December 2024 arXiv papers — page 99

Alessandro Sinibaldi, Douglas Hendry, Filippo Vicentini, Giuseppe Carleo

We introduce a classical computational method for quantum dynamics that relies on a global-in-time variational principle. Unlike conventional time-stepping approaches, our scheme computes the entire state trajectory over a finite time window by minimizing a loss function that enforces the Schr\"odinger's equation. The variational state is parametrized with a

Xinquan Chen, Junqi Gao, Biqing Qi, Dong Li

Binary Neural Networks (BNNs) have garnered significant attention due to their immense potential for deployment on edge devices. However, the non-differentiability of the quantization function poses a challenge for the optimization of BNNs, as its derivative cannot be backpropagated. To address this issue, hypernetwork based methods, which utilize neural net

Clémentine Phung-Ngoc, Alexandre Bousse, Antoine De Paepe, Hong-Phuong Dang

This study introduces a novel framework for joint reconstruction of the activity and the attenuation (JRAA) in positron emission tomography (PET) using diffusion posterior sampling (DPS). By leveraging diffusion models (DMs), this approach directly addresses activity-attenuation dependencies, mitigating crosstalk issues prevalent in non-time-of-flight (TOF)

Huaiyu Tan, Yikang Lu, Alfonso de Miguel-Arribas, Lei Shi

Human behavior presents significant challenges for data-driven approaches and machine learning, particularly in modeling the emergent and complex dynamics observed in social dilemmas. These challenges complicate the accurate prediction of strategic decision-making in structured populations, which is crucial for advancing our understanding of collective behav

Stijn Cambie, François Dross, Kolja Knauer, Hoang La

A question at the intersection of Barnette's Hamiltonicity and Neumann-Lara's dicoloring conjecture is: Can every Eulerian oriented planar graph be vertex-partitioned into two acyclic sets? A CAI-partition of an undirected/oriented graph is a partition into a tree/connected acyclic subgraph and an independent set. Consider any plane Eulerian oriented triangu

Alexander Tyurin

We study the classical optimization problem $\min_{x \in \mathbb{R}^d} f(x)$ and analyze the gradient descent (GD) method in both nonconvex and convex settings. It is well-known that, under the $L$-smoothness assumption ($\|\nabla^2 f(x)\| \leq L$), the optimal point minimizing the quadratic upper bound $f(x_k) + \langle\nabla f(x_k), x_{k+1} - x_k\rangle +

Mauricio Figueroa-Torres

The development and deployment of chatbot technology, while spanning decades and employing different techniques, require innovative frameworks to understand and interrogate their functionality and implications. A mere technocentric account of the evolution of chatbot technology does not fully illuminate how conversational systems are embedded in societal dyn

Matteo Casati, Daniele Valeri

In this paper we study local Hamiltonian operators for multi-component evolutionary differential-difference equations. We address two main problems: the first one is the classification of low order operators for the two-component case. On the one hand, this extends the previously known results in the scalar case; on the other hand, our results include the de

Ziqun Li, Qi Zhang, Xiaofeng Huang, Zhao Wang

High-efficient image compression is a critical requirement. In several scenarios where multiple modalities of data are captured by different sensors, the auxiliary information from other modalities are not fully leveraged by existing image-only codecs, leading to suboptimal compression efficiency. In this paper, we increase image compression performance with

Shinichi Nishihaya, Malcolm J. A. Jardine, Hadass S. Inbar, Aranya Goswami

The interplay between half-metallic ferromagnetism and spin-orbit coupling within the inversion symmetry-broken structure of half Heuslers provides an ideal platform for various spintronics functionalities. Taking advantage of good lattice matching, it is highly desired to epitaxially integrate promising Heuslers into III-V semiconductor-based devices. PtMnS

Pratik Sutar, Jason Naradowsky, Yusuke Miyao

Natural language is commonly used to describe instrument timbre, such as a "warm" or "heavy" sound. As these descriptors are based on human perception, there can be disagreement over which acoustic features correspond to a given adjective. In this work, we pursue a data-driven approach to further our understanding of such adjectives in the context of guitar

Minghao Xu, Lichuan Xiang, Xu Cai, Hongkai Wen

In this work, we question the necessity of adaptive gradient methods for training deep neural networks. SGD-SaI is a simple yet effective enhancement to stochastic gradient descent with momentum (SGDM). SGD-SaI performs learning rate Scaling at Initialization (SaI) to distinct parameter groups, guided by their respective gradient signal-to-noise ratios (g-SN

Chen Liang, Lianghua Huang, Jingwu Fang, Huanzhang Dou

Real-world design tasks - such as picture book creation, film storyboard development using character sets, photo retouching, visual effects, and font transfer - are highly diverse and complex, requiring deep interpretation and extraction of various elements from instructions, descriptions, and reference images. The resulting images often implicitly capture k

Alfonso de Miguel-Arribas, Alberto Aleta, Yamir Moreno

Modeling human behavior is essential to accurately predict epidemic spread, with behaviors like vaccine hesitancy complicating control efforts. While epidemic spread is often treated as a simple contagion, vaccine uptake may follow complex contagion dynamics, where individuals' decisions depend on multiple social contacts. Recently, the concept of complex co

B. J. P Jones, J. A. Formaggio

Superradiance emerges from collective spontaneous emission in optically pumped gases, and is characterized by photon emission enhancements of up to $\frac{1}{4}N^{2}$ in an $N$ atom system. The gain mechanism derives from correlations developed within the decay medium rather than from stimulated emission as in lasing, so analog of this process should be poss

Jiayu Chen, Chao Yu, Yuqing Xie, Feng Gao

Executing precise and agile flight maneuvers is critical for quadrotors in various applications. Traditional quadrotor control approaches are limited by their reliance on flat trajectories or time-consuming optimization, which restricts their flexibility. Recently, RL-based policy has emerged as a promising alternative due to its ability to directly map obse

Mohammad Aflah Khan, Neemesh Yadav, Sarah Masud, Md. Shad Akhtar

The rise of large language models (LLMs) has created a need for advanced benchmarking systems beyond traditional setups. To this end, we introduce QUENCH, a novel text-based English Quizzing Benchmark manually curated and transcribed from YouTube quiz videos. QUENCH possesses masked entities and rationales for the LLMs to predict via generation. At the inter

Qingyue Deng, Jijiang Li, Haibin Ling, Bingyao Huang

We present GS-ProCams, the first Gaussian Splatting-based framework for projector-camera systems (ProCams). GS-ProCams is not only view-agnostic but also significantly enhances the efficiency of projection mapping (PM) that requires establishing geometric and radiometric mappings between the projector and the camera. Previous CNN-based ProCams are constraine

Junchao Chen, Suyash Gupta, Daniel P. Hughes, Mohammad Sadoghi

Each application developer desires to provide its users with consistent results and an always-available system despite failures. Boldly, the CALM theorem disagrees. It states that it is hard to design a system that is both consistent and available under network partitions; select at most two out of these three properties. One possible solution is to design c

Timothée Anne, Noah Syrkis, Meriem Elhosni, Florian Turati

Large Language Models (LLMs) have demonstrated remarkable performance across various tasks. Their potential to facilitate human coordination with many agents is a promising but largely under-explored area. Such capabilities would be helpful in disaster response, urban planning, and real-time strategy scenarios. In this work, we introduce (1) a real-time stra

Louis Wiesmann, Elias Marks, Saurabh Gupta, Tiziano Guadagnino

Constructing precise global maps is a key task in robotics and is required for localization, surveying, monitoring, or constructing digital twins. To build accurate maps, data from mobile 3D LiDAR sensors is often used. Mapping requires correctly aligning the individual point clouds to each other to obtain a globally consistent map. In this paper, we investi

Andrew Berget, Alex Fink

We introduce the Schubert variety of a pair of linear subspaces in $\mathbf{C}^n$ and the external activity complex of a pair of not necessarily realizable matroids. Both of these generalize constructions of Ardila et al., which occur when one of the linear spaces is one-dimensional. We prove that our external activity complex is Cohen-Macaulay and deduce a

Gabriel de Jesus, Sérgio Nunes

Searching for information on the internet and digital platforms requires effective retrieval solutions. However, such solutions are not yet available for Tetun, making it difficult to find relevant documents for search queries in this language. To address this gap, we investigate Tetun text retrieval with a focus on the ad-hoc retrieval task. The study begin

Xuanliang Zhang, Dingzirui Wang, Baoxin Wang, Longxu Dou

Scientific question answering (SQA) is an important task aimed at answering questions based on papers. However, current SQA datasets have limited reasoning types and neglect the relevance between tables and text, creating a significant gap with real scenarios. To address these challenges, we propose a QA benchmark for scientific tables and text with diverse

Elisa Davoli, Emanuele Tasso

We provide a novel sharp-interface analysis via Gamma-convergence for a non-local and non-homogeneous diffuse-interface model for phase transitions, featuring an interplay between a non-local interaction kernel and a spatially dependent double-well potential. This interaction requires the development of new strategies both for the Gamma-liminf inequality and

Tianyi Zhu, Dongwei Ren, Qilong Wang, Xiaohe Wu

Generative inbetweening aims to generate intermediate frame sequences by utilizing two key frames as input. Although remarkable progress has been made in video generation models, generative inbetweening still faces challenges in maintaining temporal stability due to the ambiguous interpolation path between two key frames. This issue becomes particularly seve

Christel Baier, Sascha Klüppelholz, Jakob Piribauer, Robin Ziemek

In adaptive systems, predictors are used to anticipate changes in the systems state or behavior that may require system adaption, e.g., changing its configuration or adjusting resource allocation. Therefore, the quality of predictors is crucial for the overall reliability and performance of the system under control. This paper studies predictors in systems e

Xiaoyin Yang

We introduce a wearable driving status recognition device and our open-source dataset, along with a new real-time method robust to changes in lighting conditions for identifying driving status from eye observations of drivers. The core of our method is generating event frames from conventional intensity frames, and the other is a newly designed Attention Dri

Yi-Hua Huang, Ming-Xian Lin, Yang-Tian Sun, Ziyi Yang

Recently, Gaussian splatting has emerged as a robust technique for representing 3D scenes, enabling real-time rasterization and high-fidelity rendering. However, Gaussians' inherent radial symmetry and smoothness constraints limit their ability to represent complex shapes, often requiring thousands of primitives to approximate detailed geometry. We introduce

Arpan Das

Let $p$ be a prime and $F$ a non-archimedean local field of residue characteristic $p$. In this paper, we study the restriction of smooth irreducible $\bar{\mathbb{F}}_p$-representations of $\mathrm{SL}_2(F)$ to its Borel subgroup. In essence, we show that the action of $\mathrm{SL}_2(F)$ on its irreducibles is controlled by the action of the Borel subgroup.

Javier A. Lopetegui, Arij Riabi, Djamé Seddah

Variations in languages across geographic regions or cultures are crucial to address to avoid biases in NLP systems designed for culturally sensitive tasks, such as hate speech detection or dialog with conversational agents. In languages such as Spanish, where varieties can significantly overlap, many examples can be valid across them, which we refer to as c

Rimo Das, V. Gayathri, Divyajyoti, Sijil Jose

Parameter estimation of gravitational wave data is often computationally expensive, requiring simplifying assumptions such as circularisation of binary orbits. Although, if included, the sub-dominant effects like orbital eccentricity may provide crucial insights into the formation channels of compact binary mergers. To address these challenges, we present a

Simin Yu, Ruixin Zhou, Guangcanlan Yang, Qiang Zhang

Thin film lithium niobate (TFLN) has emerged as a leading material platform for integrated nonlinear photonics, enabling transformative applications such as broadband Kerr soliton microcomb and high-speed electro-optic modulation. While stimulated Brillouin scattering has been numerically proposed in TFLN, achieving sufficient gain remains challenging due to

Junjie Huang, Jiarui Qin, Yong Yu, Weinan Zhang

Given the large volume of side information from different modalities, multimodal recommender systems have become increasingly vital, as they exploit richer semantic information beyond user-item interactions. Recent works highlight that leveraging Graph Convolutional Networks (GCNs) to explicitly model multimodal item-item relations can significantly enhance

Pei Zheng, Yidian Chen, Danning Li, Mei Huang

By using the holographic approach, we investigate the interplay between the order parameter and Goldstone modes in the real-time dynamics of the chiral phase transition. By quenching the system to a different thermal bath and obtaining different kinds of initial states, we solve the real-time evolution of the system numerically. Our main focus is on studying

Arij Riabi, Virginie Mouilleron, Menel Mahamdi, Wissam Antoun

The proliferation of radical content on online platforms poses significant risks, including inciting violence and spreading extremist ideologies. Despite ongoing research, existing datasets and models often fail to address the complexities of multilingual and diverse data. To bridge this gap, we introduce a publicly available multilingual dataset annotated w

Yanfeng Yang, Shuai Li, Yingjie Zhang, Zhuoran Sun

Conditional independence (CI) testing is a fundamental task in modern statistics and machine learning. The conditional randomization test (CRT) was recently introduced to test whether two random variables, $X$ and $Y$, are conditionally independent given a potentially high-dimensional set of random variables, $Z$. The CRT operates exceptionally well under th

Shreya Sinha Roy, Richard G. Everitt, Christian P. Robert, Ritabrata Dutta

Bayesian reinforcement learning (BRL) is a method that merges principles from Bayesian statistics and reinforcement learning to make optimal decisions in uncertain environments. As a model-based RL method, it has two key components: (1) inferring the posterior distribution of the model for the data-generating process (DGP) and (2) policy learning using the l

Huafu Liao, Chenchen Mou

This paper studies the $N$-particle systems as well as the HJB/master equations for a class of generalized mean field control (MFC) problems and the corresponding potential mean field games of control (MFGC). A local in time classical solution for the HJB equation is generated via a probabilistic approach based on the mean field maximum principle. Given an e

Hongxuan Zhang, Yao Zhao, Jiaqi Zheng, Chenyi Zhuang

The emergence of long-context text applications utilizing large language models (LLMs) has presented significant scalability challenges, particularly in memory footprint. The linear growth of the Key-Value (KV) cache responsible for storing attention keys and values to minimize redundant computations can lead to substantial increases in memory consumption, p

Aditi Chakrabarty, Sanjoy Datta

The eigenstates of one-dimensional Hermitian and non-Hermitian tight-binding systems (in the presence/absence of quasiperiodic potential) and an external electric field undergo complete localization with equally spaced eigenenergies, known as the Wannier-Stark (WS) localization. In this work, we demonstrate that when the electric field is slowly modulated wi

Fangbing Liu, Qing Wang

Optimizing spectral graph neural networks (GNNs) remains a critical challenge in the field, yet the underlying processes are not well understood. In this paper, we investigate the inherent differences between graph convolution parameters and feature transformation parameters in spectral GNNs and their impact on the optimization landscape. Our analysis reveal

Guillaume Rond

The aim of this survey papier is to present a result due to Eisenstein, to prove a generalized version of it, and to present some applications of this Eisenstein's Theorem, in particular to the study of the algebraic closure of the field of power series in several indeterminates.

Xue Yang, Depan Peng, Yan Feng, Xiaohu Tang

Bidirectional privacy-preservation federated learning is crucial as both local gradients and the global model may leak privacy. However, only a few works attempt to achieve it, and they often face challenges such as excessive communication and computational overheads, or significant degradation of model accuracy, which hinders their practical applications. I

Hang Zeng, Chaoyue Niu, Fan Wu, Chengfei Lv

Existing work on large language model (LLM) personalization assigned different responding roles to LLMs, but overlooked the diversity of queriers. In this work, we propose a new form of querier-aware LLM personalization, generating different responses even for the same query from different queriers. We design a dual-tower model architecture with a cross-quer

Wenyun Li, Zheng Zhang, Xiangyuan Lan, Dongmei Jiang

Traditional adversarial attacks typically produce adversarial examples under norm-constrained conditions, whereas unrestricted adversarial examples are free-form with semantically meaningful perturbations. Current unrestricted adversarial impersonation attacks exhibit limited control over adversarial face attributes and often suffer from low transferability.

V. V. Brazhkin

A lot has been said about the vibrational density of states (DoS) in liquids. A more recent discussion introduces contradictions with earlier results, and here I briefly review several pieces of evidence from modeling, experiments and theory showing this. I then show that the origin of contradictions often comes from misinterpreting the nature of excitations

Dorian S. H. Brandmüller, David Grafinger, Robert Nuster, Andreas Hohenau

Recent advances in the miniaturization of optical elements have led to the emergence of novel imaging systems, used for industrial and consumer-based applications. The underlying methods are particularly prevalent in the realms of medical imaging and optical microscopy. Avoiding bulky optical elements can be extremely beneficial to many microscopy modalities

Longyue Wang, Siyou Liu, Chenyang Lyu, Wenxiang Jiao

Following last year, we have continued to host the WMT translation shared task this year, the second edition of the Discourse-Level Literary Translation. We focus on three language directions: Chinese-English, Chinese-German, and Chinese-Russian, with the latter two ones newly added. This year, we totally received 10 submissions from 5 academia and industry

Christoph Laaber, Shaukat Ali, Thomas Schwitalla, Jan F. Nygård

The Cancer Registry of Norway (CRN) collects and processes cancer-related data for patients in Norway. For this, it employs a sociotechnical software system that evolves with changing requirements and medical standards. The current practice is to manually test CRN's system to prevent faults and ensure its dependability. This paper focuses on automatically te

Manuel Hohmann, Vasiliki Karanasou

In this article, we focus on symmetric teleparallel gravity, a modification of General Relativity where gravity is described by the non-metricity of an affine connection, whose curvature and torsion vanish. In these theories, the fundamental variables are the metric and an affine connection. Starting from the coincident gauge, a system of coordinates for whi

Cong Xu, Yunhang He, Jun Wang, Wei Zhang

While the mining of modalities is the focus of most multimodal recommendation methods, we believe that how to fully utilize both collaborative and multimodal information is pivotal in e-commerce scenarios where, as clarified in this work, the user behaviors are rarely determined entirely by multimodal features. In order to combine the two distinct types of i

Wenchao Gu, Ensheng Shi, Yanlin Wang, Lun Du

Code retrieval, which retrieves code snippets based on users' natural language descriptions, is widely used by developers and plays a pivotal role in real-world software development. The advent of deep learning has shifted the retrieval paradigm from lexical-based matching towards leveraging deep learning models to encode source code and queries into vector

Dmitrii V. Semenok, Florian Bärtl, Di Zhou, Toni Helm

The discovery of near-room temperature superconductivity in the lanthanum hydride LaH$_{10}$ has revolutionized this field of research. However, the need to use diamond anvils for the synthesis of such superconductors severely limits the number of experimental techniques to study these materials. Nuclear magnetic resonance (NMR) is one of the key methods for

David G. Zeitoun, Thierry Dana-Picard

The study of some parametric integrals is presented with a combined approach of analytical development, the usage of a Computed Algebra System (CAS) and of the Online Encyclopedia of Integer Sequences. The methodology for the solution includes a) an analytical investigation for the study of the parametric integral, b) computations with a CAS of the integral

Vjekoslav Kovač, Bruno Predojević

Paul Erd\H{o}s and R. Daniel Mauldin asked a series of questions on certain types of polygons of area $1$, the vertices of which can be found in every planar set of infinite Lebesgue measure. We address two of these questions, one on cyclic quadrilaterals and the other on convex polygons with congruent sides, with respectively positive and negative answers.

Toan T. Nguyen

In this paper, we establish nonlinear Landau damping below survival threshold for collisionless charged particles following the meanfield Vlasov theory near general radial equilibria. In absence of collisions, the long-range Coulomb pair interaction between particles self-consistently gives rise to oscillations, known in the physical literature as plasma osc

Donghyun Kim, Sriram Ravula, Taemin Ha, Alexandros G. Dimakis

Workload traces are essential to understand complex computer systems' behavior and manage processing and memory resources. Since real-world traces are hard to obtain, synthetic trace generation is a promising alternative. This paper proposes a first-of-a-kind approach that relies on training a large language model (LLM) to generate synthetic workload traces,

R. C. Silva, R. L. Silva

Micromagnetic simulations were employed to investigate the dynamics of a single skyrmion within an antiferromagnetic nanostripe with spatially engineered magnetic properties. This study investigates skyrmion motion within an antiferromagnetic nanostripe engineered with trapezoidal regions of enhanced magnetic anisotropy, enabling diode-like functionality by

I. Panin, A. Stavrova

Let D be a DVR of mixed characteristic. Let G be a reductive D-group scheme. Then the Grothendieck-Serre conjecture is true for the D-group scheme G and any geometrically regular local D-algebra R. Also we prove a version of Lindel-Ojanguren-Gabber's geometric presentation lemma in the DVR context.

Mohamed A. Fouad, Marcelo de Almeida Maia

Software engineering agents (swe-agents), as key innovations in intelligent software engineering, are poised in the industry's end-of-programming debate to transcend from assistance to primary roles. we argue the importance of swe-agents' economic viability to their transcendence -- defined as their capacity to maintain efficient operations in constrained en

C. Muthumariappan, K. Khushbu, V. Kerni

We study the properties of 26 PNe with PG1159-type central stars known till date and compare them with the properties of PNe having [WR], $wels$ and hydrogen-rich central stars published earlier. We use archival photometric measurements of $2MASS$ for near-IR analysis and $WISE$ and $IRAS$ data for mid- and far-IR analysis and derive the IR properties of PG1

Sindre Stenen Blakseth, Ailo Aasen, André Massing, Petter Nekså

Future use of liquid hydrogen (LH$_2$) as an effective energy carrier will require elimination or minimization of hydrogen boil-off that is not utilized by demands in the value chain. The present work promotes local area cooling (LAC) as a promising boil-off reduction technology. In contrast to the more conventional broad area cooling (BAC), LAC targets loca

Serhii Nazarovets

This study analyses the publication activity and migration patterns of Ukrainian scholars in the social sciences and humanities (SSH) during the initial two years of the Russo-Ukrainian war. Focusing on scholars who published at least three papers, the study underscores the resilience of these scholars, who continued their academic endeavours within their ho

Alex S. Arvanitakis, Lewis T. Cole, Saskia Demulder, Daniel C. Thompson

We construct a new class of topological surface defects in Chern-Simons theory with non-compact, non-Abelian gauge groups. These defects are characterized by isotropic subalgebras defined by solutions of the modified classical Yang-Baxter equation, and their fusion realizes a semi-group structure with non-invertible elements. From a Hamiltonian perspective,

Rick van Essen, Eldert van Henten, Gert Kootstra

UAVs are becoming popular in agriculture, however, they usually use time-consuming row-by-row flight paths. This paper presents a deep-reinforcement-learning-based approach for path planning to efficiently localize weeds in agricultural fields using UAVs with minimal flight-path length. The method combines prior knowledge about the field containing uncertain

Zhuoyun Du, Lujie Zheng, Renjun Hu, Yuyang Xu

Training medical personnel using standardized patients (SPs) remains a complex challenge, requiring extensive domain expertise and role-specific practice. Previous research on Large Language Model (LLM)-based SPs mostly focuses on improving data retrieval accuracy or adjusting prompts through human feedback. However, this focus has overlooked the critical ne

RunLin Yu, Yipu Gong, Wenrui Li, Aiwen Sun

Audio-visual Zero-Shot Learning (ZSL) has attracted significant attention for its ability to identify unseen classes and perform well in video classification tasks. However, modal imbalance in (G)ZSL leads to over-reliance on the optimal modality, reducing discriminative capabilities for unseen classes. Some studies have attempted to address this issue by mo

Wenjie Wang, Mengyan Li, Fenzhuo Guo, Yukun Wang

In the device-independent scenario, positive operator-valued measurements (POVMs) can certify more randomness than projective measurements. This paper self-tests a three-outcome extremal qubit POVM in the X-Z plane of the Bloch sphere by achieving the maximal quantum violation of a newly constructed Bell expression C'3, adapted from the chained inequality C3

Xuanming Zhang, Yuxuan Chen, Yiming Zheng, Zhexin Zhang

In real world software development, improper or missing exception handling can severely impact the robustness and reliability of code. Exception handling mechanisms require developers to detect, capture, and manage exceptions according to high standards, but many developers struggle with these tasks, leading to fragile code. This problem is particularly evid

Nicolás Rodríguez-Segovia, Ashley J. Ruiter, Ivo R. Seitenzahl

Subdwarf B stars are a well-known class of hot, low-mass stars thought to be formed through interactions in stellar binary systems. While different formation channels for subdwarf B stars have been studied through a binary population synthesis approach, it has also become evident that the characteristics of the found populations depend on the initial set of

Zheng Li, Yang Du, Mao Zheng, Mingyang Song

Extensive research has been conducted to explore the capability of Large Language Models (LLMs) for table reasoning and has significantly improved the performance on existing benchmarks. However, tables and user questions in real-world applications are more complex and diverse, presenting an unignorable gap compared to the existing benchmarks. To fill the ga

Etele Molnár, Dirk H. Rischke

We apply the method of moments to the relativistic Boltzmann-Vlasov equation and derive the equations of motion for the irreducible moments of arbitrary tensor-rank of the invariant single-particle distribution function. We study two cases, in the first of which the moments are taken to be irreducible with respect to the little group associated with the time

Yuanzhi Wang, Yong Li, Mengyi Liu, Xiaoya Zhang

Editing videos with textual guidance has garnered popularity due to its streamlined process which mandates users to solely edit the text prompt corresponding to the source video. Recent studies have explored and exploited large-scale text-to-image diffusion models for text-guided video editing, resulting in remarkable video editing capabilities. However, the

Gabriela Holubová, Petr Nečesal

In this paper, we study the Fu\v{c}\'{\i}k spectrum of a square matrix $A$ and provide necessary and sufficient conditions for the existence of Fu\v{c}\'{\i}k curves emanating from the point $(\lambda,\lambda)$ with $\lambda$ being a real eigenvalue of $A$. We extend recent results by Maroncelli (2024) and remove his assumptions on symmetry of $A$ and simpli

Alexander Glazman, Lucas Rey

We consider ergodic translation-invariant Gibbs measures for the dimer model (i.e. perfect matchings) on the hexagonal lattice. The complement to a dimer configuration is a fully-packed loop configuration: each vertex has degree two. This is also known as the loop $O(1)$ model at $x=\infty$. We show that, if the measure is non-frozen, then it exhibits either

Sangryul Kim, James Thorne

Question Answering (QA) in NLP is the task of finding answers to a query within a relevant context retrieved by a retrieval system. Yet, the mix of relevant and irrelevant information in these contexts can hinder performance enhancements in QA tasks. To address this, we introduce a context filtering approach that removes non-essential details, summarizing cr

Wenhao Sun, Rong-Cheng Tu, Jingyi Liao, Zhao Jin

Diffusion Transformers (DiTs) have proven effective in generating high-quality videos but are hindered by high computational costs. Existing video DiT sampling acceleration methods often rely on costly fine-tuning or exhibit limited generalization capabilities. We propose Asymmetric Reduction and Restoration (AsymRnR), a training-free and model-agnostic meth

Yohan Lee, Jonas Herbig, Serkan Arslan, Dominik Ludescher

Colour printing based on metallic or dielectric nanostructures has revolutionized colour science due to its unprecedented subwavelength resolution. Evidently, the evolution towards the active control of such structural colours with smart materials is in progress for real applications. Here we experimentally demonstrate a large colour gamut with high intensit

Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio, Nikolaos Aletras

Vocabulary expansion (VE) is the de-facto approach to language adaptation of large language models (LLMs) by adding new tokens and continuing pre-training on target data. While this is effective for base models trained on unlabeled data, it poses challenges for chat models trained to follow instructions through labeled conversation data. Directly adapting th

Said Pashayev, Romain Lhermerout, Christophe Roblin, Eric Alibert

In this article, we show that it is possible to differentiate between water adsorbed on the outside of a single-walled carbon nanotube and that confined inside. To this aim, we measured the electronic transport of a carbon nanotube based field effect transistor (CNTFET) constructed with an isolated single carbon nanotube subjected to controlled environments.

Mukul Lokhande, Gopal Raut, Santosh Kumar Vishvakarma

The rapid adaptation of data driven AI models, such as deep learning inference, training, Vision Transformers (ViTs), and other HPC applications, drives a strong need for runtime precision configurable different non linear activation functions (AF) hardware support. Existing solutions support diverse precision or runtime AF reconfigurability but fail to addr

Ben Dutton, Nikos Katzourakis

In this paper we study $2$nd order $L^\infty$ variational problems, through seeking to minimise a supremal functional involving the Hessian of admissible functions as well as lower-order terms. Specifically, given a bounded domain $\Omega\subseteq \mathbb R^n$ and $\mathrm H : \Omega\times\big(\mathbb R \times\mathbb R^n \times \mathbb R^{n^{\otimes2}}_s \bi

Dinar Khusyainov, Rein Liefferink, MengXing Na, Kammerbauer Fabian

Controlling magnetic textures at ever smaller length and time scales is of key fundamental and technological interest. Achieving nanoscale control often relies on finding an external stimulus that is able to act on that small length scales, which is highly challenging. A promising alternative is to achieve nanoscale control using the inhomogeneity of the mag

Chengwei Wei, Bin Wang, Jung-jae Kim, Guimei Liu

Large Language Models (LLMs) have shown strong performance in solving mathematical problems, with code-based solutions proving particularly effective. However, the best practice to leverage coding instruction data to enhance mathematical reasoning remains underexplored. This study investigates three key questions: (1) How do different coding styles of mathem

Matteo Esposito, Francesco Palagiano, Valentina Lenarduzzi, Davide Taibi

Context. The security of critical infrastructure has been a pressing concern since the advent of computers and has become even more critical in today's era of cyber warfare. Protecting mission-critical systems (MCSs), essential for national security, requires swift and robust governance, yet recent events reveal the increasing difficulty of meeting these cha

Chin-Chia Chang, Hendrik Herrmann, Chin-Yu Hsiao

Let $X$ be a compact strictly pseudoconvex embeddable CR manifold and let $A$ be the Toeplitz operator on $X$ associated with a Reeb vector field $\mathcal{T}\in\mathscr{C}^\infty(X,TX)$. Consider the operator $\chi_k(A)$ defined by functional calculus of $A$, where $\chi$ is a smooth function with compact support in the positive real line and $\chi_k(\lambd

Krishnendu Chatterjee, Ruichen Luo, Raimundo Saona, Jakub Svoboda

We consider a class of optimization problems defined by a system of linear equations with min and max operators. This class of optimization problems has been studied under restrictive conditions, such as, (C1) the halting or stability condition; (C2) the non-negative coefficients condition; (C3) the sum up to 1 condition; and (C4) the only min or only max oe

Ming Wei Lee, John Y. H. Soo, Syarawi M. H. Sharoni

The structural information of spiral galaxies such as the spiral arm number, offer valuable insights into their formation processes and physical roles in galaxy evolution. We developed classifiers based on CNNs using variants of the EfficientNet architecture with different transfer learning techniques and pre-trained weights to categorise spiral galaxies by

Eloy Geenjaar, Lie Lu

Transfer learning for bio-signals has recently become an important technique to improve prediction performance on downstream tasks with small bio-signal datasets. Recent works have shown that pre-training a neural network model on a large dataset (e.g. EEG) with a self-supervised task, replacing the self-supervised head with a linear classification head, and

Shixin Jiang, Jiafeng Liang, Jiyuan Wang, Xuan Dong

To tackle complex tasks in real-world scenarios, more researchers are focusing on Omni-MLLMs, which aim to achieve omni-modal understanding and generation. Beyond the constraints of any specific non-linguistic modality, Omni-MLLMs map various non-linguistic modalities into the embedding space of LLMs and enable the interaction and understanding of arbitrary

Xiaoshan Luo, Zhenyu Wang, Qingchang Wang, Jian Lv

Deep learning-based generative models have emerged as powerful tools for modeling complex data distributions and generating high-fidelity samples, offering a transformative approach to efficiently explore the configuration space of crystalline materials. In this work, we present CrystalFlow, a flow-based generative model specifically developed for the genera

Li Ma, Benedetta Bruni

Tree-based priors for probability distributions are usually specified using a predetermined, data-independent collection of candidate recursive partitions of the sample space. To characterize an unknown target density in detail over the entire sample space, candidate partitions must have the capacity to expand deeply into all areas of the sample space with p

Daryna Dementieva, Nikolay Babakov, Amit Ronen, Abinew Ali Ayele

Even with various regulations in place across countries and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022, digital abusive speech remains a significant issue. One potential approach to address this challenge is automatic text detoxification, a text style transfer (TST) approach that transforms

Salman Faroz

The medical domain is vast and diverse, with many existing embedding models focused on general healthcare applications. However, these models often struggle to capture a deep understanding of diseases due to their broad generalization across the entire medical field. To address this gap, I present DisEmbed, a disease-focused embedding model. DisEmbed is trai

José Carmona Tapia, Antonio J. Martínez Aparicio, Pedro J. Martínez-Aparicio

In this paper, we study the behavior of multiple continua of solutions to the semilinear elliptic problem \begin{equation*} \begin{cases} -\Delta u = \lambda f(u) &\text{ in } \Omega, u=0 &\text{ on } \partial\Omega, \end{cases} \end{equation*} where $\Omega$ is a bounded open subset of $\re^N$ and $f$ is a nonnegative continuous real function with multiple

Andrei Semenov, Philip Zmushko, Alexander Pichugin, Aleksandr Beznosikov

Vertical Federated Learning (VFL) aims to enable collaborative training of deep learning models while maintaining privacy protection. However, the VFL procedure still has components that are vulnerable to attacks by malicious parties. In our work, we consider feature reconstruction attacks, a common risk targeting input data compromise. We theoretically clai

Jingxuan Li, Jiaqi Miao, Alan C. H. Tsang

Self-regulated actuators harness material intelligence to enable complex deformations and dynamics, representing a significant advancement in automated soft robotics. However, investigations on self-regulated soft actuators, particularly those using simplified actuation modules such as a unidirectional light beam, remain limited. Here, we present a design pa

Luis Romero-Ben, Paul Irofti, Florin Stoican, Vicenç Puig

Leakage in water systems results in significant daily water losses, degrading service quality, increasing costs, and aggravating environmental problems. Most leak localization methods rely solely on pressure data, missing valuable information from other sensor types. This article proposes a hydraulic state estimation methodology based on a dual Unscented Kal

Alexander G. Abanov, Dimitri M. Gangardt

The emptiness formation problem is addressed for a one-dimensional quantum polytropic gas characterized by an arbitrary polytropic index $\gamma$, which defines the equation of state $P \sim \rho^\gamma$, where $P$ is the pressure and $\rho$ is the density. The problem involves determining the probability of the spontaneous formation of an empty interval in