February 2024 arXiv papers — page 60

Stefan Meinecke, Kathy Lüdge

Efficient simulation of the timing jitter in passively mode-locking lasers is key to their numerical investigation and optimization. We introduce a method based on the pulse-period fluctuation auto-correlation function and compare it against established methods with respect to their estimate error. Potential improvements of the computational cost by about tw

Han Tang, Shikun Feng, Bicheng Lin, Yuyan Ni

In recent years, self-supervised learning has emerged as a powerful tool to harness abundant unlabelled data for representation learning and has been broadly adopted in diverse areas. However, when applied to molecular representation learning (MRL), prevailing techniques such as masked sub-unit reconstruction often fall short, due to the high degree of freed

Martynas Pocius, Wen Yan, Dean C. Barratt, Mark Emberton

In this paper we propose a reinforcement learning based weakly supervised system for localisation. We train a controller function to localise regions of interest within an image by introducing a novel reward definition that utilises non-binarised classification probability, generated by a pre-trained binary classifier which classifies object presence in imag

Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei

Deep generative models (DGMs) have demonstrated great success across various domains, particularly in generating texts, images, and videos using models trained from offline data. Similarly, data-driven decision-making and robotic control also necessitate learning a generator function from the offline data to serve as the strategy or policy. In this case, app

Lianghu Guo, Tianli Tao, Xinyi Cai, Zihao Zhu

Early infancy is a rapid and dynamic neurodevelopmental period for behavior and neurocognition. Longitudinal magnetic resonance imaging (MRI) is an effective tool to investigate such a crucial stage by capturing the developmental trajectories of the brain structures. However, longitudinal MRI acquisition always meets a serious data-missing problem due to par

Stephen Theriault

Let M be a simply-connected closed Poincare Duality complex of dimension n. Then M is obtained by attaching a cell of highest dimension to its (n-1)-skeleton M'. Conditions are given for when the skeletal inclusion i:M' --> M has the property that the based loops on i has a right homotopy inverse. This is an integral version of the rational statement that su

Y. -Y. Li, G. -S. Zhou

The Adams operators on a Hopf algebra $H$ are the convolution powers of the identity map of $H$. They are also called Hopf powers or Sweedler powers. It is a natural family of operators on $H$ that contains the antipode. We study the linear properties of the Adams operators when $H=\bigoplus_{m\in \mathbb{N}} H_m$ is connected graded. The main result is that

Philipp Mackensen, Paul Staat, Stefan Roth, Aydin Sezgin

Wireless communication infrastructure is a cornerstone of modern digital society, yet it remains vulnerable to the persistent threat of wireless jamming. Attackers can easily create radio interference to overshadow legitimate signals, leading to denial of service. The broadcast nature of radio signal propagation makes such attacks possible in the first place

Olga Kozachek, Nikolay Nikolaev, Olga Slita, Alexey Bobtsov

In this paper an adaptive state observer and parameter identification algorithm for a linear time-varying system are developed under condition that the state matrix of the system contains unknown time-varying parameters of a known form. The state vector is observed using only output and input measurements without identification of the unknown parameters. Whe

Dongti Zhang, Patricio Peralta-Braz, Chun Tung Chou, Elena Atroshchenko

The current battery-powered fault detection system for vibration monitoring has a rather limited lifetime. This is because the high-frequency sampling (typically tens of kilo-Hertz) required for vibration monitoring results in high energy consumption in both the analog-to-digital (ADC) converter and wireless transmissions. This paper proposes a new fault det

Siddharth D Jaiswal, Ankit Kr. Verma, Animesh Mukherjee

AI based Face Recognition Systems (FRSs) are now widely distributed and deployed as MLaaS solutions all over the world, moreso since the COVID-19 pandemic for tasks ranging from validating individuals' faces while buying SIM cards to surveillance of citizens. Extensive biases have been reported against marginalized groups in these systems and have led to hig

Zefang Li, Huai Zhang, Guanqi Li, Jiangteng Guo

Realizing room-temperature magnetic skyrmions in two-dimensional van der Waals ferromagnets offers unparalleled prospects for future spintronic applications. However, due to the intrinsic spin fluctuations that suppress atomic long-range magnetic order and the inherent inversion crystal symmetry that excludes the presence of the Dzyaloshinskii-Moriya interac

An Zhang, Wenchang Ma, Pengbo Wei, Leheng Sheng

Graph neural networks (GNNs) have shown impressive performance in recommender systems, particularly in collaborative filtering (CF). The key lies in aggregating neighborhood information on a user-item interaction graph to enhance user/item representations. However, we have discovered that this aggregation mechanism comes with a drawback, which amplifies bias

Linus Seelinger, Anne Reinarz, Mikkel B. Lykkegaard, Robert Akers

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulat

Sukanya Maji, Supantha Pandit, Sanjib Sadhu

We study the Generalized Red-Blue Annulus Cover problem for two sets of points, red ($R$) and blue ($B$), where each point $p \in R\cup B$ is associated with a positive penalty ${\cal P}(p)$. The red points have non-covering penalties, and the blue points have covering penalties. The objective is to compute an annulus (either a rectangular or a circular) $\c

Filippo Fecit

We compute the counterterms necessary for the renormalization of the one-loop effective action of massive gravity from a worldline perspective. This is achieved by employing the recently proposed massive $\mathcal{N}=4$ spinning particle model to describe the propagation of the massive graviton on those backgrounds that solve the Einstein equations without c

Yasushi Esaki, Akihiro Nakamura, Keisuke Kawano, Ryoko Tokuhisa

Classification models based on deep neural networks (DNNs) must be calibrated to measure the reliability of predictions. Some recent calibration methods have employed a probabilistic model on the probability simplex. However, these calibration methods cannot preserve the accuracy of pre-trained models, even those with a high classification accuracy. We propo

Tian Lan, Wenwei Zhang, Chen Xu, Heyan Huang

Critique ability, i.e., the capability of Large Language Models (LLMs) to identify and rectify flaws in responses, is crucial for their applications in self-improvement and scalable oversight. While numerous studies have been proposed to evaluate critique ability of LLMs, their comprehensiveness and reliability are still limited. To overcome this problem, we

Sifei Li, Yuxin Zhang, Fan Tang, Chongyang Ma

With the development of diffusion models, text-guided image style transfer has demonstrated high-quality controllable synthesis results. However, the utilization of text for diverse music style transfer poses significant challenges, primarily due to the limited availability of matched audio-text datasets. Music, being an abstract and complex art form, exhibi

Bradley J. Kavanagh, Theophanes K. Karydas, Gianfranco Bertone, Pierfrancesco Di Cintio

Future gravitational wave observatories can probe dark matter by detecting the dephasing in the waveform of binary black hole mergers induced by dark matter overdensities. Such a detection hinges on the accurate modelling of the dynamical friction, induced by dark matter on the secondary compact object in intermediate and extreme mass ratio inspirals. In thi

Stefan Meinecke, Kathy Lüdge

Passively mode-locked semiconductor disk lasers have received tremendous attention from both science and industry. Their relatively inexpensive production combined with excellent pulse performance and great emission wavelength flexibility make them suitable laser candidates for applications ranging from frequency comb tomography to spectroscopy. However, due

Martin Habedank

Various astrophysical observations point towards an as-of-yet unexplained, mainly gravitationally interacting type of matter. If this matter, called Dark Matter, is an elementary particle, it could be produced in particle collisions at the Large Hadron Collider. Given its weak interaction with ordinary matter, however, it would not be directly observable wit

Fujia Lu, Qianying Hu, Yang Xu, Hongyi Yu

We theoretically investigated the coupling between the exciton internal and center-of-mass motions in monolayer transition metal dichalcogenides subjected to a periodic electrostatic potential. The coupling leads to the emergence of multiple absorption peaks in the exciton spectrum which are the hybridizations of 1s, 2s and 2p$\pm$ Rydberg states with differ

Zheheng Luo, Qianqian Xie, Sophia Ananiadou

Factual inconsistency with source documents in automatically generated summaries can lead to misinformation or pose risks. Existing factual consistency (FC) metrics are constrained by their performance, efficiency, and explainability. Recent advances in Large language models (LLMs) have demonstrated remarkable potential in text evaluation but their effective

Vishnu Pulloor Kuttanikkad, Martin Puschmann, Rajesh Narayanan, Thomas Vojta

We investigate the critical behavior and the dynamics of the amplitude (Higgs) mode close to the superfluid-insulator quantum phase transition in an amorphous system (i.e., a system subject to topological randomness). In particular, we map the two-dimensional Bose-Hubbard Hamiltonian defined on a random Voronoi-Delaunay lattice onto a (2+1)-dimensional layer

Luca Crupi, Alessandro Giusti, Daniele Palossi

Relative drone-to-drone localization is a fundamental building block for any swarm operations. We address this task in the context of miniaturized nano-drones, i.e., 10cm in diameter, which show an ever-growing interest due to novel use cases enabled by their reduced form factor. The price for their versatility comes with limited onboard resources, i.e., sen

Rustam Latypov, Yannic Maus, Shreyas Pai, Jara Uitto

Classic symmetry-breaking problems on graphs have gained a lot of attention in models of modern parallel computation. The Adaptive Massively Parallel Computation (AMPC) is a model that captures the central challenges in data center computations. Chang et al. [PODC'2019] gave an extremely fast, constant time, algorithm for the $(\Delta + 1)$-coloring problem,

Akash Kundu

A significant hurdle in the noisy intermediate-scale quantum (NISQ) era is identifying functional quantum circuits. These circuits must also adhere to the constraints imposed by current quantum hardware limitations. Variational quantum algorithms (VQAs), a class of quantum-classical optimization algorithms, were developed to address these challenges in the c

Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu

Large context window is a desirable feature in large language models (LLMs). However, due to high fine-tuning costs, scarcity of long texts, and catastrophic values introduced by new token positions, current extended context windows are limited to around 128k tokens. This paper introduces LongRoPE that, for the first time, extends the context window of pre-t

Aleksei Kychkin, Georgios C. Chasparis

The flexibility in electricity consumption and production in communities of residential buildings, including those with renewable energy sources and energy storage (a.k.a., prosumers), can effectively be utilized through the advancement of short-term demand response mechanisms. It is known that flexibility can further be increased if demand response is perfo

H. Yoshimochi, R. Takagi, J. Ju, N. D. Khanh

Topological swirling spin textures, such as skyrmions and merons, have recently attracted much attention as a unique building block for high-density magnetic information devices. The controlled transformation among different types of such quasi-particles is an important challenge, while it was previously achieved only in a few non-centrosymmetric systems cha

Qian Zhao, Hao Qian, Ziqi Liu, Gong-Duo Zhang

Recommendation systems are widely used in e-commerce websites and online platforms to address information overload. However, existing systems primarily rely on historical data and user feedback, making it difficult to capture user intent transitions. Recently, Knowledge Base (KB)-based models are proposed to incorporate expert knowledge, but it struggle to a

J. Healy, W. J. G. de Blok, F. M. Maccagni, P. Amram

The existing reservoirs of neutral atomic hydrogen gas (H$\,$I) in galaxies are insufficient to have maintained the observed levels of star formation without some kind of replenishment. {This refuelling of the H$\,$I reservoirs} is likely to occur at column densities an order of magnitude lower than previous observational limits (N$_{\rm{H\,I}\, limit} \sim

Maximilian Engel, Peter K. Friz, Tal Orenshtein

The combination of functional limit theorems with the pathwise analysis of deterministic and stochastic differential equations has proven to be a powerful approach to the analysis of fast-slow systems. In a multivariate setting, this requires rough path ideas, as already suggested in the seminal work [Melbourne-Stuart, Nonlinearity, 24, 2011]. This initiated

Niklas Vaara, Pekka Sangi, Miguel Bordallo López, Janne Heikkilä

Ray tracing is a deterministic method that produces propagation paths between a transmitter and a receiver. The simulation accuracy is significantly influenced by the environment details. One way to capture the environment with great precision is the utilization of depth sensors and cameras. Such reconstructed environment is in the form of a point cloud. How

Ali Alshumrani, Nathan Clarke, Bogdan Ghita

The modern digital world is highly heterogeneous, encompassing a wide variety of communications, devices, and services. This interconnectedness generates, synchronises, stores, and presents digital information in multidimensional, complex formats, often fragmented across multiple sources. When linked to misuse, this digital information becomes vital digital

Huichen Zhang, Yoann Prado, Rodolphe Alchaar, Henri Lehouelleur

Transferring the nanocrystals (NCs) from the laboratory environment toward practical applications has raised new challenges. In the case of NCs for display and lightning, the focus was on reduced Auger recombination and maintaining luminescence at high temperatures. When it comes to infrared sensing, narrow band gap materials are required and HgTe appears as

Danilo Numeroso

The development of artificial intelligence systems with advanced reasoning capabilities represents a persistent and long-standing research question. Traditionally, the primary strategy to address this challenge involved the adoption of symbolic approaches, where knowledge was explicitly represented by means of symbols and explicitly programmed rules. However

Moritz Möller, Gargi Nirmal, Dario Fabietti, Quintus Stierstorfer

Generative AI is expected to have a vast, positive impact on education; however, at present, this potential has not yet been demonstrated at scale at university level. In this study, we present first evidence that generative AI can increase the speed of learning substantially in university students. We tested whether using the AI-powered teaching assistant S

Huaxiang Lü, Xiangchan Zhu

We prove existence of infinitely many stationary solutions as well as ergodic stationary solutions for the stochastic Navier-Stokes equations on $\mathbb{T}^2$ \begin{align*} \dif u+\div(u\otimes u)\dif t+\nabla p\dif t&=\Delta u\dif t + (-\Delta)^{\fa/2}\dif B_t,\ \ \ \ \div u=0,\notag \end{align*} driven by derivative of space-time white noise, where $\fa\

Phuwadon Chunaksorn, Ratchaphat Nakarachinda, Pitayuth Wongjun

We investigate the possibility of describing the thermal system with different temperatures for a black hole with multiple horizons. The black hole with two horizons such as Schwarzschild-de Sitter black hole corresponds to two thermal systems with generically different temperatures. Then, it is not suitable to describe these systems with equilibrium thermod

Guozheng Li, Wenjun Ke, Peng Wang, Zijie Xu

The in-context learning (ICL) for relational triple extraction (RTE) has achieved promising performance, but still encounters two key challenges: (1) how to design effective prompts and (2) how to select proper demonstrations. Existing methods, however, fail to address these challenges appropriately. On the one hand, they usually recast RTE task to text-to-t

Luming Lu, Jiyuan An, Yujie Wang, Liner yang

Natural Language Processing (NLP) technologies have revolutionized the way we interact with information systems, with a significant focus on converting natural language queries into formal query languages such as SQL. However, less emphasis has been placed on the Corpus Query Language (CQL), a critical tool for linguistic research and detailed analysis withi

Sergey Titov, Konstantin Grotov, Ashwin Prasad S. Venkatesh

In this paper, we outline potential ways for the further development of computational notebooks in Integrated Development Environments (IDEs). We discuss notebooks integration with IDEs, focusing on three main areas: facilitating experimentation, adding collaborative features, and improving code comprehension. We propose that better support of notebooks will

Thomas Melvin, Ben Shipway, Nigel Wood, Tommaso Benacchio

The reformulation of the Met Office's dynamical core for weather and climate prediction previously described by the authors is extended to spherical domains using a cubed-sphere mesh. This paper updates the semi-implicit mixed finite-element formulation to be suitable for spherical domains. In particular the finite-volume transport scheme is extended to take

Xudong Ling, Chaorong Li, Fengqing Qin, Peng Yang

Diffusion models are widely used in image generation because they can generate high-quality and realistic samples. This is in contrast to generative adversarial networks (GANs) and variational autoencoders (VAEs), which have some limitations in terms of image quality.We introduce the diffusion model to the precipitation forecasting task and propose a short-t

Fan Xu, Tao Cai

In this study, we conducted a linear instability analysis of penetrative magneto-convection in rapidly rotating Boussinesq flows within tilted f-planes, under the influence of a uniform background magnetic field. We integrated wave theory and convection theory to elucidate the penetration dynamics in rotating magneto-convection. Our findings suggest that eff

Felix Tamke, Florian Linß, Leopold Kuttner, Udo Buscher

This paper presents a new branch-and-cut algorithm based on infeasible path elimination for the three-dimensional loading capacitated vehicle routing problem (3L-CVRP) with different loading problem variants. We show that a previously infeasible route can become feasible by adding a new customer if support constraints are enabled in the loading subproblem an

Tianyi Bai, Jean-François Delmas, Yueyun Hu

The branching capacity has been introduced by [Zhu 2016] as the limit of the hitting probability of a symmetric branching random walk in $\mathbb Z^d$, $d\ge 5$. Similarly, we define the Brownian snake capacity in $\mathbb R^d$, as the scaling limit of the hitting probability by the Brownian snake starting from afar. Then, we prove our main result on the vag

R S. Stroud, A. Al-Saffar, M. Carter, M P. Moody

Atom probe tomography is commonly used to study solute clustering and precipitation in materials. However, standard techniques, such as the density based spatial clustering applications with noise (DBSCAN) perform poorly with respect to small clusters of less than 25 atoms. This is a fundamental limitation of density-based clustering techniques due to the us

Omer Hamdi, Stanislav Burov, Eli Barkai

In biological, glassy, and active systems, various tracers exhibit Laplace-like, i.e., exponential, spreading of the diffusing packet of particles. The limitations of the central limit theorem in fully capturing the behaviors of such diffusive processes, especially in the tails, have been studied using the continuous time random walk model. For cases when th

Simon Ellinger, Thomas Müller-Gronbach, Larisa Yaroslavtseva

We study strong approximation of scalar additive noise driven stochastic differential equations (SDEs) at time point $1$ in the case that the drift coefficient is bounded and has Sobolev regularity $s\in(0,1)$. Recently, it has been shown in [arXiv:2101.12185v2 (2022)] that for such SDEs the equidistant Euler approximation achieves an $L^2$-error rate of at

Yuheng Chen, Pengfei Cao, Yubo Chen, Yining Wang

Large language models (LLMs) store extensive factual knowledge, but the underlying mechanisms remain unclear. Previous research suggests that factual knowledge is stored within multi-layer perceptron weights, and some storage units exhibit degeneracy, referred to as Degenerate Knowledge Neurons (DKNs). Despite the novelty and unique properties of this concep

Luca Di Luzio, Alfredo Walter Mario Guerrera, Xavier Ponce Díaz, Stefano Rigolin

In this talk the ALP production from radiative quarkonium decays is presented. To this purpose, the relevant cross-section is computed from a $d=5$ effective Lagrangian containing simultaneous ALP couplings to $b(c)$-quarks and photons. The interplay between resonant and non-resonant contributions is shown to be relevant for experiments operating at $\sqrt{s

Kihong Kim, Haneol Lee, Jihye Park, Seyeon Kim

Generating high-quality videos that synthesize desired realistic content is a challenging task due to their intricate high-dimensionality and complexity of videos. Several recent diffusion-based methods have shown comparable performance by compressing videos to a lower-dimensional latent space, using traditional video autoencoder architecture. However, such

Daniel Beaglehole, Peter Súkeník, Marco Mondelli, Mikhail Belkin

Deep Neural Collapse (DNC) refers to the surprisingly rigid structure of the data representations in the final layers of Deep Neural Networks (DNNs). Though the phenomenon has been measured in a variety of settings, its emergence is typically explained via data-agnostic approaches, such as the unconstrained features model. In this work, we introduce a data-d

Allan Tameshtit

We utilize a mass independent Klein-Gordon equation that is first order in a variable that plays the role of time, the approach taken in parametric time formulations. Using concepts from semigroup evolution, we examine the sign of a noisy Feynman propagator in a quantum field theory, namely, scalar electrodynamics.

Otmar Ertl

This work introduces ExaLogLog, a new data structure for approximate distinct counting, which has the same practical properties as the popular HyperLogLog algorithm. It is commutative, idempotent, mergeable, reducible, has a constant-time insert operation, and supports distinct counts up to the exa-scale. At the same time, as theoretically derived and experi

Saul Santos, Vlad Niculae, Daniel McNamee, Andre F. T. Martins

Modern Hopfield networks have enjoyed recent interest due to their connection to attention in transformers. Our paper provides a unified framework for sparse Hopfield networks by establishing a link with Fenchel-Young losses. The result is a new family of Hopfield-Fenchel-Young energies whose update rules are end-to-end differentiable sparse transformations.

Zechen Bai, Peng Chen, Xiaolan Peng, Lu Liu

Animating virtual characters has always been a fundamental research problem in virtual reality (VR). Facial animations play a crucial role as they effectively convey emotions and attitudes of virtual humans. However, creating such facial animations can be challenging, as current methods often involve utilization of expensive motion capture devices or signifi

Nik Vaessen, David A. van Leeuwen

Foundation models in speech are often trained using many GPUs, which implicitly leads to large effective batch sizes. In this paper we study the effect of batch size on pre-training, both in terms of statistics that can be monitored during training, and in the effect on the performance of a downstream fine-tuning task. By using batch sizes varying from 87.5

S M Rafiuddin, Mohammed Rakib, Sadia Kamal, Arunkumar Bagavathi

Aspect-Based Sentiment Analysis (ABSA) is a fine-grained linguistics problem that entails the extraction of multifaceted aspects, opinions, and sentiments from the given text. Both standalone and compound ABSA tasks have been extensively used in the literature to examine the nuanced information present in online reviews and social media posts. Current ABSA m

Ji-peng Lv, Zi-han Yu, Zuo-tang Liang, Qun Wang

The observation of the vector meson's global spin alignment by the STAR Collaboration reveals that strong spin correlations may exist for quarks and antiquarks in relativistic heavy-ion collisions in the normal direction of the reaction plane. We propose a systematic method to describe such correlations in the quark matter. The correlations can be classified

Weilin Zhao, Yuxiang Huang, Xu Han, Wang Xu

Speculative decoding is a widely used method that accelerates the generation process of large language models (LLMs) with no compromise in model performance. It achieves this goal by using an existing smaller model for drafting and then employing the target LLM to verify the draft in a low-cost parallel manner. Under such a drafting-verification framework, d

Esra'a Alhenawi, Ruba Abu Khurma, Pedro A. Castillo, Maribel G. Arenas

Classifying text is a method for categorizing documents into pre-established groups. Text documents must be prepared and represented in a way that is appropriate for the algorithms used for data mining prior to classification. As a result, a number of term weighting strategies have been created in the literature to enhance text categorization algorithms' fun

Werner Brannath, Liane Kluge, Martin Scharpenberg

Simultaneous confidence intervals (SCIs) that are compatible with a given closed test procedure are often non-informative. More precisely, for a one-sided null hypothesis, the bound of the SCI can stick to the border of the null hypothesis, irrespective of how far the point estimate deviates from the null hypothesis. This has been illustrated for the Bonferr

Xinrong Zhang, Yingfa Chen, Shengding Hu, Zihang Xu

Processing and reasoning over long contexts is crucial for many practical applications of Large Language Models (LLMs), such as document comprehension and agent construction. Despite recent strides in making LLMs process contexts with more than 100K tokens, there is currently a lack of a standardized benchmark to evaluate this long-context capability. Existi

Xiaoyan Yu, Tongxu Luo, Yifan Wei, Fangyu Lei

Large Language Models (LLMs) have revolutionized open-domain dialogue agents but encounter challenges in multi-character role-playing (MCRP) scenarios. To address the issue, we present Neeko, an innovative framework designed for efficient multiple characters imitation. Unlike existing methods, Neeko employs a dynamic low-rank adapter (LoRA) strategy, enablin

Dario Cavallaro, Ken-ichi Kawarabayashi, Stephan Kreutzer

Disjoint paths problems are among the most prominent problems in combinatorial optimization. The edge- as well as vertex-disjoint paths problem, are NP-complete on directed and undirected graphs. But on undirected graphs, Robertson and Seymour (Graph Minors XIII) developed an algorithm for the vertex- and the edge-disjoint paths problem that runs in cubic ti

Amanat Kafizov, Ahmed Elzanaty, Mohamed-Slim Alouini

The limited modulation bandwidth of the light emitting diodes (LEDs) presents a challenge in the development of practical high-data-rate visible light communication (VLC) systems. In this paper, a novel adaptive coded probabilistic shaping (PS)-based nonorthogonal multiple access (NOMA) scheme is proposed to improve spectral efficiency (SE) of VLC systems in

Fatma A. Hashim, Reham R. Mostafa, Ruba Abu Khurma, Raneem Qaddoura

Sea Horse Optimizer (SHO) is a noteworthy metaheuristic algorithm that emulates various intelligent behaviors exhibited by sea horses, encompassing feeding patterns, male reproductive strategies, and intricate movement patterns. To mimic the nuanced locomotion of sea horses, SHO integrates the logarithmic helical equation and Levy flight, effectively incorpo

Hengchuang Yin, Zhonghui Gu, Fanhao Wang, Yiparemu Abuduhaibaier

Large language models (LLMs) such as ChatGPT have gained considerable interest across diverse research communities. Their notable ability for text completion and generation has inaugurated a novel paradigm for language-interfaced problem solving. However, the potential and efficacy of these models in bioinformatics remain incompletely explored. In this work,

Marley Young

We consider semigroup dynamical systems defined by several monnomials over a number field $K$. We prove a finiteness result for preperiodic points of such systems which are $S$-integral with respect to a non-preperiodic point $\beta$, which is uniform as $\beta$ varies over number fields of bounded degree. This generalises results of Baker, Ih and Rumely, wh

Marley Young

We classify the pairs of polynomials $f,g \in \mathbb{C}[X]$ having orbits satisfying infinitely many multiplicative dependence relations, extending a result of Ghioca, Tucker and Zieve. Moreover, we show that given $f_1,\ldots, f_n$ from a certain class of polynomials with integer coefficients, the vectors of indices $(m_1,\ldots,m_n)$ such that $f_1^{m_1}(

Seungyoon Choi, Wonjoong Kim, Sungwon Kim, Yeonjun In

We investigate the replay buffer in rehearsal-based approaches for graph continual learning (GCL) methods. Existing rehearsal-based GCL methods select the most representative nodes for each class and store them in a replay buffer for later use in training subsequent tasks. However, we discovered that considering only the class representativeness of each repl

Justus Bogner, Sebastian Kotstein, Daniel Abajirov, Timothy Ernst

RESTful APIs based on HTTP are one of the most important ways to make data and functionality available to applications and software services. However, the quality of the API design strongly impacts API understandability and usability, and many rules have been specified for this. While we have evidence for the effectiveness of many design rules, it is still d

Vamshi Krishna Bonagiri, Sreeram Vennam, Priyanshul Govil, Ponnurangam Kumaraguru

Despite recent advancements showcasing the impressive capabilities of Large Language Models (LLMs) in conversational systems, we show that even state-of-the-art LLMs are morally inconsistent in their generations, questioning their reliability (and trustworthiness in general). Prior works in LLM evaluation focus on developing ground-truth data to measure accu

K. S. Park, Y. D. Kim, K. M. Bang, H. K Park

The Center for Underground Physics of the Institute for Basic Science (IBS) in Korea has been planning the construction of a deep underground laboratory since 2013 to search for extremely rare interactions such as dark matter and neutrinos. In September 2022, a new underground laboratory, Yemilab, was finally completed in Jeongseon, Gangwon Province, with a

Erwin Luesink, Arnout Franken, Sagy Ephrati, Bernard Geurts

We present a geometric derivation of the quasi-geostrophic equations on the sphere, starting from the rotating shallow water equations. We utilise perturbation series methods in vorticity and divergence variables. The derivation employs asymptotic analysis techniques, leading to a global quasi-geostrophic potential vorticity model on the sphere without appro

Anthony Hastir, Birgit Jacob, Hans Zwart

Linear-Quadratic optimal controls are computed for a class of boundary controlled, boundary observed hyperbolic infinite-dimensional systems, which may be viewed as networks of waves. The main results of this manuscript consist in converting the infinite-dimensional continuous-time systems into infinite-dimensional discrete-time systems for which the operato

Raphaël Lachièze-Rey, D. Yogeshwaran

We examine optimal matchings or transport between two stationary random measures. It covers allocation from the Lebesgue measure to a point process and matching a point process to a regular (shifted) lattice. The main focus of the article is the impact of hyperuniformity(reduced variance fluctuations in point processes) to optimal transport: in dimension 2,

Marley Young

Given polynomials $f_1,\ldots,f_n$ in $m$ variables with integral coefficients, we give upper bounds for the number of integral $m$-tuples $\mathbf{u}_1,\ldots, \mathbf{u}_n$ of bounded height such that $f_1(\mathbf{u}_1), \ldots, f_n(\mathbf{u}_n)$ are multiplicatively dependent. We also prove, under certain conditions, a finiteness result for $\mathbf{u} \

Alexander Arno Weber, Klaudia Thellmann, Jan Ebert, Nicolas Flores-Herr

The adaption of multilingual pre-trained LLMs into eloquent and helpful assistants is essential to facilitate their use across different language regions. In that spirit, we are the first to conduct an extensive study of the performance of multilingual models instruction-tuned on different language compositions on parallel instruction-tuning benchmarks acros

Mitali Sisodia, Manoj Kumar Mandal, Binayak S. Choudhury

The way a new type of state called a hybrid state, which contains more than one degree of freedom, is used in many practical applications of quantum communication tasks with lesser amount of resources. Similarly, our aim is here to perform multi-quantum communication tasks in a protocol to approach quantum information in multipurpose and multi-directional. W

Cristina Erbeia, Francesca Scala, Camilla Colombo

The impact of formation flying on interferometry is growing over the years for the potential performance it could offer. However, it is still an open field, and many studies are still required. This article presents the basic principles behind interferometry focusing first on a single array and secondly on a formation of satellites. A sensitivity analysis is

Natalia Korsakova, Stanislav Babak, Michael L. Katz, Nikolaos Karnesis

The future space based gravitational wave detector LISA (Laser Interferometer Space Antenna) will observe millions of Galactic binaries constantly present in the data stream. A small fraction of this population (of the order of several thousand) will be individually resolved. One of the challenging tasks from the data analysis point of view will be to estima

Mathilde Raynal, Carmela Troncoso

Collaborative Machine Learning (CML) allows participants to jointly train a machine learning model while keeping their training data private. In many scenarios where CML is seen as the solution to privacy issues, such as health-related applications, safety is also a primary concern. To ensure that CML processes produce models that output correct and reliable

L. Di Lucchio, G. Modanese

We show how the combined use of the free software packages networkX and NetLogo allows to implement quickly and with large flexibility agent-based network simulations of the classical Bass diffusion model and of its extensions and modifications. In addition to the standard internal graph implementations available in NetLogo (random, Barabasi-Albert-1 and sma

Daniel Schug, Tyler J. Kovach, M. A. Wolfe, Jared Benson

The rapid development of quantum dot (QD) devices for quantum computing has necessitated more efficient and automated methods for device characterization and tuning. This work demonstrates the feasibility and advantages of applying explainable machine learning techniques to the analysis of quantum dot measurements, paving the way for further advances in auto

Alessandro Pelizzola, Marco Pretti

We study a totally asymmetric simple exclusion process with open boundary conditions and local resetting at the injection node. We investigate the stationary state of the model, using both mean-field approximation and kinetic Monte Carlo simulations, and identify three regimes, depending on the way the resetting rate scales with the lattice size. The most in

Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Hiroshi Murase

Zero-shot Panoptic Segmentation (ZPS) aims to recognize foreground instances and background stuff without images containing unseen categories in training. Due to the visual data sparsity and the difficulty of generalizing from seen to unseen categories, this task remains challenging. To better generalize to unseen classes, we propose Conditional tOken aligNm

Justus Bogner, Pawel Wójcik, Olaf Zimmermann

Microservices expose their functionality via remote Application Programming Interfaces (APIs), e.g., based on HTTP or asynchronous messaging technology. To solve recurring problems in this design space, Microservice API Patterns (MAPs) have emerged to capture the collective experience of the API design community. At present, there is a lack of empirical evid

Erik Burman, Lauri Oksanen, Ziyao Zhao

We consider finite element approximations of unique continuation problems subject to elliptic equations in the case where the normal derivative of the exact solution is known to reside in some finite dimensional space. To give quantitative error estimates we prove Lipschitz stability of the unique continuation problem in the global H1-norm. This stability is

Ritam Basu, Anirban Ganguly, Souparna Nath, Onkar Parrikar

For any state in a $D$-dimensional Hilbert space with a choice of basis, one can define a discrete version of the Wigner function -- a quasi-probability distribution which represents the state on a discrete phase space. The Wigner function can, in general, take on negative values, and the amount of negativity in the Wigner function has an operational meaning

Yuanze Ji, Bobo Li, Jun Zhou, Fei Li

Multimodal Named Entity Recognition (MNER) is a pivotal task designed to extract named entities from text with the support of pertinent images. Nonetheless, a notable paucity of data for Chinese MNER has considerably impeded the progress of this natural language processing task within the Chinese domain. Consequently, in this study, we compile a Chinese Mult

Jiahua Wan, Hong Ren, Zhiyuan Yu, Zhenkun Zhang

This paper studies a comprehensive framework for reconfigurable intelligent surface (RIS)-assisted integrated communication, sensing, and computation (ICSC) systems with a User-centric focus. The study encompasses two scenarios: the general multi-user equipment (UE) scenario and the simplified single-UE scenario. To satisfy the critical need for time-efficie

Fabrizio Cinque, Enzo Orsingher

We study Cauchy problems of fractional differential equations in both space and time variables by expressing the solution in terms of ``stochastic composition" of the solutions to two simpler problems. These Cauchy sub-problems respectively concern the space and the time differential operator involved in the main equation. We provide some probabilistic and p

Aparajita Dasgupta, Shyam Swarup Mondal, Michael Ruzhansky, Abhilash Tushir

This article aims to investigate the semi-classical analog of the general Caputo-type diffusion equation with time-dependent diffusion coefficient associated with the discrete Schr\"{o}dinger operator, $\mathcal{H}_{\hbar,V}:=-\hbar^{-2}\mathcal{L}_{\hbar}+V$ on the lattice $\hbar\mathbb{Z}^{n},$ where $V$ is a non-negative multiplication operator and $\math

Simon Allais, Pierre-Alexandre Arlove, Sheila Sandon

Using Givental's non-linear Maslov index we define a sequence of spectral selectors on the universal cover of the identity component of the contactomorphism group of any lens space. As applications, we prove for lens spaces with equal weights that the standard Reeb flow is a geodesic for the discriminant and oscillation norms, and we define for general lens

Maurizio Vergari, Tanja Kojić, Nicole Stefanie Bertges, Francesco Vona

Nowadays, Augmented Reality (AR) is available on almost all smartphones creating some exciting interaction opportunities but also challenges. For example, already after the famous AR app Pokemon GO was released in July 2016, numerous accidents related to the use of the app were reported by users. At the same time, the spread of AR can be noticed in the touri