December 2024 arXiv papers — page 134

Alejandro Campoy-Nieves, Antonio Manjavacas, Javier Jiménez-Raboso, Miguel Molina-Solana

Simulation has become a crucial tool for Building Energy Optimization (BEO) as it enables the evaluation of different design and control strategies at a low cost. Machine Learning (ML) algorithms can leverage large-scale simulations to learn optimal control from vast amounts of data without supervision, particularly under the Reinforcement Learning (RL) para

Nikil Roashan Selvam, Amil Merchant, Stefano Ermon

In diffusion models, samples are generated through an iterative refinement process, requiring hundreds of sequential model evaluations. Several recent methods have introduced approximations (fewer discretization steps or distillation) to trade off speed at the cost of sample quality. In contrast, we introduce Self-Refining Diffusion Samplers (SRDS) that reta

Nishat Raihan, Christian Newman, Marcos Zampieri

Large language models (LLMs) have demonstrated remarkable capabilities across various NLP tasks and have recently expanded their impact to coding tasks, bridging the gap between natural languages (NL) and programming languages (PL). This taxonomy-based survey provides a comprehensive analysis of LLMs in the NL-PL domain, investigating how these models are ut

Tongyu Nian, Shuhei Tsujie, Ryo Uchiumi, Masahiko Yoshinaga

We first observe a mysterious similarity between the braid arrangement and the arrangement of all hyperplanes in a vector space over the finite field $\mathbb{F}_q$. These two arrangements are defined by the determinants of the Vandermonde and the Moore matrix, respectively. These two matrices are transformed to each other by replacing a natural number $n$ w

Feijiang Li, Jieting Wang, Liuya zhang, Yuhua Qian

Clustering ensemble has been a popular research topic in data science due to its ability to improve the robustness of the single clustering method. Many clustering ensemble methods have been proposed, most of which can be categorized into clustering-view and sample-view methods. The clustering-view method is generally efficient, but it could be affected by t

A. -H. Abdel-Aty, D. R. K. Massembele, P. Djorwé, A. N. Al-Ahmadi

We propose a scheme to enhance quantum entanglement in an optomechanical system consisting of two mechanically coupled mechanical resonators, which are driven by a common electromagnetic field. Each mechanical resonator is linearly and quadratically coupled to the electromagnetic field. Moreover, the mechanical coupling between the resonators is modulated th

Cheikh Ahmed, Alexandre Forel, Axel Parmentier, Thibaut Vidal

Districting is a complex combinatorial problem that consists in partitioning a geographical area into small districts. In logistics, it is a major strategic decision determining operating costs for several years. Solving districting problems using traditional methods is intractable even for small geographical areas and existing heuristics often provide sub-o

Ines Boujnah, Nehal Afifi, Andreas Wettstein, Sven Matthiesen

Bolted joints are critical in engineering for maintaining structural integrity and reliability. Accurate prediction of parameters influencing their function and behavior is essential for optimal performance. Traditional methods often fail to capture the non-linear behavior of bolted joints or require significant computational resources, limiting accuracy and

Minh Le, Tien Ngoc Luu, An Nguyen The, Thanh-Thien Le

To address catastrophic forgetting in Continual Relation Extraction (CRE), many current approaches rely on memory buffers to rehearse previously learned knowledge while acquiring new tasks. Recently, prompt-based methods have emerged as potent alternatives to rehearsal-based strategies, demonstrating strong empirical performance. However, upon analyzing exis

Zuan Xie, Yang Xu, Hongli Xu, Yunming Liao

In 5G smart cities, edge computing is employed to provide nearby computing services for end devices, and the large-scale models (e.g., GPT and LLaMA) can be deployed at the network edge to boost the service quality. However, due to the constraints of memory size and computing capacity, it is difficult to run these large-scale models on a single edge node. To

Anindita Mondal, Rangavajjala Sankara Bharadwaj, Jhansi Mallela, Anil Kumar Vuppala

Automatic detection of prominence at the word and syllable-levels is critical for building computer-assisted language learning systems. It has been shown that prosody embeddings learned by the current state-of-the-art (SOTA) text-to-speech (TTS) systems could generate word- and syllable-level prominence in the synthesized speech as natural as in native speec

Wenjun Ding, Ying An, Lixing Chen, Shichao Kan

Federated Adversarial Learning (FAL) is a robust framework for resisting adversarial attacks on federated learning. Although some FAL studies have developed efficient algorithms, they primarily focus on convergence performance and overlook generalization. Generalization is crucial for evaluating algorithm performance on unseen data. However, generalization a

Naryeong Kim, Sungmin Kang, Gabin An, Shin Yoo

Large Language Models are increasingly used to build agents to perform more complex tasks. As LLMs perform more complicated reasoning through longer interactions, self-consistency, i.e., the idea that the answer obtained from sampling and marginalising a number of multiple independent inferences is more likely to be correct, has received much attention as a

M. Liempi, D. R. G. Schleicher, A. Benson, A. Escala

The coexistence of nuclear star clusters (NSCs) and supermassive black holes (SMBHs) in galaxies with stellar masses $\sim 10^{10}~$M$_\odot$, the scaling relations between their properties and properties of the host galaxy (e.g., $M_{NSC}^{stellar}-M_{galaxy}^{stellar}$, $M_{BH}-M_{galaxy}^{stellar}$), and the fact that NSCs seem to take on the role of SMBH

Marta R. Costa-jussà, Joy Chen, Ifeoluwanimi Adebara, Joe Chuang

The purpose of this work is to share an English-Yor\`ub\'a evaluation dataset for open-book reading comprehension and text generation to assess the performance of models both in a high- and a low- resource language. The dataset contains 358 questions and answers on 338 English documents and 208 Yor\`ub\'a documents. The average document length is ~ 10k words

Tzu-Yuan Huang, Armin Lederer, Nicolas Hoischen, Jan Brüdigam

Achieving global optimality in nonlinear model predictive control (NMPC) is challenging due to the non-convex nature of the underlying optimization problem. Since commonly employed local optimization techniques depend on carefully chosen initial guesses, this non-convexity often leads to suboptimal performance resulting from local optima. To overcome this li

Zhengchuan Chen, Yi Qu, Nikolaos Pappas, Chaowei Tang

Using multiple sensors to update the status process of interest is promising in improving the information freshness. The unordered arrival of status updates at the monitor end poses a significant challenge in analyzing the timeliness performance of parallel updating systems. This work investigates the age of information (AoI) of a discrete-time dual-sensor s

Yuanwei Liu, Chengyu Jia, Ruqi Xiao, Xuemai Jia

The task of privacy-preserving face recognition (PPFR) currently faces two major unsolved challenges: (1) existing methods are typically effective only on specific face recognition models and struggle to generalize to black-box face recognition models; (2) current methods employ data-driven reversible representation encoding for privacy protection, making th

Kento Kawaharazuka, Koki Shinjo, Yoichiro Kawamura, Kei Okada

In this study, we propose a predictive model composed of a recurrent neural network including parametric bias and stochastic elements, and an environmentally adaptive robot control method including variance minimization using the model. Robots which have flexible bodies or whose states can only be partially observed are difficult to modelize, and their predi

Marta R. Costa-jussà, Bokai Yu, Pierre Andrews, Belen Alastruey

We introduce the first highly multilingual speech and American Sign Language (ASL) comprehension dataset by extending BELEBELE. Our dataset covers 74 spoken languages at the intersection of BELEBELE and FLEURS, and one sign language (ASL). We evaluate 2M-BELEBELE dataset for both 5-shot and zero-shot settings and across languages, the speech comprehension ac

Jesus L. Lobo, Javier Del Ser

Artificial Intelligence is widely regarded as a transformative force with the potential to redefine numerous sectors of human civilization. While Artificial Intelligence has evolved from speculative fiction to a pivotal element of technological progress, its role as a truly transformative agent, or transformative Artificial Intelligence, remains a subject of

Zhi-Yuan Cui, Yuan Li, Dun Zhao

We investigate the decay estimates of global solutions for a class of one-dimensional inhomogeneous nonlinear Schr\"odinger equations. While most existing results focus on spatial dimensions $d\geq2$, the decay properties in one dimension remain less explored due to the absence of effective Morawetz inequalities. For equations without external potential, by

Feng Zhou, Qi Zhang, Ju Dai, Lei Li

Point cloud completion aims to recover partial geometric and topological shapes caused by equipment defects or limited viewpoints. Current methods either solely rely on the 3D coordinates of the point cloud to complete it or incorporate additional images with well-calibrated intrinsic parameters to guide the geometric estimation of the missing parts. Althoug

Kento Kawaharazuka, Kei Tsuzuki, Shogo Makino, Moritaka Onitsuka

The musculoskeletal humanoid has many benefits that human beings have, but the modeling of its complex flexible body is difficult. Although we have developed an online acquisition method of the nonlinear relationship between joints and muscles, we could not completely match the actual robot and its self-body image. When realizing a certain task, the direct r

Emin Mijit, Peiyue Ma, Christoph J. Sahle, Angelika D. Rosa

The recent discovery of superconductivity in $\rm La_3Ni_2O_7$ has attracted significant attention due to its high critical temperature and analogy to cuprate oxides. The oxidation and spin states of Ni ions are among the most important local properties in this compound, extensively discussed in the context of its superconductivity. Despite their direct link

Marta R. Costa-jussà, Pierre Andrews, Mariano Coria Meglioli, Joy Chen

This paper presents the Long Context and Form Output (LCFO) benchmark, a novel evaluation framework for assessing gradual summarization and summary expansion capabilities across diverse domains. LCFO consists of long input documents (5k words average length), each of which comes with three summaries of different lengths (20%, 10%, and 5% of the input text),

José Garrido, Michael Roa, Miguel Guevara

In this talk, we present the CGC/saturation approach of Ref.[C.~Contreras, E.~Levin, R.~Meneses and M.~Sanhueza,Eur. Phys. J. C 80 (2020) no.11, 1029] and its parameters determined from the combined HERA data. This model features an analytical solution for the non-linear Balitsky-Kovchegov (BK) evolution equation and the exponential behavior of the saturatio

Tetsuro Nagai, Koji Yoshida

Given a multidimensional free-energy or potential-energy landscape, finding reaction paths that connect an initial (or reactant) state and a final (or product) state is important for biophysics and materials science. The likelihood of a path can be evaluated using an objective function, and the most likely reaction path can be found by optimizing its objecti

Yihan Cao, Jiazhao Zhang, Zhinan Yu, Kai Xu

Camera placement is crutial in multi-camera systems such as virtual reality, autonomous driving, and high-quality reconstruction. The camera placement challenge lies in the nonlinear nature of high-dimensional parameters and the unavailability of gradients for target functions like coverage and visibility. Consequently, most existing methods tackle this chal

Ufuk Çakır, Anna Lena Schaible, Tobias Buck

We present RUBIX, a fully tested, well-documented, and modular Open Source tool developed in JAX, designed to forward model IFU cubes of galaxies from cosmological hydrodynamical simulations. The code automatically parallelizes computations across multiple GPUs, demonstrating performance improvements over state-of-the-art codes by a factor of 600. This optim

Zhiwei Hu, Víctor Gutiérrez-Basulto, Ru Li, Jeff Z. Pan

Multimodal entity linking (MEL) aims to link ambiguous mentions within multimodal contexts to corresponding entities in a multimodal knowledge base. Most existing approaches to MEL are based on representation learning or vision-and-language pre-training mechanisms for exploring the complementary effect among multiple modalities. However, these methods suffer

Matthias J. Ehrhardt, Silvia Gazzola, Sebastian J. Scott

Many optimization problems require hyperparameters, i.e., parameters that must be pre-specified in advance, such as regularization parameters and parametric regularizers in variational regularization methods for inverse problems, and dictionaries in compressed sensing. A data-driven approach to determine appropriate hyperparameter values is via a nested opti

Pascal Tilli, Ngoc Thang Vu

Explainable artificial intelligence (XAI) aims to make machine learning models more transparent. While many approaches focus on generating explanations post-hoc, interpretable approaches, which generate the explanations intrinsically alongside the predictions, are relatively rare. In this work, we integrate different discrete subset sampling methods into a g

Marien Renaud, Julien Hermant, Nicolas Papadakis

Plug-and-Play methods for image restoration are iterative algorithms that solve a variational problem to recover a clean image from a degraded observation. These algorithms are known to be flexible to changes of degradation and to perform state-of-the-art restoration. Recently, significant efforts have been made to explore new stochastic algorithms based on

Chongkai Gao, Haozhuo Zhang, Zhixuan Xu, Zhehao Cai

We aim to develop a model-based planning framework for world models that can be scaled with increasing model and data budgets for general-purpose manipulation tasks with only language and vision inputs. To this end, we present FLow-centric generative Planning (FLIP), a model-based planning algorithm on visual space that features three key modules: 1. a multi

Francesco Polizzi, Pietro Sabatino

Let $\Sigma_b$ be a closed Riemann surface of genus $b$. We investigate finite quotients $G$ of the pure braid group on two strands $\mathsf{P}_2(\Sigma_b)$ which do not factor through $\pi_1(\Sigma_b \times \Sigma_b)$. Building on our previous work on some special systems of generators on finite groups that we called \emph{diagonal double Kodaira structures

J. Strohsack, A. Shumilin, H. Zhao, G. Jecl

The interface between a ferromagnetic metal and an organic molecular semiconductor, commonly referred to as a spinterface, is an important component for advancing spintronic technologies. Hybridization of the ferromagnetic-metal surface d orbitals with the molecular-semiconductor p orbitals induces profound modifications not only in the interfacial molecular

Zhiqiang Yuan, Jiapei Zhang, Ying Deng, Yeshuang Zhu

As a common form of communication in social media,stickers win users' love in the internet scenarios, for their ability to convey emotions in a vivid, cute, and interesting way. People prefer to get an appropriate sticker through retrieval rather than creation for the reason that creating a sticker is time-consuming and relies on rule-based creative tools wi

Kai Lehniger, Peter Langendörfer

This is a comment on "RIO: Return Instruction Obfuscation for Bare-Metal IoT Devices with Binary Analysis". RIO prevents finding gadgets for Return-Oriented Programming attacks by encrypting return instructions. This paper shows flaws in the design of RIO that allow for the easy retrieval of the plaintext return instructions without decrypting them. Addition

Sébastien Martin

This manuscript describes the notions of blocker and interdiction applied to well-known optimization problems. The main interest of these two concepts is the capability to analyze the existence of a combinatorial structure after some modifications. We focus on graph modification, like removing vertices or links in a network. In the interdiction version, we h

Jiacheng Hu, Runyuan Bao, Yang Lin, Hanchao Zhang

This study evaluated the effect of BioBERT in medical text processing for the task of medical named entity recognition. Through comparative experiments with models such as BERT, ClinicalBERT, SciBERT, and BlueBERT, the results showed that BioBERT achieved the best performance in both precision and F1 score, verifying its applicability and superiority in the

Jean-Daniel Fournier, Mikhaël Pichot du Mézeray

This report aims to provide gravitational waves data analysts with an introduction to the ideas and practice of the Pad\'e Filtering method for disentangling a signal from the noise. Technically it comes to the tracking of the zeros and singularities of random z-Transforms by noisy Pad\'e Approximants.

Klaus Nielsen

Let $O(p,q)$ be the orthogonal groups of signature $(p,q)$ over the reals. It is shown that an element of the commutator subgroup $O(p,q)'$ of $O(p,q)$ is bireflectional (product of 2 involutions in $O(p,q)'$) if and only if it is reversible (conjugate to its inverse). Moreover, the bireflectional elements of $O(p, q)'$ are classified.

Anas Abdelwahab, Christoph Karrasch, Roman Rausch

We introduce the concept of tetris chains, which are linear arrays of 4-site molecules that differ by their intermolecular hopping geometry. We investigate the fermionic symmetry-protected topological Haldane phase in these systems using Hubbard-type models. The topological phase diagrams can be understood via different competing limits and mechanisms: stron

Shuo Wang, Kuojun Yang, Zelin Ji, Qinchuan Zhang

Automatic modulation recognition (AMR) critically contributes to spectrum sensing, dynamic spectrum access, and intelligent communications in cognitive radio systems. The introduction of deep learning has greatly improved the accuracy of AMR. However, current automatic identification methods require the input of key parameters such as the carrier frequency,

Trinh Van Chien, Nguyen Minh Quan, Tri Nhu Do, Cuong Le

Low Earth orbit (LEO) satellites has brought about significant improvements in wireless communications, characterized by low latency and reduced transmission loss compared to geostationary orbit (GSO) satellites. Ultra-dense LEO satellites can serve many users by generating active beams effective to their locations. The beam placement problem is challenging

L. -R. Gounis, A. Kehagias, A. Riotto

We investigate the tidal response of Kerr black holes in four-dimensional space-times subjected to external gravitational fields. Using the Ernst formalism and Weyl coordinates, we analyze the non-linear tidal deformation of rotating black holes and demonstrate that their static tidal Love numbers vanish at all orders of the external tidal field. We also sho

Sam Shepherd

We prove that if a group $G$ admits a virtually special action on a CAT(0) cube complex, then any product of convex-cocompact subgroups of $G$ is separable. Previously, this was only known for products of three subgroups, or in the case where $G$ is hyperbolic, or in some other more technical cases with additional assumptions on the subgroups (plus these pre

Junjie Li, Ke Zhang, Shuai Wang, Kong Aik Lee

Audio-visual Target Speaker Extraction (AV-TSE) aims to isolate the speech of a specific target speaker from an audio mixture using time-synchronized visual cues. In real-world scenarios, visual cues are not always available due to various impairments, which undermines the stability of AV-TSE. Despite this challenge, humans can maintain attentional momentum

S. Strnat, J. Sommerfeldt, A. K. Sahoo, L. Sharma

We present a theoretical study of the inelastic scattering of vortex electrons by a hydrogen atom. In our study, special emphasis is placed on the effects of the Coulomb interaction between a projectile electron and a target atom. To understand these effects, we construct vortex electron wave functions both from free space and distorted solutions of the Schr

X. -D. Xu, I. Mukha, J. G. Li, S. M. Wang

The previously-unknown nucleus 20Al has been observed for the first time by detecting its in-flight decays. Tracking trajectories of all decay products with silicon micro-strip detectors allowed for a conclusion that 20Al is unbound with respect to three-proton (3p) emission. The 3p-decay energy of 20Al ground state has been determined to be 1.93(+0.11,-0.09

IAU Centre for the Protection of the Dark, Quiet Sky from Satellite Constellation Interference, Gyula I. G. Józsa, Andrew Williams

The growing number of satellite constellations in low Earth orbit (LEO) enhances global communications and Earth observation, and support of space commerce is a high priority of many governments. At the same time, the proliferation of satellites in LEO has negative effects on astronomical observations and research, and the preservation of the dark and quiet

Bohan Li, Jiajun Deng, Yasheng Sun, Xiaofeng Wang

Camera-based 3D Semantic Occupancy Prediction (SOP) is crucial for understanding complex 3D scenes from limited 2D image observations. Existing SOP methods typically aggregate contextual features to assist the occupancy representation learning, alleviating issues like occlusion or ambiguity. However, these solutions often face misalignment issues wherein the

Alexandros T. Oratis, Kai van den Berg, Vincent Bertin, Jacco H. Snoeijer

Lubrication flows between two solid surfaces can be found in a variety of biological and engineering settings. In many of these systems, the lubricant exhibits viscoelastic properties, which modify the associated lubrication forces. Here, we experimentally study viscoelastic lubrication by considering the motion of a submerged cylinder sliding down an inclin

Haiming Yao, Wei Luo, Xue Wang

Raman spectroscopy, as a label-free detection technology, has been widely utilized in the clinical diagnosis of pathogenic bacteria. However, Raman signals are naturally weak and sensitive to the condition of the acquisition process. The characteristic spectra of a bacteria can manifest varying signal-to-noise ratios and domain discrepancies under different

Ramy A. Zeineldin, Franziska Mathis-Ullrich

Accurate segmentation of brain tumors from 3D multimodal MRI is vital for diagnosis and treatment planning across diverse brain tumors. This paper addresses the challenges posed by the BraTS 2023, presenting a unified transfer learning approach that applies to a broader spectrum of brain tumors. We introduce HT-CNNs, an ensemble of Hybrid Transformers and Co

Yuan Zhang, Kuo Zhan, Peilin Xin, Yingqi Zhao

Proline (Pro) is one kind of proteinogenic amino acid and an important signaling molecule in the process of metabolism. Hydroxyproline (Hyp) is a product on Pro oxygen sensing post-translational modification (PTM), which is efficiently modulated tumor cells for angiogenesis. Distinguishing between Pro and Hyp is crucial for diagnosing connective tissue disor

Yihan Cao, Jiazhao Zhang, Zhinan Yu, Shuzhen Liu

Object goal navigation (ObjectNav) is a fundamental task in embodied AI, requiring an agent to locate a target object in previously unseen environments. This task is particularly challenging because it requires both perceptual and cognitive processes, including object recognition and decision-making. While substantial advancements in perception have been dri

Augustinos D. Saravanos, Hunter Kuperman, Alex Oshin, Arshiya Taj Abdul

Quadratic programming (QP) forms a crucial foundation in optimization, encompassing a broad spectrum of domains and serving as the basis for more advanced algorithms. Consequently, as the scale and complexity of modern applications continue to grow, the development of efficient and reliable QP algorithms is becoming increasingly vital. In this context, this

Imre Bárány

In a vector balancing game, on step $k$ player 1 chooses a unit vector $v_k$ and player 2 chooses a sign $\varepsilon_k\in \{-1,1\}$, and the position after $n$ steps is $z_n=\sum_1^n\varepsilon_k v_k$. Player 1's target is to make $\|z_n\|$ large and player 2's target is to make it small. We consider a special case of this game.

Xingchen Song, Mengtao Xing, Changwei Ma, Shengqiang Li

It is well known that LLM-based systems are data-hungry. Recent LLM-based TTS works typically employ complex data processing pipelines to obtain high-quality training data. These sophisticated pipelines require excellent models at each stage (e.g., speech denoising, speech enhancement, speaker diarization, and punctuation models), which themselves demand hig

Doha Ouardi, Manel Barkallah, Jean-Marie Jacquet

Process algebras have been widely used to verify security protocols in a formal manner. However they mostly focus on synchronous communication based on the exchange of messages. We present an alternative approach relying on asynchronous communication obtained through information available on a shared space. More precisely this paper first proposes an embeddi

Laurence Cliffe, James Mansell, Joanne Cormac, Chris Greenhalgh

This paper introduces two ongoing projects where audio augmented reality is implemented as a means of engaging museum and gallery visitors with audio archive material and associated objects, artworks and artefacts. It outlines some of the issues surrounding the presentation and engagement with sound based material within the context of the cultural instituti

Franco Barbanera, Rolf Hennicker

The Participants-as-Interfaces (PaI) approach to system composition suggests that participants of a system may be viewed as interfaces. Given a set of systems,one participant per system is chosen to play the role of an interface. When systems are composed, the interface participants are replaced by gateways which communicate to each other by forwarding messa

Farid Arfi, Hélène Coullon, Frédéric Loulergue, Jolan Philippe

We propose an overview of the decentralized reconfiguration language Concerto-D through its Maude formalization. Concerto-D extends the already published Concerto language. Concerto-D improves on two different parameters compared with related work: the decentralized coordination of numerous local reconfiguration plans which avoid a single point of failure wh

Bas van den Heuvel, Jorge A. Pérez

While formal models of concurrency tend to focus on synchronous communication, asynchronous communication is relevant in practice. In this paper, we will discuss asynchronous communication in the context of session-based concurrency, the model of computation in which session types specify the structure of the two-party protocols implemented by the channels o

Yiming Yang, Weipeng Hu, Haifeng Hu

Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) offers a more flexible and cost-effective alternative compared to supervised methods. This field has gained increasing attention due to its promising potential. Existing methods simply cluster modality-specific samples and employ strong association techniques to achieve instance-to

I. Knyazeva, I. Lysov, E. Kurochkin, A. Shendrik

The advancement of observational technologies and software for processing and visualizing spectro-polarimetric microwave data obtained with the RATAN-600 radio telescope opens new opportunities for studying the physical characteristics of solar plasma at the levels of the chromosphere and corona. These levels remain some difficult to detect in the ultraviole

Mario Christopher Bedrunka, Tobias Horstmann, Ben Picard, Dirk Reith

Integrating machine learning techniques in established numerical solvers represents a modern approach to enhancing computational fluid dynamics simulations. Within the lattice Boltzmann method (LBM), the collision operator serves as an ideal entry point to incorporate machine learning techniques to enhance its accuracy and stability. In this work, an invaria

Célia Blondin, Joris Guérin, Kelly Inagaki, Guilherme Longo

Automated benthic image annotation is crucial to efficiently monitor and protect coral reefs against climate change. Current machine learning approaches fail to capture the hierarchical nature of benthic organisms covering reef substrata, i.e., coral taxonomic levels and health condition. To address this limitation, we propose to annotate benthic images usin

Laurence Cliffe, James Mansell, Chris Greenhalgh, Adrian Hazzard

This article presents the results of a study based on a group of participants' interactions with an experimental sound installation at the National Science and Media Museum in Bradford, UK. The installation used audio augmented reality to attach virtual sound sources to a vintage radio receiver from the museum's collection, with a view to understanding the p

Zian Zhai, Sima Qing, Xiaoyang Wang, Wenjie Zhang

Signed Graph Neural Networks (SGNNs) are effective in learning expressive representations for signed graphs but typically require substantial task-specific labels, limiting their applicability in label-scarce industrial scenarios. In contrast, unsigned graph structures are abundant and can be readily leveraged to pre-train Graph Neural Networks (GNNs), offer

Liang Li, Yu Wang

The \emph{Swift} Burst Alert Telescope (BAT), operating in the 15--150 keV energy band, struggles to detect the peak energy ($E_{\rm p}$) of gamma-ray bursts (GRBs), as most GRBs have $E_{\rm p}$ values typically distributed between 200-300 keV, exceeding BAT's upper limit. To address this, we develop an innovative method to robustly estimate the lower limit

Jake Thomas, Jeremie Houssineau

A popular strategy for active learning is to specifically target a reduction in epistemic uncertainty, since aleatoric uncertainty is often considered as being intrinsic to the system of interest and therefore not reducible. Yet, distinguishing these two types of uncertainty remains challenging and there is no single strategy that consistently outperforms th

Yuri Sao, Olivier Roustant, Geraldo de Freitas Maciel

Global sensitivity analysis (GSA) aims at quantifying the contribution of input variables over the variability of model outputs. In the frame of functional outputs, a common goal is to compute sensitivity maps (SM), i.e sensitivity indices at each output dimension (e.g. time step for time series, or pixels for spatial outputs). In specific settings, some wor

Yi Li, Zengyu Liu, Xiandi Zhu, Ning Xie

Virtual Reality (VR) creates a highly realistic and controllable simulation environment that can manipulate users' sense of space and time. While the sensation of "losing track of time" is often associated with enjoyable experiences, the link between time perception and user experience in VR and its underlying mechanisms remains largely unexplored. This stud

Hanzhe Yang, Youlong Wu, Dingzhu Wen, Yong Zhou

The Information Bottleneck (IB) principle has emerged as a promising approach for enhancing the generalization, robustness, and interpretability of deep neural networks, demonstrating efficacy across image segmentation, document clustering, and semantic communication. Among IB implementations, the IB Lagrangian method, employing Lagrangian multipliers, is wi

Ziqi Gao, Weikai Huang, Jieyu Zhang, Aniruddha Kembhavi

Recent advances in text-to-vision generation excel in visual fidelity but struggle with compositional generalization and semantic alignment. Existing datasets are noisy and weakly compositional, limiting models' understanding of complex scenes, while scalable solutions for dense, high-quality annotations remain a challenge. We introduce Generate Any Scene, a

Kuang Huang, Bangti Jin, Yavar Kian, Georges Sadaka

In this work we investigate an inverse problem of recovering point sources and their time-dependent strengths from {a posteriori} partial internal measurements in a subdiffusion model which involves a Caputo fractional derivative in time and a general second-order elliptic operator in space. We establish the well-posedness of the direct problem in the sense

Jie Qi, Jiaqi Hu, Jing Zhang, Miroslav Krstic

A transport PDE with a spatial integral and recirculation with constant delay has been a benchmark for neural operator approximations of PDE backstepping controllers. Introducing a spatially-varying delay into the model gives rise to a gain operator defined through integral equations which the operator's input -- the varying delay function -- enters in previ

Kaixin Wang, Kaiqiang Yu, Cheng Long

Maximal clique enumeration (MCE) is crucial for tasks like community detection and biological network analysis. Existing algorithms typically adopt the branch-and-bound framework with the vertex-oriented Bron-Kerbosch (BK) branching strategy, which forms the sub-branches by expanding the partial clique with a vertex. In this paper, we present a novel approac

J. Wijnen, J. Parker, M. Gagliano, E. Martínez-Pañeda

We present a novel computational framework to assess the structural integrity of welds. In the first stage of the simulation framework, local fractions of microstructural constituents within weld regions are predicted based on steel composition and welding parameters. The resulting phase fraction maps are used to define heterogeneous properties that are subs

Wladimir Sarlin, Zhaodong Niu, Alban Sauret, Philippe Gondret

In the present study, we investigated the generation phase of laboratory-scale water waves induced by the impulsive motion of a rigid piston, whose maximum velocity $U$ and total stroke $L$ are independently varied, as well as the initial liquid depth $h$. By doing so, the influence of two dimensionless numbers is studied: the Froude number $\mathrm{Fr}_p=U/

Dalibor Javůrek

Two distinct energy-momentum tensors of the theory of weak gravity and spinor quantum mechanics are analyzed with respect to their four-divergence and expectation values of energy. The first energy-momentum tensor is obtained by a straightforward generalization of the symmetric energy-momentum tensor of a free Dirac field, and the second is derived by the se

Daniel Yaacoub, Stéphane Blanco, Jean-François Cornet, Jérémi Dauchet

In 1905, Einstein's theory of Brownian motion supported the molecular basis of the diffusion equation and introduced two complementary viewpoints: a deterministic field description and a probabilistic formulation based on stochastic particle ensembles. The consequences were far-reaching in the development of key concepts of modern physics such as wave-partic

Georges Gras

Let $k=\mathbb{Q}(\sqrt{-m})$ be an imaginary quadratic field. We consider the properties of capitulation of the $p$-class group of $k$ in the anti-cyclotomic $\mathbb{Z}_p$-extension $k^{\rm ac}$ of $k$; for this, using a new approach based on the Log$_p$-function (Theorems 2.3, 3.4), we determine the first layer $k_1^{\rm ac}$ of $k^{\rm ac}$ over $k$, and

Hang Yan, Ze-Xian Deng, Xue-Qing Yu, Yan-Ling Xiong

We report transport measurements of infinite-layer cuprate Sr$_{1-x}$Eu$_{x}$CuO$_{2+y}$ films with controlled electron (by trivalent europium) and hole (by interstitial apical oxygen) carriers grown on SrTiO$_3$(001) with molecular beam epitaxy. An unusual enhancement of superconductivity upon moderate electron-hole coexistence in the films is found, which

Maxime Noizet, Philippe Xu, Philippe Bonnifait

Detecting road features is a key enabler for autonomous driving and localization. For instance, a reliable detection of poles which are widespread in road environments can improve localization. Modern deep learning-based perception systems need a significant amount of annotated data. Automatic annotation avoids time-consuming and costly manual annotation. Be

Maxime Noizet, Philippe Xu, Philippe Bonnifait

For autonomous navigation, accurate localization with respect to a map is needed. In urban environments, infrastructure such as buildings or bridges cause major difficulties to Global Navigation Satellite Systems (GNSS) and, despite advances in inertial navigation, it is necessary to support them with other sources of exteroceptive information. In road envir

Ximing Xing, Juncheng Hu, Ziteng Xue, Jing Zhang

Generating high-quality Scalable Vector Graphics (SVGs) from text remains a significant challenge. Existing LLM-based models that generate SVG code as a flat token sequence struggle with poor structural understanding and error accumulation, while optimization-based methods are slow and yield uneditable outputs. To address these limitations, we introduce SVGF

Kingman Cheung, C. J. Ouseph, Sin Kyu Kang

We investigate the potential of using the signature of mono-Higgs plus large missing energies to constrain on two new physics models, namely the model of an axion-like particle (ALP) and the model of sterile neutrinos. We focus on the Higgs-ALP interactions starting at dimension-six and the Higgs-sterile neutrino interactions starting at dimension-five, via

Hanlei Li, Guangyi Zhang, Kequan Zhou, Yunlong Cai

Developing channel-adaptive deep joint source-channel coding (JSCC) systems is a critical challenge in wireless image transmission. While recent advancements have been made, most existing approaches are designed for static channel environments, limiting their ability to capture the dynamics of channel environments. As a result, their performance may degrade

Qi Zheng, Haozhi Wang, Zihao Liu, Jiaming Liu

Prevalent lossy image compression schemes can be divided into: 1) explicit image compression (EIC), including traditional standards and neural end-to-end algorithms; 2) implicit image compression (IIC) based on implicit neural representations (INR). The former is encountering impasses of either leveling off bitrate reduction at a cost of tremendous complexit

Antonio Leitao, Nina Otter

Persistent homology (PH) is one of the main methods used in Topological Data Analysis. An active area of research in the field is the study of appropriate notions of PH representatives, which allow to interpret the meaning of the information provided by PH, making it an important problem in the application of PH, and in the study of its interpretability. Com

Haruka Kogure, Taishi Kurahashi

We study the existence of a $\Theta$ sentence which is simultaneously $\Gamma$-conservative over consistent RE extensions $T$ and $U$ of Peano Arithmetic for various reasonable pairs $(\Gamma, \Theta)$. As a result of this study, we prove the existence of a sentence which is essentially $\Theta$ and exactly hereditarily $\Gamma$-conservative over any single

Yifan Sun, Xiangdong Zhang

Recently, quantum convolutional neural networks (QCNNs) are proposed, harnessing the power of quantum computing for faster training compared to the classical counterparts. However, this framework for deep learning also relies on multiple processing layers to capture the representation of data, which necessitates precise dynamical control. Given the current s

Wenbo Liu, Akang Wang, Wenguo Yang, Qingjiang Shi

Mixed-integer linear programs (MILPs) are extensively used to model practical problems such as planning and scheduling. A prominent method for solving MILPs is large neighborhood search (LNS), which iteratively seeks improved solutions within specific neighborhoods. Recent advancements have integrated machine learning techniques into LNS to guide the constru

Yuhao Guo, Swarnim Shashank, Cosimo Bambi

The detection of gravitational waves with ground-based laser interferometers has opened a new window to test and constrain General Relativity (GR) in the strong, dynamical, and non-linear regime. In this paper, we follow an agnostic approach and we study the quasi-normal modes of gravitational perturbations of Johannsen black holes under the assumptions of t

Sajad Azizi, Mohamed El-Amine Madjet, Zheng Li, Jan M. Rost

Upon absorbing a photon, the ionized electron sails through the target force field in attoseconds to reach free space. This navigation probes details of the potential landscape that get imprinted into the phase of the ionization amplitude. The Eisenbud-Wigner-Smith (EWS) time delay, the energy derivative of this phase, provides the navigation time relative t

Alberto Bottino, Annika Stier, Mathias Boesl, Thomas Hayward-Schneider

Over the past decades, multiple gyrokinetic codes have shown to be able to simulate turbulence and associated transport in the core of Tokamak devices. However, their application to the edge and scrape-off layer (SOL) region presents significant challenges. To date, only few codes and models have been adapted to SOL/edge conditions. To further study the SOL