March 2025 arXiv papers — page 29

Albert Cabot, Federico Carollo, Igor Lesanovsky

Many-body quantum systems can exhibit collective effects that enhance the sensitivity of parameter estimation protocols. An example is provided by resonantly driven two-level atoms subject to collective dissipation, which can display a transition between a stationary phase and a time-crystal one. Previous work has shown that the light emitted in the time-cry

Cosmin Pohoata, Daniel G. Zhu

We introduce a higher-uniformity analogue of graphic zonotopes and permutohedra. Specifically, given a $(d+1)$-uniform hypergraph $H$, we define its hypergraphic zonotope $\mathcal{Z}_H$, and when $H$ is the complete $(d+1)$-uniform hypergraph $K^{(d+1)}_n$, we call its hypergraphic zonotope the acyclohedron $\mathcal{A}_{n,d}$. We express the volume of $\ma

Yan Xia, Xiaowei Zhou, Etienne Vouga, Qixing Huang

In this paper, we introduce a method for reconstructing 3D humans from a single image using a biomechanically accurate skeleton model. To achieve this, we train a transformer that takes an image as input and estimates the parameters of the model. Due to the lack of training data for this task, we build a pipeline to produce pseudo ground truth model paramete

Eylon Persky, Minhao He, Jiaqi Cai, Takashi Taniguchi

Flat bands in graphene-based moir\'e structures host a wide range of emerging strongly correlated and topological phenomena. Optically probing and controlling them can reveal important information such as symmetry and dynamics, but have so far been challenging due to the small energy gap compared to optical wavelengths. Here, we report near infrared optical

Shitian Zhao, Qilong Wu, Xinyue Li, Bo Zhang

We introduce LeX-Art, a comprehensive suite for high-quality text-image synthesis that systematically bridges the gap between prompt expressiveness and text rendering fidelity. Our approach follows a data-centric paradigm, constructing a high-quality data synthesis pipeline based on Deepseek-R1 to curate LeX-10K, a dataset of 10K high-resolution, aesthetical

Frank Ernesto Quintela Rodriguez, Francesco Anna Mele, Salvatore Francesco Emanuele Oliviero, Vittorio Giovannetti

Quantum thermodynamics is often formulated as a theory with constrained access to operations and resources. In this manuscript, we find a closed formula for the Gaussian ergotropy, i.e. the maximum energy that can be extracted from bosonic systems governed by quadratic Hamiltonians by means of Gaussian unitaries only. This formula resembles the well-known ei

Aniket Didolkar, Andrii Zadaianchuk, Rabiul Awal, Maximilian Seitzer

Object-centric representation learning aims to decompose visual scenes into fixed-size vectors called "slots" or "object files", where each slot captures a distinct object. Current state-of-the-art object-centric models have shown remarkable success in object discovery in diverse domains, including complex real-world scenes. However, these models suffer from

Johannes V. Roth, Yunxin Ye, Sören Schlichting, Lorenz von Smekal

In this work we study the quark-meson model within a real-time formulation of the functional renormalization group (FRG) on the Schwinger-Keldysh contour. First, we discuss in detail the symmetry of thermal equilibrium for the fermionic sector of the Keldysh action. We take into account dissipation for the bosonic degrees of freedom in the spirit of the Cald

Yuhan Zhang, Mengchen Zhang, Tong Wu, Tengfei Wang

3D generation is experiencing rapid advancements, while the development of 3D evaluation has not kept pace. How to keep automatic evaluation equitably aligned with human perception has become a well-recognized challenge. Recent advances in the field of language and image generation have explored human preferences and showcased respectable fitting ability. Ho

Ryo Sawada

Pair-instability supernovae (PISNe) are predicted thermonuclear explosions of massive stars with helium core masses exceeding $\sim 65M_\odot$ and synthesize substantial amounts of radioactive $\mathrm{^{56}Ni}$ ($M(\mathrm{^{56}Ni})\sim60M_\odot$ in extreme cases). To investigate their observational signatures, we developed a multi-D Monte Carlo radiation t

D. A. Dunne, K. A. Cleary, P. C. Breysse, D. T. Chung

Line-intensity mapping (LIM) is a growing technique that measures the integrated spectral-line emission from unresolved galaxies over a three-dimensional region of the Universe. Although LIM experiments ultimately aim to provide powerful cosmological constraints via auto-correlation, many LIM experiments are also designed to take advantage of overlapping gal

Loïc Bramley, Lotte Hollands, Subrabalan Murugesan

In these lectures we detail the interplay between the low-energy dynamics of quantum field theories with four supercharges and the exact WKB analysis. This exposition may be the first comprehensive account of this connection and includes new arguments and results. The lectures start with the introduction of massive two-dimensional $\mathcal{N}=(2,2)$ theorie

Maximilian Lutz, Lorenzo Piroli, Georgios Styliaris, J. Ignacio Cirac

We propose applying the adiabatic algorithm to prepare high-energy eigenstates of integrable models on a quantum computer. We first review the standard adiabatic algorithm to prepare ground states in each magnetization sector of the prototypical XXZ Heisenberg chain. Based on the thermodynamic Bethe ansatz, we show that the algorithm circuit depth is polynom

Gia Dvali, Michael Zantedeschi, Sebastian Zell

Mounting theoretical evidence suggests that black holes are subjected to the memory burden effect, implying that after certain time the information stored in them suppresses the decay rate. This effect opens up a new window for small primordial black holes (PBHs) below $10^{15}\,{\rm g}$ as dark matter. We show that the smooth transition from semi-classical

H. Z. Shen, Cheng Shang, Yan-Hui Zhou, X. X. Yi

Non-Markovian dynamics go beyond the Markovian approximation by capturing memory effects and information backflow in open quantum systems, which are crucial for describing realistic physical processes. In this work, we study the exact non-Markovian dynamics of a driven cavity coupled to an anisotropic three-dimensional photonic-crystal environment via counte

Juan M. Espejo Salcedo, Stavros Pastras, Josef Vácha, Claudia Pulsoni

The way in which radial flows shape galaxy structure and evolution remains an open question. Internal drivers of such flows, such as bars and spiral arms, known to mediate gas flows in the local Universe, are now observable at high redshift thanks to JWST's unobscured view. We investigated the morphology of massive star-forming galaxies at 0.8<z<1.3 and 2.0<

Kailin Li, Puhao Li, Tengyu Liu, Yuyang Li

Human hands play a central role in interacting, motivating increasing research in dexterous robotic manipulation. Data-driven embodied AI algorithms demand precise, large-scale, human-like manipulation sequences, which are challenging to obtain with conventional reinforcement learning or real-world teleoperation. To address this, we introduce ManipTrans, a n

Tillmann Bühler, Barbara Dembin, Ritvik Ramanan Radhakrishnan, Franco Severo

We study Voronoi percolation on a large class of $d$-dimensional Riemannian manifolds, which includes the hyperbolic spaces $\mathbb{H}^d$, $d\geq 2$. We prove that as the intensity $\lambda$ of the underlying Poisson point process tends to infinity, both critical parameters $p_c(M,\lambda)$ and $p_u(M,\lambda)$ converge to the Euclidean critical parameter $

James M. Sullivan, Uros Seljak

Primordial non-Gaussianity (PNG) is a signature of fundamental physics in the early universe that is probed by cosmological observations. It is well known that the local type of PNG generates a strong signal in the two-point function of large-scale structure tracers, such as galaxies. This signal, often termed ``scale-dependent bias'' is a generic feature of

Arsham Gholamzadeh Khoee, Shuai Wang, Robert Feldt, Dhasarathy Parthasarathy

Ensuring reliable data-driven decisions is crucial in domains where analytical accuracy directly impacts safety, compliance, or operational outcomes. Decision support in such domains relies on large tabular datasets, where manual analysis is slow, costly, and error-prone. While Large Language Models (LLMs) offer promising automation potential, they face chal

Suzanne Schlich

In this paper, we study representations from the four-punctured sphere group into isometry groups of Gromov-hyperbolic spaces. We prove that the set of simple-stable representations (in analogy with Minsky's notion of primitive-stability) and the set of Bowditch representations (inspired by Bowditch's work on the free group of rank two, generalized by Tan, W

Junjie Dong, Gabriel-Darius Mardaru, Paul D. Asimow, Lars P. Stixrude

We present globally inverted pressure-temperature (P-T) phase diagrams up to 5,000 GPa for four fundamental planetary materials, Fe, MgO, SiO2, and MgSiO3, derived from logistic regression and supervised learning, together with an experimental phase equilibria database. These new P-T phase diagrams provide a solution to long-standing disputes about their mel

Jacob Holm, Wojciech Nadara, Eva Rotenberg, Marek Sokołowski

We present a deterministic fully-dynamic data structure for maintaining information about the cut-vertices in a graph; i.e. the vertices whose removal would disconnect the graph. Our data structure supports insertion and deletion of edges, as well as queries to whether a pair of connected vertices are either biconnected, or can be separated by a cutvertex, a

Xianglong He, Zi-Xin Zou, Chia-Hao Chen, Yuan-Chen Guo

Creating high-fidelity 3D meshes with arbitrary topology, including open surfaces and complex interiors, remains a significant challenge. Existing implicit field methods often require costly and detail-degrading watertight conversion, while other approaches struggle with high resolutions. This paper introduces SparseFlex, a novel sparse-structured isosurface

Corin Lee, Tereso del Río, Hamid Rahkooy

CylindricalAlgebraicDecomposition.m2 is the first implementation of Cylindrical Algebraic Decomposition (CAD) in Macaulay2. CAD decomposes space into 'cells' where input polynomials are sign-invariant. This package computes an Open CAD (full-dimensional cells only) for sets of real polynomials with rational coefficients, enabling users to solve existential p

Yongce Li, Chung-En Sun, Tsui-Wei Weng

Large language Models (LLMs) have demonstrated remarkable skills across various domains. Understanding the mechanisms behind their abilities and implementing controls over them is becoming increasingly important for developing better models. In this paper, we focus on skill unlearning in LLMs, specifically unlearning a particular skill while retaining their

Zhicheng Lee, Shulin Cao, Jinxin Liu, Jiajie Zhang

Large Reasoning Models (LRMs) exhibit remarkable reasoning abilities but rely primarily on parametric knowledge, limiting factual accuracy. While recent works equip reinforcement learning (RL)-based LRMs with retrieval capabilities, they suffer from overthinking and lack robustness in reasoning, reducing their effectiveness in question answering (QA) tasks.

Michal Moravec, Graham Baker, Maja D. Bachmann, Aaron Sharpe

Studies of electronic transport in width-restricted channels of PdCoO$_2$ have recently revealed a novel `directional ballistic' regime, in which ballistic propagation of electrons on an anisotropic Fermi surface breaks the symmetries of bulk transport. Here we introduce a magnetic field to this regime, in channels of PdCoO$_2$ and PtCoO$_2$ along two crysta

S. Munshi, F. G. Mertens, L. V. E. Koopmans, M. Mevius

Radio-frequency interference (RFI) is a major systematic limitation in radio astronomy, particularly for science cases requiring high sensitivity, such as 21 cm cosmology. Traditionally, RFI is dealt with by identifying its signature in the dynamic spectra of visibility data and flagging strongly affected regions. However, for RFI sources that do not occupy

Nadav Cohen, Itzik Klein

The accurate navigation of autonomous underwater vehicles critically depends on the precision of Doppler velocity log (DVL) velocity measurements. Recent advancements in deep learning have demonstrated significant potential in improving DVL outputs by leveraging spatiotemporal dependencies across multiple sensor modalities. However, integrating these estimat

Nathaniel Tamminga, Scott Feister, Kyle D. Frische, Ronak Desai

Ultra-intense laser-matter interactions are often difficult to predict from first principles because of the complexity of plasma processes and the many degrees of freedom relating to the laser and target parameters. An important approach to controlling and optimizing ultra-intense laser interactions involves gathering large data sets and using this data to t

Mallika Garg, Debashis Ghosh, Pyari Mohan Pradhan

Occlusion is one of the challenging issues when estimating 3D hand pose. This problem becomes more prominent when hand interacts with an object or two hands are involved. In the past works, much attention has not been given to these occluded regions. But these regions contain important and beneficial information that is vital for 3D hand pose estimation. Thu

Alessandro Buratto, Elia Guerra, Marco Miozzo, Paolo Dini

The Internet of Things requires intelligent decision making in many scenarios. To this end, resources available at the individual nodes for sensing or computing, or both, can be leveraged. This results in approaches known as participatory sensing and federated learning, respectively. We investigate the simultaneous implementation of both, through a distribut

Jaywon Koo, Jefferson Hernandez, Moayed Haji-Ali, Ziyan Yang

Evaluating text-to-image and text-to-video models is challenging due to a fundamental disconnect: established metrics fail to jointly measure visual quality and semantic alignment with text, leading to a poor correlation with human judgments. To address this critical issue, we propose cFreD, a general metric based on a Conditional Fr\'echet Distance that uni

Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag, Soumya Suvra Ghosal

Alignment of Large Language models (LLMs) is crucial for safe and trustworthy deployment in applications. Reinforcement learning from human feedback (RLHF) has emerged as an effective technique to align LLMs to human preferences and broader utilities, but it requires updating billions of model parameters, which is computationally expensive. Controlled Decodi

A. Robson, P. Roloff, J. de Blas

The staging scenario for CLIC has been updated following new studies of the beam emittance through the accelerator chain, which has resulted in higher expected luminosities, and a change in baseline to a 100 Hz repetition rate at the initial energy stage. Here, the Higgs coupling sensitivities are updated for the new staging plan.

Martin Metodiev, Maarten Marsman, Lourens Waldorp, Quentin F. Gronau

The fact that redundant information does not update a rational belief implies that rational beliefs are updated using Bayes rule. In the framework of Hild (1998a), this is true under mild conditions for discrete, continuous, and arbitrary measure spaces. We prove this result and illustrate it with two examples.

Iuri Macocco, Nora Graichen, Gemma Boleda, Marco Baroni

We study last-layer outlier dimensions, i.e. dimensions that display extreme activations for the majority of inputs. We show that outlier dimensions arise in many different modern language models, and trace their function back to the heuristic of constantly predicting frequent words. We further show how a model can block this heuristic when it is not context

Jiefu Ou, William Gantt Walden, Kate Sanders, Zhengping Jiang

A core part of scientific peer review involves providing expert critiques that directly assess the scientific claims a paper makes. While it is now possible to automatically generate plausible (if generic) reviews, ensuring that these reviews are sound and grounded in the papers' claims remains challenging. To facilitate LLM benchmarking on these challenges,

Jeremy Karam, Michiko S. Fujii, Alison Sills

We perform a high resolution zoom-in simulation of star cluster assembly including the merger of two sub-clusters with initial conditions taken from previous large scale giant molecular cloud (GMC) simulations. We couple hydrodynamics to N-body dynamics to simulate the individual stars themselves, and the gas-rich environment in which they evolve. We include

Mauricio Olivares, Tomasz Olma, Daniel Wilhelm

This paper proposes a nonparametric test of pairwise independence of one random variable from a large pool of other random variables. The test statistic is the maximum of several Chatterjee's rank correlations and critical values are computed via a block multiplier bootstrap. We show in simulations that other popular tests based on distance covariances do no

Pietro Tropeano, Maria Maistro, Tuukka Ruotsalo, Christina Lioma

Language Model (LM) pruning compresses the model by removing weights, nodes, or other parts of its architecture. Typically, pruning focuses on the resulting efficiency gains at the cost of effectiveness. However, when looking at how individual data points are affected by pruning, it turns out that a particular subset of data points always bears most of the b

Adam Gee, Sydney O. Seese, James P. Curley, Owen G. Ward

The presence or absence of winner-loser effects is a widely discussed phenomenon across both sports and psychology research. Investigation of such effects is often hampered by the limited availability of data. Online chess has exploded in popularity in recent years and provides vast amounts of data which can be used to explore this question. With a hierarchi

Rizwan Ullah, Andres Barrio-Zhang, Arezoo M. Ardekani

Acoustic pressure nodes in acoustophoretic devices are crucial for applications in tissue engineering, cell analysis, and particle trapping. Typically, a single primary node forms at the half-wavelength resonance condition, while its shape and position are constrained by the dimensions of the channel. The generation of additional nodes, along with control ov

Hans G. Rinderknecht, E. Dill, A. J. MacLeod, B. King

Stimulated photon-photon scattering is a predicted consequence of quantum electrodynamics that has yet to be measured directly. Measuring the cross-section for stimulated photon-photon scattering is the aim of a flagship experiment for NSF OPAL, a proposed laser user facility with two, 25-PW beamlines. We present optimized experimental designs for achieving

Alexander Gribov

This paper focuses on computing the directional extremal boundary of a union of equal-radius circles. We introduce an efficient algorithm that accurately determines this boundary by analyzing the intersections and dominant relationships among the circles. The algorithm has time complexity of O(n log n).

Boyang Yang, Jiadong Ren, Shunfu Jin, Yang Liu

Repository-level software repair faces challenges in bridging semantic gaps between issue descriptions and code patches. Existing approaches, which primarily rely on large language models (LLMs), are hindered by semantic ambiguities, limited understanding of structural context, and insufficient reasoning capabilities. To address these limitations, we propose

Arsh Jha

This paper introduces a novel framework that combines traditional centrality measures with eigenvalue spectra and diffusion processes for a more comprehensive analysis of complex networks. While centrality measures such as degree, closeness, and betweenness have been commonly used to assess nodal importance, they provide limited insight into dynamic network

Felix Stollenwerk

Layer normalization (LN) is an essential component of modern neural networks. While many alternative techniques have been proposed, none of them have succeeded in replacing LN so far. The latest suggestion in this line of research is a dynamic activation function called Dynamic Tanh (DyT). Although it is empirically well-motivated and appealing from a practi

Robert A. Lawrence, Matt I. J. Probert

Thin film effects on the Magnetocrystalline Anisotropy Energy (MAE) of MnN were studied using density functional theory (DFT). Initially, strain effects on bulk MnN were considered as a proxy for lattice-matching induced strain and a linear relationship between the $c/a$ ratio and the MAE was found. A fundamental explanation for this relationship in terms of

Ashish Kumar Meena, Sung Kei Li, Adi Zitrin, Patrick L. Kelly

The Flashlights program with the Hubble Space Telescope imaged the six Hubble Frontier Fields galaxy clusters in two epochs and detected twenty transients. These are primarily expected to be caustic-crossing events (CCEs) where bright stars in distant lensed galaxies, typically at redshift $z\approx1$--3, get temporarily magnified close to cluster caustics.

Eugen Bronasco, Adrien Busnot Laurent, Baptiste Huguet

We present a new class of numerical methods for solving stochastic differential equations with additive noise on general Riemannian manifolds with high weak order of accuracy. In opposition to the popular approach with projection methods, the proposed methods are intrinsic: they only rely on geometric operations and avoid coordinates and embeddings. We provi

Artemii Redkin, Zdravko Dugonjic, Mike Lambeta, Roberto Calandra

Vision-based tactile sensors use structured light to measure deformation in their elastomeric interface. Until now, vision-based tactile sensors such as DIGIT and GelSight have been using a single, static pattern of structured light tuned to the specific form factor of the sensor. In this work, we investigate the effectiveness of dynamic illumination pattern

Timo Pohl, Pavel Novák, Marc Ohm, Michael Meier

The disconnect between distributed software artifacts and their supposed source code enables attackers to leverage the build process for inserting malicious functionality. Past research in this field focuses on compiled language ecosystems, mostly analysing Linux distribution packages. However, the popular scripting language ecosystems potentially face uniqu

Yan-Ying Chen, Yue Weng, Alexandre Filipowicz, Rumen Iliev

Human decision making can be challenging to predict because decisions are affected by a number of complex factors. Adding to this complexity, decision-making processes can differ considerably between individuals, and methods aimed at predicting human decisions need to take individual differences into account. Behavioral science offers methods by which to mea

Bernhard Böhmler

Let $G$ be a finite group of even order, let $k$ be an algebraically closed field of characteristic $2$, and let $B$ be a block of the group algebra $kG$ which is of domestic representation type. Up to splendid Morita equivalence, precisely three cases can occur: $kV_4$, $k\mathfrak{A}_4$ and the principal block of $k\mathfrak{A}_5$. In each case, given the

Hongyi Zeng, Wenxuan Liu, Tianhua Xia, Jinhui Chen

Instance segmentation is essential for augmented reality and virtual reality (AR/VR) as it enables precise object recognition and interaction, enhancing the integration of virtual and real-world elements for an immersive experience. However, the high computational overhead of segmentation limits its application on resource-constrained AR/VR devices, causing

Yoav Rotman, Luis Welbanks, Michael R. Line, Peter McGill

Atmospheric retrievals are essential tools for interpreting exoplanet transmission and eclipse spectra, enabling quantitative constraints on the chemical composition, aerosol properties, and thermal structure of planetary atmospheres. The James Webb Space Telescope (JWST) offers unprecedented spectral precision, resolution, and wavelength coverage, unlocking

Corentin Lemoine, Rafael Ballabriga, Eric Buschmann, Michael Campbell

CERN's strategic R&D programme on technologies for future experiments recently started investigating the TPSCo 65nm ISC CMOS imaging process for monolithic active pixels sensors for application in high energy physics. In collaboration with the ALICE experiment and other institutes, several prototypes demonstrated excellent performance, qualifying the technol

Jun Jiang, Rui Zhang, Kiran Prasai, Riccardo Bassiri

The mechanical loss angle of amorphous TiO$_2$-doped GeO$_2$ can be lower than 10$^{-4}$, making it a candidate for Laser Interferometer Gravitational-wave Observatory (LIGO) mirror coatings. Amorphous oxides have complex atomic structures that are influenced by various factors, including doping concentration, preparation, and thermal history, resulting in d

Linda Feeken, Martin Fränzle

The synthesis of reactive systems aims for the automated construction of strategies for systems that interact with their environment. Whereas the synthesis approach has the potential to change the development of reactive systems significantly due to the avoidance of manual implementation, it still suffers from a lack of efficient synthesis algorithms for man

Daniele Barbera, Filippo Boni, Simone Dovetta, Lorenzo Tentarelli

We investigate normalized solutions for doubly nonlinear Schr\"odinger equations on the real line with a defocusing standard nonlinearity and a focusing nonlinear point interaction of $\delta$-type at the origin. We provide a complete characterization of existence and uniqueness for normalized solutions and for energy ground states for every value of the non

Liuyue Xie, Avik Kuthiala, George Z. Wei, Ce Zheng

We introduce MAVERIX (Multimodal audiovisual Evaluation and Recognition IndeX), a unified benchmark to probe the video understanding in multimodal LLMs, encompassing video, audio, text inputs with human performance baselines. Although recent advancements in models with vision and audio understanding capabilities have shown substantial progress, the field lac

Mohsen Yarmohammadi, Ulrich Zülicke, Jamal Berakdar, Jacob Linder

Altermagnets are known in spintronics for their intrinsic spin-splitting and unconventional magnetic responses, particularly to magnetic impurities. However, effectively controlling the magnetic exchange interactions in altermagnets is challenging for practical applications. Here, we propose using circularly polarized light to tune the Ruderman-Kittel-Kasuya

Alessandro Conti, Massimiliano Mancini, Enrico Fini, Yiming Wang

Traditional image classification requires a predefined list of semantic categories. In contrast, Large Multimodal Models (LMMs) can sidestep this requirement by classifying images directly using natural language (e.g., answering the prompt "What is the main object in the image?"). Despite this remarkable capability, most existing studies on LMM classificatio

Lorenzo Clemente

A formal series in noncommuting variables $\Sigma$ over the rationals is a mapping $\Sigma^* \to \mathbb Q$. We say that a series is commutative if the value in the output does not depend on the order of the symbols in the input. The commutativity problem for a class of series takes as input a (finite presentation of) a series from the class and amounts to e

Wenqi Zhang, Mengna Wang, Gangao Liu, Xu Huixin

Recent advances in deep thinking models have demonstrated remarkable reasoning capabilities on mathematical and coding tasks. However, their effectiveness in embodied domains which require continuous interaction with environments through image action interleaved trajectories remains largely -unexplored. We present Embodied Reasoner, a model that extends o1 s

Jiahe Qian, Yaoyu Fang, Jinkui Hao, Bo Zhou

Accurate segmentation of cell nuclei in histopathology images is essential for numerous biomedical research and clinical applications. However, existing cell nucleus segmentation methods only consider a single dataset (i.e., primary domain), while neglecting to leverage supplementary data from diverse sources (i.e., auxiliary domains) to reduce overfitting a

Zhiyuan Ma, Xinyue Liang, Rongyuan Wu, Xiangyu Zhu

It is highly desirable to obtain a model that can generate high-quality 3D meshes from text prompts in just seconds. While recent attempts have adapted pre-trained text-to-image diffusion models, such as Stable Diffusion (SD), into generators of 3D representations (e.g., Triplane), they often suffer from poor quality due to the lack of sufficient high-qualit

R. Ovcharenko, B. P. Fingerhut

Path integral methods, like the quasi-adiabatic propagator path integral (QUAPI), are widely used in general-purpose and highly accurate numerical benchmark simulations of open quantum systems, particularly in regimes inaccessible to perturbative methods. Nevertheless, the applicability of the QUAPI method to realistic systems of interest is restricted by th

Daniel Bermuth, Alexander Poeppel, Wolfgang Reif

The integration of multi-view imaging and pose estimation represents a significant advance in computer vision applications, offering new possibilities for understanding human movement and interactions. This work presents a new algorithm that improves multi-view multi-person pose estimation, focusing on fast triangulation speeds and good generalization capabi

Aleksi Anttila, Søren Brinck Knudstorp

We prove expressive completeness results for convex propositional and modal team logics, where a logic is convex if, for each formula, if it is true in two teams $t$ and $u$ and $t\subseteq s\subseteq u$, then it is also true in $s$. We introduce multiple propositional/modal logics which are expressively complete for the class of all convex propositional/mod

Nikin~Matharaarachchi, Muhammad~Fermi Pasha, Sonya~Coleman, Kah PengWong

Micro-expressions are short bursts of emotion that are difficult to hide. Their detection in children is an important cue to assist psychotherapists in conducting better therapy. However, existing research on the detection of micro-expressions has focused on adults, whose expressions differ in their characteristics from those of children. The lack of researc

Alex Preston, Graceson Aufderheide, Will Ballard, Richard Mawhorter

New high-precision microwave spectroscopic measurements and analysis of rotational energy level transitions in the ground vibronic state of the open-shell BaF molecule are reported with the purpose of contributing to studies of physics beyond the Standard Model. BaF is currently among the key candidate molecules being examined in the searches for a measurabl

Jiten Dhandha, Anastasia Fialkov, Thomas Gessey-Jones, Harry T. J. Bevins

In the current era of JWST, we continue to uncover a wealth of information about the Universe deep into the Epoch of Reionization. In this work, we use a suite of simulations with 21cmSPACE, to explore the astrophysical properties of early galaxies and their imprint on high-redshift observables. Our analysis incorporates a range of multi-wavelength datasets

Yuichi Kamata, Quoc Hoan Tran, Yasuhiro Endo, Hirotaka Oshima

The Transformer model, renowned for its powerful attention mechanism, has achieved state-of-the-art performance in various artificial intelligence tasks but faces challenges such as high computational cost and memory usage. Researchers are exploring quantum computing to enhance the Transformer's design, though it still shows limited success with classical da

Roosmarijn de Wit, Jonathan Keeling, Brendon W. Lovett, Alex W. Chin

Methods for reconstructing the spectral density of a vibrational environment from experimental data can yield key insights into the impact of the environment on molecular function. Although such experimental methods exist, they generally only access vibrational modes that couple diagonally to the electron system. Here we present a method for extracting the s

Stanley Alama, Lia Bronsard, Xinyang Lu, Chong Wang

We study a two-dimensional inhibitory ternary system characterized by a free energy functional which combines an interface short-range interaction energy promoting micro-domain growth with a Coulomb-type long-range interaction energy which prevents micro-domains from unlimited spreading. Here we consider a scenario in which two species are dominant and one s

Hui Wang

In recent years, large language models (LLMs) have shown significant advancements in natural language processing (NLP), with strong capa-bilities in generation, comprehension, and rea-soning. These models have found applications in education, intelligent decision-making, and gaming. However, effectively utilizing LLMs for strategic planning and decision-maki

Siegfred Baluyot, Brian Conrey

Recently, Keating and the second author of this paper devised a heuristic for predicting asymptotic formulas for moments of the Riemann zeta-function $\zeta(s)$. Their approach indicates how lower twisted moments of $\zeta(s)$ may be used to evaluate higher moments. In this paper, we present a rigorous random matrix theory analogue of their heuristic. To do

Luis Wyss, Vincent Mallet, Wissam Karroucha, Karsten Borgwardt

The relationship between RNA structure and function has recently attracted interest within the deep learning community, a trend expected to intensify as nucleic acid structure models advance. Despite this momentum, the lack of standardized, accessible benchmarks for applying deep learning to RNA 3D structures hinders progress. To this end, we introduce a col

R. P. Malik

Within the framework of Becchi-Rouet-Stora-Tyutin (BRST) formalism, we show the existence of (i) a couple of off-shell nilpotent (i.e. fermionic) BRST and co-BRST symmetry transformations, and (ii) a full set of non-nilpotent (i.e. bosonic) symmetry transformations for an appropriate Lagrangian density that describes the combined system of the free Abelian 3

Yunze Xiao, Tingyu He, Lionel Z. Wang, Yiming Ma

This paper introduces JiraiBench, the first bilingual benchmark for evaluating large language models' effectiveness in detecting self-destructive content across Chinese and Japanese social media communities. Focusing on the transnational "Jirai" (landmine) online subculture that encompasses multiple forms of self-destructive behaviors including drug overdose

Zsolt Páles, Tomasz Szostok

The main aim of this paper is to study the functional inequality \begin{equation*} \int_{[0,1]}f\bigl((1-t)x+ty\bigr)d\mu(t)\geq 0, \qquad x,y\in I \mbox{ with } x<y, \end{equation*} for a continuous unknown function $f:I\to{\mathbb R}$, where $I$ is a nonempty open real interval and $\mu$ is a signed and bounded Borel measure on $[0,1]$. We derive necessary

Olivier Serris, Stéphane Doncieux, Olivier Sigaud

Several hierarchical reinforcement learning methods leverage planning to create a graph or sequences of intermediate goals, guiding a lower-level goal-conditioned (GC) policy to reach some final goals. The low-level policy is typically conditioned on the current goal, with the aim of reaching it as quickly as possible. However, this approach can fail when an

Nicolas Zucchet, Jörg Bornschein, Stephanie Chan, Andrew Lampinen

Large language models accumulate vast knowledge during pre-training, yet the dynamics governing this acquisition remain poorly understood. This work investigates the learning dynamics of language models on a synthetic factual recall task, uncovering three key findings: First, language models learn in three phases, exhibiting a performance plateau before acqu

I. M. Tsyfra, P. Sitko

Symmetry reductions of systems of two nonlinear partial differential equations are studied. We find ansatzes reducing system of partial differential equations to system of ordinary differential equations. The method is applied to system related to Korteweg -- de Vries (KdV) equation, and reaction-diffusion equations. We have also shown the possibility of con

Bastien Mallein, Francesco Paparella, Emmanuel Schertzer, Zsófia Talyigás

Biological evolution depends on the passing down to subsequent generations of genetic information encoding beneficial traits, and on the removal of unfit individuals by a selection mechanism. However, selection acts on phenotypes, and is affected by random contingencies. Thus, a combination of fitness and luck determines which individuals will successfully r

Jonathan Attard, Dylan Seychell

News videos require efficient content organisation and retrieval systems, but their unstructured nature poses significant challenges for automated processing. This paper presents a comprehensive comparative analysis of image, video, and audio classifiers for automated news video segmentation. This work presents the development and evaluation of multiple deep

Satvik Verma, Qun Wang, E. Wes Bethel

The widespread adoption of Internet of Things (IoT) devices has introduced significant cybersecurity challenges, particularly with the increasing frequency and sophistication of Distributed Denial of Service (DDoS) attacks. Traditional machine learning (ML) techniques often fall short in detecting such attacks due to the complexity of blended and evolving pa

Maximilian Ramgraber, Daniel Sharp, Mathieu Le Provost, Youssef Marzouk

Decision making under uncertainty is a cross-cutting challenge in science and engineering. Most approaches to this challenge employ probabilistic representations of uncertainty. In complicated systems accessible only via data or black-box models, however, these representations are rarely known. We discuss how to characterize and manipulate such representatio

Florian Galliot, Valentin Gledel, Aline Parreau

In the Avoider-Enforcer convention of positional games, two players, Avoider and Enforcer, take turns selecting vertices from a hypergraph H. Enforcer wins if, by the time all vertices of H have been selected, Avoider has completely filled an edge of H with her vertices; otherwise, Avoider wins. In this paper, we first give some general results, in particula

Yong Xie, Yunlian Sun, Hongwen Zhang, Yebin Liu

We present ReCoM, an efficient framework for generating high-fidelity and generalizable human body motions synchronized with speech. The core innovation lies in the Recurrent Embedded Transformer (RET), which integrates Dynamic Embedding Regularization (DER) into a Vision Transformer (ViT) core architecture to explicitly model co-speech motion dynamics. This

Yesmine Abdennadher, Giovanni Perin, Riccardo Mazzieri, Jacopo Pegoraro

Spiking Neural Networks (SNNs) are highly regarded for their energy efficiency, inherent activation sparsity, and suitability for real-time processing in edge devices. However, most current SNN methods adopt architectures resembling traditional artificial neural networks (ANNs), leading to suboptimal performance when applied to SNNs. While SNNs excel in ener

Panagiotis Chaidos, Giorgos Armeniakos, Sotirios Xydis, Dimitrios Soudris

Printed electronics have gained significant traction in recent years, presenting a viable path to integrating computing into everyday items, from disposable products to low-cost healthcare. However, the adoption of computing in these domains is hindered by strict area and power constraints, limiting the effectiveness of general-purpose microprocessors. This

Rajvee Sheth, Himanshu Beniwal, Mayank Singh

We introduce COMI-LINGUA, the largest manually annotated Hindi-English code-mixed dataset, comprising 125K+ high-quality instances across five core NLP tasks: Matrix Language Identification, Token-level Language Identification, Part-Of-Speech Tagging, Named Entity Recognition, and Machine Translation. Each instance is annotated by three bilingual annotators,

Allen Caldwell, John Farmer, Nelson Lopes, Alexander Pukhov

We discuss the main elements of a collider facility based on proton-driven plasma wakefield acceleration. We show that very competitive luminosities could be reached for high energy $e^+e^-$ colliders. A first set of parameters was developed for a Higgs Factory indicating that such a scheme is indeed potentially feasible. There are clearly many challenges to

Claudio Bettini, Azin Moradbeikie, Gabriele Civitarese

Researchers in pervasive computing have worked for decades on sensor-based human activity recognition (HAR). Among the digital health applications, the recognition of activities of daily living (ADL) in smart home environments enables the identification of behavioral changes that clinicians consider as a digital bio-marker of early stages of cognitive declin

Danaja Rutar, Alva Markelius, Konstantinos Voudouris, José Hernández-Orallo

One of the core components of our world models is 'intuitive physics' - an understanding of objects, space, and causality. This capability enables us to predict events, plan action and navigate environments, all of which rely on a composite sense of objecthood. Despite its importance, there is no single, unified account of objecthood, though multiple theoret

Davide Tebaldi, Roberto Zanasi

Bode plots represent an essential tool in control and systems engineering. In order to perform an initial qualitative analysis of the considered systems, the construction of asymptotic Bode plots is often sufficient. The standard methods for constructing asymptotic Bode plots are characterized by the same drawbacks: they are not systematic, may be not precis