal medical assistant that combines the dialog capabilities of large language models with specialized m

C. Larrodera, M. Temmer

This study covers a thorough statistical investigation of the evolution of interplanetary coronal mass ejections (ICMEs) with and without sheaths, through a broad heliocentric distance and temporal range. The analysis treats the sheath and magnetic obstacle (MO) separately to gain more insight about their physical properties. In detail, we aim to unravel dif

Karim Derrick

The Belief Rule Base (BRB) system that adopts a hybrid approach integrating the precision of expert systems with the adaptability of data-driven models. Characterized by its use of if-then rules to accommodate various types of uncertainty through belief degrees, BRB adeptly handles fuzziness, randomness, and ignorance. This semi-quantitative tool excels in p

Karim Derrick

In this paper we explore the challenges of measuring sentiment in relation to Environmental, Social and Governance (ESG) social media. ESG has grown in importance in recent years with a surge in interest from the financial sector and the performance of many businesses has become based in part on their ESG related reputations. The use of sentiment analysis to

Chenxiaoji Ling, Bangzheng Sun, Cheng Cheng, Nan Li

We present COSBO-7, a strong millimeter (mm) source known for more than sixteen years but was just revealed its near-to-mid-IR counterpart by the James Webb Space Telescope (JWST). The precise pin-pointing by the Atacama Large Millimeter Array (ALMA) on the exquisite NIRCam and MIRI images show that it is a background source gravitationally lensed by a singl

G. Catanzaro, A. Frasca, J. Alonso-Santiago, C. Colombo

In this paper, we present the results of a comprehensive study of six eclipsing binaries whose components are confirmed or suspected Am stars. By combining long-term high-resolution CAOS spectroscopy and TESS photometry we have been able to accurately obtain the orbital parameters of each system as well as the atmospheric parameters of its components. We per

T. M. Kamsma, R. van Roij, C. Spitoni

In pursuit of neuromorphic (brain-inspired) devices, memristors (memory-resistors) have emerged as effective components for emulating neuronal circuitry. Here we formally define a class of Simple Volatile Memristors (SVMs) based on a simple conductance equation of motion from which we build a simple mathematical theory on the dynamics of isolated SVMs and SV

Shanmugasundaram Gnanasekaran, Alessandro Columbu, Rafael Díaz Fuentes, Nagarajan Nithyadevi

This paper investigates the properties of classical solutions to a class of chemotaxis systems that model interactions between tumor and immune cells. Our focus is on examining the global existence and explosion of such solutions in bounded domains of $\mathbb{R}^n$, $n\geq3$, under Neumann boundary conditions. We distinguish between two scenarios: one where

Selinay Sude Binici, Cemsinan Deliduman, Furkan Şakir Dilsiz

James Webb Space Telescope's (JWST) observations since its launch have shown us that there could be very massive and very large galaxies, as well as massive quasars very early in the history of the universe, conflicting expectations of the $\Lambda$CDM model. This so-called ''impossibly early galaxy problem'' requires too rapid star formation in the earliest

Jean Pierre Allamaa, Panagiotis Patrinos, Herman Van der Auweraer, Tong Duy Son

In this work, we focus on the challenge of transferring an autonomous driving controller from simulation to the real world (i.e. Sim2Real). We propose a data-efficient method for online and on-the-fly adaptation of parametrizable control architectures such that the target closed-loop performance is optimized while accounting for uncertainties as model mismat

Li Tuobang

Due to the complexity of order statistics, the finite sample behaviour of robust statistics is generally not analytically solvable. While the Monte Carlo method can provide approximate solutions, its convergence rate is typically very slow, making the computational cost to achieve the desired accuracy unaffordable for ordinary users. In this paper, we propos

Kevin Tirta Wijaya, Navid Ansari, Hans-Peter Seidel, Vahid Babaei

Data-driven generation of molecules with desired properties, also known as inverse molecular design (IMD), has attracted significant attention in recent years. Despite the significant progress in the accuracy and diversity of solutions, existing IMD methods lag behind in terms of trustworthiness. The root issue is that the design process of these methods is

Cosme G. Ayani, M. Bosnar, F. Calleja, Andrés Pinar Solé

This study delves into the intriguing properties of 1H/1T-TaS$_2$ van der Waals heterostructure, focusing on the transparency of the 1H layer to the Charge Density Wave of the underlying 1T layer. Despite the sizable interlayer separation and metallic nature of the 1H layer, positive bias voltages result in a pronounced superposition of the 1T charge density

Sascha Kurz

It has been known since the 1970's that the difference of the non-zero weights of a projective $\mathbb{F}_q$-linear two-weight has to be a power of the characteristic of the underlying field. Here we study non-projective two-weight codes and e.g.\ show the same result under mild extra conditions. For small dimensions we give exhaustive enumerations of the f

Daniel Leite, Alisson Silva, Gabriella Casalino, Arnab Sharma

We introduce a modified incremental learning algorithm for evolving Granular Neural Network Classifiers (eGNN-C+). We use double-boundary hyper-boxes to represent granules, and customize the adaptation procedures to enhance the robustness of outer boxes for data coverage and noise suppression, while ensuring that inner boxes remain flexible to capture drifts

Leila M. Calcaferro, Paulina Sowicka, Murat Uzundag, Alejandro H. Córsico

Significant advances have been achieved through the latest improvements in the photometric observations accomplished by the recent space missions, substantially boosting the study of pulsating stars via asteroseismology. The TESS mission has already proven to be of relevance for pulsating white dwarf and pre-white dwarf stars. We report a detailed asteroseis

Haoning Wu, Hanwei Zhu, Zicheng Zhang, Erli Zhang

Comparative settings (e.g. pairwise choice, listwise ranking) have been adopted by a wide range of subjective studies for image quality assessment (IQA), as it inherently standardizes the evaluation criteria across different observers and offer more clear-cut responses. In this work, we extend the edge of emerging large multi-modality models (LMMs) to furthe

Shang Wu, Bin Wang

Multi-person pose estimation (MPPE), which aims to locate the key points for all persons in the frames, is an active research branch of computer vision. Variable human poses and complex scenes make MPPE dependent on local details and global structures; their absence may cause key point feature misalignment. In this case, high-order spatial interactions that