December 2025 arXiv papers — page 104

Noah Messerli, Martin Hoferichter, Bai-Long Hoid, Simon Holz

The rare decays $\eta^{(\prime)}\to\ell^+\ell^-$, $\ell\in\{e,\mu\}$, are highly suppressed in the Standard Model, both by their chirality structure and the required loop attaching the lepton line to the $\eta^{(\prime)}\to\gamma^*\gamma^*$ matrix element. The latter is described by a single scalar function, the transition form factor, which has recently bee

Miguel Correia, Celina Pasiecznik

Most particles in nature are unstable, manifesting as resonances in scattering processes. Using analyticity and unitarity, we show nonperturbatively that resonances, defined as poles on higher Riemann sheets of scattering amplitudes, share basic properties with stable particles: (i) Universality, that a resonance generically appears in every S-matrix element

Rahel Lea Baumgartner, Pietro Pelliconi, Soumik Bandyopadhyay, Francesca Orsi

All-to-all interacting and disordered many-body systems are notoriously hard to simulate on quantum platforms, as interactions are commonly mediated by auxiliary degrees of freedom that lower the amount of disorder, introducing undesired correlations. In this work, we show how a Trotterization scheme can be effectively utilized to densify the disorder of the

Evgeni Grishin, Jet Winter, Jaime A. Alvarado-Montes

Hot Jupiters (HJs) are giant planets with orbital periods shorter than $10$ days, found around $\sim 0.5$-$1\%$ of Sun-like stars. Their origins remain debated despite decades of study. The high prevalence of stellar companions, the eccentricity distribution of 'Cold' Jupiters on longer orbits, and the wide range of stellar spin-orbit misalignments support h

Ciarán M. Gilligan-Lee, Yìlè Yīng, Jonathan Richens, David Schmid

We show that quantum oracles provide an advantage over classical oracles for answering classical counterfactual questions in causal models, or equivalently, for identifying unknown causal parameters such as distributions over functional dependences. In structural causal models with discrete classical variables, observational data and even ideal interventions

Susung Hong, Chongjian Ge, Zhifei Zhang, Jui-Hsien Wang

Video diffusion models have revolutionized generative video synthesis, but they are imprecise, slow, and can be opaque during generation -- keeping users in the dark for a prolonged period. In this work, we propose DiffusionBrowser, a model-agnostic, lightweight decoder framework that allows users to interactively generate previews at any point (timestep or

Yuanwen Yue, Damien Robert, Jianyuan Wang, Sunghwan Hong

Modern neural architectures for 3D point cloud processing contain both convolutional layers and attention blocks, but the best way to assemble them remains unclear. We analyse the role of different computational blocks in 3D point cloud networks and find an intuitive behaviour: convolution is adequate to extract low-level geometry at high-resolution in early

Jingfeng Yao, Yuda Song, Yucong Zhou, Xinggang Wang

The quality of the latent space in visual tokenizers (e.g., VAEs) is crucial for modern generative models. However, the standard reconstruction-based training paradigm produces a latent space that is biased towards low-level information, leading to a foundation flaw: better pixel-level accuracy does not lead to higher-quality generation. This implies that po

Juncheng Huo, Yunfan Gao, Xinxin Liu, Sa Wang

As processor designs grow more complex, verification remains bottlenecked by slow software simulation and low-quality random test stimuli. Recent research has applied software fuzzers to hardware verification, but these rely on semantically blind random mutations that may generate shallow, low-quality stimuli unable to explore complex behaviors. These limita

Dylan Phelps, Rodrigo Wilkens, Edward Gow-Smith, Lilian Hubner

Alzheimer's Disease (AD) is a progressive neurodegenerative condition that adversely affects cognitive abilities. Language-related changes can be automatically identified through the analysis of outputs from linguistic assessment tasks, such as picture description. Language models show promise as a basis for screening tools for AD, but their limited interpre

Daniel Zoran, Nikhil Parthasarathy, Yi Yang, Drew A Hudson

We present Recurrent Video Masked-Autoencoders (RVM): a novel approach to video representation learning that leverages recurrent computation to model the temporal structure of video data. RVM couples an asymmetric masking objective with a transformer-based recurrent neural network to aggregate information over time, training solely on a simple pixel reconstr

Lu Ling, Yunhao Ge, Yichen Sheng, Aniket Bera

Generalization remains the central challenge for interactive 3D scene generation. Existing learning-based approaches ground spatial understanding in limited scene dataset, restricting generalization to new layouts. We instead reprogram a pre-trained 3D instance generator to act as a scene level learner, replacing dataset-bounded supervision with model-centri

J. M. S. Donnellan, B. Pautasso, S. J. Oliver, M. Béthermin

The PRobe far-Infrared Mission for Astrophysics concept aims to map large areas with spectral coverage and sensitivities inaccessible to previous FIR space telescopes, covering 25-235um. We synthesise images representing a deep imaging survey, with realistic instrumental and confusion noise, reflecting the latest PRIMAger instrument specifications. We presen

Tianye Ding, Yiming Xie, Yiqing Liang, Moitreya Chatterjee

Recent feed-forward reconstruction models like VGGT and $\pi^3$ achieve impressive reconstruction quality but cannot process streaming videos due to quadratic memory complexity, limiting their practical deployment. While existing streaming methods address this through learned memory mechanisms or causal attention, they require extensive retraining and may no

Konstantinos Tanidis, David Alonso, Lance Miller, Joachim Harnois-Déraps

We present a quadratic estimator that detects and reconstructs spatially-varying multiplicative ($m-$) bias in weak lensing shear measurements, by exploiting the $EB$ mode coupling that it generates. The method combines $E$ and $B$ modes with inverse-variance weights, to yield an unbiased reconstruction of $m(\boldsymbol{\theta})$ to first order. We study th

Ziqi Ma, Hongqiao Chen, Yisong Yue, Georgia Gkioxari

Recent progress in image-to-3D has opened up immense possibilities for design, AR/VR, and robotics. However, to use AI-generated 3D assets in real applications, a critical requirement is the capability to edit them easily. We present a feedforward method, Steer3D, to add text steerability to image-to-3D models, which enables editing of generated 3D assets wi

David Ball

Modern AI systems lack a way to express and enforce requirements. Pre-training produces intelligence, and post-training optimizes preferences, but neither guarantees that models reliably satisfy explicit, context-dependent constraints. This missing abstraction explains why highly intelligent models routinely fail in deployment despite strong benchmark perfor

Baixiang Huang, Limeng Cui, Jiapeng Liu, Haoran Wang

Personalization is becoming indispensable for LLMs to align with individual user preferences and needs. Yet current approaches are often computationally expensive, data-intensive, susceptible to catastrophic forgetting, and prone to performance degradation in multi-turn interactions or when handling implicit queries. To address these challenges, we conceptua

Ziqian Tang, Chen Yang, Hanyu Xue, Haochen Yu

Gravity-induced entanglement (GIE) is widely regarded as key evidence of nonclassical gravity. Recent work, however, argues that a classical gravitational background can generate entanglement through virtual matter propagation between separated masses. Here we show that this mechanism is negligible once realistic matter dynamics is taken into account. For bo

Yiyi Cai, Xuangeng Chu, Xiwei Gao, Sitong Gong

We introduce Interactive Intelligence, a novel paradigm of digital human that is capable of personality-aligned expression, adaptive interaction, and self-evolution. To realize this, we present Mio (Multimodal Interactive Omni-Avatar), an end-to-end framework composed of five specialized modules: Thinker, Talker, Face Animator, Body Animator, and Renderer. T

Panagiotis Giannadakis, Matthew Elley, Raphael Flauger, Eugene A. Lim

We show that, for a given fixed value of the number of e-folds of the homogeneous solution, inflation succeeds with order unity inhomogeneities in the initial conditions above a characteristic value of the tensor-to-scalar ratio $r$. In practice, we work with an $\alpha$-attractor $T$-model and vary its characteristic scale $\mu$, keeping the initial inhomog

Kunhee Kim, NaHyeon Park, Kibeom Hong, Hyunjung Shim

Textual Inversion (TI) is an efficient approach to text-to-image personalization but often fails on complex prompts. We trace these failures to embedding norm inflation: learned tokens drift to out-of-distribution magnitudes, degrading prompt conditioning in pre-norm Transformers. Empirically, we show semantics are primarily encoded by direction in CLIP toke

Junwen Miao, Penghui Du, Yingying Fan, Yi Liu

Industrial anomaly detection (IAD) is challenging due to the subtle and highly localized nature of many defects, which single-pass vision--language models (VLMs) often fail to capture. Moreover, existing approaches lack mechanisms to actively acquire complementary evidence during inference. We propose AgentIAD, an agentic vision--language framework that enab

Álvaro Díaz Ramos, Garrett Ervin, Saharon Shelah

We study generalized sums of linear orders. These are binary operations that, given linear orders $A$ and $B$, return an order $A \oplus B$ that can be decomposed as an isomorphic copy of $A$ interleaved with a copy of $B$. We show that there is a rich array of associative sums different from the usual sum $+$ and its dual. The simplest of these sums arise f

Alexander Kriebitz, Caitlin Corrigan, Aive Pevkur, Alberto Santos Ferro

Cultural rights and the right to development are essential norms within the wider framework of international human rights law. However, recent technological advances in artificial intelligence (AI) and adjacent digital frontier technologies pose significant challenges to the protection and realization of these rights. This owes to the increasing influence of

Licheng Luo, Kaier Liang, Yu Xia, Mingyu Cai

While Temporal Logic provides a rigorous verification framework for robotics, it typically operates on trajectory-level signals and does not natively represent the object-centric geometric relations that are central to manipulation. Spatio-Temporal Logic (SpaTiaL) overcomes this by explicitly capturing geometric spatial requirements, making it a natural form

Tony Haddad

We give a simple inequality that compares the laws of two random variables taking values in a convex subset of a normed vector space. By combining this with Arratia's coupling, recently refined by Koukoulopoulos and the author, we obtain a general strategy to reduce the problem of finding an asymptotic formula for the number of integers whose prime facto

Guoqing Liu, Junren Li, Zihan Zhao, Eray Inanc

Solving computer-aided synthesis planning is essential for enabling fully automated, robot-assisted synthesis workflows and improving the efficiency of drug discovery. A key challenge, however, is bridging the gap between computational route design and practical laboratory execution, particularly the accurate prediction of viable experimental procedures for

Cristina Aggazzotti, Elizabeth Allyn Smith

Forensic scientists often need to identify an unknown speaker or writer in cases such as ransom calls, covert recordings, alleged suicide notes, or anonymous online communications, among many others. Speaker recognition in the speech domain usually examines phonetic or acoustic properties of a voice, and these methods can be accurate and robust under certain

Wenhan Chen, Sezer Karaoglu, Theo Gevers

Recent advances in diffusion-based generation techniques enable AI models to produce highly realistic videos, heightening the need for reliable detection mechanisms. However, existing detection methods provide only limited exploration of the 3D geometric patterns present in generated videos. In this paper, we use vanishing points as an explicit representatio

Yang Chu

We study the variational structure of the biased infinity Laplacian by introducing a notion of the $\beta$\textit{-Exponential Absolute Minimizing Extension} ($\beta$--AM) on arbitrary length space, which absolutely minimizing the exponential slope $$ L^{\beta}_u (E) := \beta \sup_{x,y \in E} \frac{u(y) - e^{-\beta |x-y|} u(x)}{1- e^{-\beta |x-y|}}. $$We als

Zihan Zhang, Sihan Chen, Mingfeng Chen, Jee Yung Park

Quantum geometry quantifies how the electron wavefunction evolves distinctly from conventional transport theory. In noncentrosymmetric materials, nonreciprocal transport with quantum geometric origin remains prominent with localized charge independent of vanished group velocity. The discovery of such nonreciprocal and nonlinear responses was realized by rece

Ljuben Mutafchiev, Steven Finch

Let $\mathcal{T}_n$ be the set of all mappings $T:[n]\to[n]$, where $[n]=\{1,2,\ldots,n\}$. The corresponding graph $G_T$ of $T$, called a functional digraph, is a union of disjoint connected components. Each component is a directed cycle of rooted labeled trees. We assume that each $T\in\mathcal{T}_n$ is chosen uniformly at random from the set $\mathcal{T}_

Robert Pinkston, Nikita Gourianov, Hirad Alipanah, Peyman Givi

Direct numerical simulation (DNS) of turbulent reactive flows has been the subject of significant research interest for several decades. Accurate prediction of the effects of turbulence on the rate of reactant conversion, and the subsequent influence of chemistry on hydrodynamics remain a challenge in combustion modeling. The key issue in DNS is to account f

Edmund Harriss, Henna Koivusalo, James J. Walton

Cut and project sets are obtained by projecting an irrational slice through a lattice to a lower dimensional subspace. Under standard conditions, the resulting pattern has no translational periods even though it retains some regularity of the lattice. Cut and project sets are one of the archetypical examples of patterns featuring aperiodic order, the other c

Mohammadreza Molavi, Mohammad Moein, Mohammadreza Tavakoli, Abdolali Faraji

As the online learning landscape evolves, the need for personalization is increasingly evident. Although educational resources are burgeoning, educators face challenges selecting materials that both align with intended learning outcomes and address diverse learner needs. Large Language Models (LLMs) are attracting growing interest for their potential to crea

Scott N. Genin, Ohyun Kwon, Seyyed Mehdi Hosseini Jenab, Seon-Jeong Lim

Molecular simulations are widely regarded as leading candidates to demonstrate quantum advantage--defined as the point at which quantum methods surpass classical approaches in either accuracy or scale. Yet the qubit counts and error rates required to realize such an advantage remain uncertain; resource estimates for ground-state electronic structure span ord

Davide Filippozzi, Alexandre Mayer, Nicolas Roy, Wei Fang

Chiral photonic metasurfaces provide unique capabilities for tailoring light-matter interactions, which are essential for next-generation photonic devices. Here, we report an advanced optimization framework that combines deep learning and evolutionary algorithms to significantly improve both the design and performance of chiral photonic nanostructures. Build

Richard J. Young

Safety alignment mechanisms in large language models prevent responses to harmful queries through learned refusal behavior, yet these same mechanisms impede legitimate research applications including cognitive modeling, adversarial testing, and security analysis. While abliteration techniques enable surgical removal of refusal representations through directi

John E. Ortega, Dhruv D. Joshi, Matt P. Borkowski

Large-language models (LLMs) have been shown to respond in a variety of ways for classification tasks outside of question-answering. LLM responses are sometimes called "hallucinations" since the output is not what is ex pected. Memorization strategies in LLMs are being studied in detail, with the goal of understanding how LLMs respond. We perform a deep dive

José Correia, Mark Hindmarsh, Joanes Lizarraga, Asier Lopez-Eiguren

Cosmic strings formed when the Peccei-Quinn symmetry breaks post-inflation are expected to emit axions throughout their lifetime. The details of the evolution of this network and the associated spectrum of axions are crucial for obtaining an accurate axion mass prediction, thus guiding searches at haloscopes. In a previous publication, we obtained evidence f

Haofan Dong, Ozgur B. Akan

Terahertz inter-satellite links (THz-ISL) offer unprecedented bandwidth for future space networks but face fundamental constraints from onboard power and thermal budgets. This paper establishes theoretical performance limits for MIMO Integrated Sensing and Communication (ISAC) systems under per-element constant-envelope (CE) transmission constraints. We demo

Leonard Susskind

In this paper I explain the relation between the need for observers in de Sitter space and the spontaneous breakdown of time-reversal symmetry.

Ali Partofard

We study the integral models of meta-unitary Shimura varieties through the lens of Scholze's fiber product conjecture. Reformulating Bultel's original construction in terms of moduli stacks of Shtukas and Igusa stacks, we prove the validity of the fiber product formula for this class of non-abelian type Shimura varieties, thereby generalizing the works of Zh

Antonio Junior Iovino, Gabriele Perna, Hardi Veermäe

LISA can observe cosmological millihertz (mHz) gravitational wave (GW) backgrounds that may offer a decisive test for asteroid-mass primordial black hole (PBH) dark matter (DM). In standard scenarios, failing to detect a scalar-induced gravitational wave (SIGW) background would exclude the last viable window for PBH DM formed through critical collapse. We sh

Sunghoon Jung, Minju Kum, Junghwan Lee

Motivated by the finiteness of de Sitter (dS) horizon entropy, we study how "bra-ket wormholes" modify correlation functions in gravitationally prepared states. Euclidean wormhole saddles in gravitational path integrals can generate non-factorizing contributions to correlation functions, as in replica-wormhole explanation of the Page curve and bra-ket-wormho

Nadav Kunievsky

The interpretation of coefficients from multivariate linear regression relies on the assumption that the conditional expectation function is linear in the variables. However, in many cases the underlying data generating process is nonlinear. This paper examines how to interpret regression coefficients under nonlinearity. We show that if the relationships bet

Raktim Gautam Goswami, Amir Bar, David Fan, Tsung-Yen Yang

Modeling dexterous hand-object interactions is challenging as it requires understanding how subtle finger motions influence the environment through contact with objects. While recent world models address interaction modeling, they typically rely on coarse action spaces that fail to capture fine-grained dexterity. We, therefore, introduce DexWM, a Dexterous I

Laura Kurek, Joshua Ashkinaze, Ceren Budak, Eric Gilbert

Can digital ads encourage users exposed to inaccurate information sources to follow accurate ones? We conduct a large-scale field experiment (N=28,582) on X, formerly Twitter, with users who follow accounts that spread health misinformation. Participants were exposed to four ad treatments varied on two dimensions: a neutral message versus a persuasive messag

Giovanni Ballarin, Lyudmila Grigoryeva, Yui Ching Li

Model combination is a powerful approach for achieving superior performance compared to selecting a single model. We study both theoretically and empirically the effectiveness of ensembles of Multi-Frequency Echo State Networks (MFESNs), which have been shown to achieve state-of-the-art macroeconomic time series forecasting results (Ballarin et al., 2024a).

Gabriel Vitorino de Andrade, Saulo Roberto dos Santos, Itallo Patrick Castro Alves da Silva, Emanuel Adler Medeiros Pereira

The validation and verification of artificial intelligence (AI) models through robustness assessment are essential to guarantee the reliable performance of intelligent systems facing real-world challenges, such as image corruptions including noise, blurring, and weather variations. Despite the global importance of mango (Mangifera indica L.), there is a lack

Manju, Stefano Olivares, Matteo G. A. Paris

Multiparameter quantum estimation becomes challenging when the parameters are incompatible, i.e., when their respective symmetric logarithmic derivatives do not commute, or when the model is sloppy, meaning that the quantum probe depends only on combinations of parameters leading to a degenerate or ill-conditioned Fisher information matrix. In this work, we

Michal Nazarczuk, Thomas Tanay, Arthur Moreau, Zhensong Zhang

This paper presents a new dataset for Novel View Synthesis, generated from a high-quality, animated film with stunning realism and intricate detail. Our dataset captures a variety of dynamic scenes, complete with detailed textures, lighting, and motion, making it ideal for training and evaluating cutting-edge 4D scene reconstruction and novel view generation

Joshua Enwright, Stefano Filipazzi, Yoshinori Gongyo, Joaquín Moraga

We define the nef complexity of a projective variety $X$. This invariant compares $\dim X+\rho(X)$ with the sum of the coefficients of nef partitions of $-K_X$. We prove that the nef complexity is non-negative and it is zero precisely for products of projective spaces. We classify smooth Fano threefolds with nef complexity at most one. In a similar vein, we

Junchao Zhu, Ruining Deng, Junlin Guo, Tianyuan Yao

Spatial transcriptomics (ST) is an emerging technology that enables researchers to investigate the molecular relationships underlying tissue morphology. However, acquiring ST data remains prohibitively expensive, and traditional fixed-grid sampling strategies lead to redundant measurements of morphologically similar or biologically uninformative regions, thu

Reza Gheissari, Aukosh Jagannath

We consider statistical tasks in high dimensions whose loss depends on the data only through its projection into a fixed-dimensional subspace spanned by the parameter vectors and certain ground truth vectors. This includes classifying mixture distributions with cross-entropy loss with one and two-layer networks, and learning single and multi-index models wit

Enrico Morgante, Riccardo Natale

We present a novel realization of axion kinetic misalignment, triggered by a Hubble-induced phase transition during a post-inflationary stiff (kination) era. A negative Ricci scalar flips the sign of a non-minimally coupled mass term for a non-minimally coupled complex field $\Phi$, driving its radial mode to large amplitudes via a tachyonic instability. At

Guransh Singh, Md Shah Fahad

Stuttering detection breaks down when disfluencies overlap. Existing parametric models struggle to distinguish complex, simultaneous disfluencies (e.g., a 'block' with a 'prolongation') due to the scarcity of these specific combinations in training data. While Retrieval-Augmented Generation (RAG) has revolutionized NLP by grounding models in external knowled

Sicheng He, Hang Li, Kivanc Ekici

Quasi-periodic trajectories with two or more incommensurate frequencies are ubiquitous in nonlinear dynamics, yet the classical Fourier-based time-spectral method is tied to strictly periodic responses. We introduce a torus time-spectral method that lifts the governing equations to an extended angular phase space, applies double-Fourier collocation on the in

Vernon Barger

Flavor hierarchies emerge from a single hierarchical parameter $B$ in a one-flavon Froggatt--Nielsen scheme. Fixing $B=5.357$ from charged-lepton ratios ($m_e:m_\mu:m_\tau\!\propto\!\epsilon^5:\epsilon^2:1$, $\epsilon=1/B$), we reproduce quark masses and CKM targets at $M_Z$ with $\ordone$ coefficients. The same $\epsilon$ gives viable lepton textures and be

Nikhil Pappu

We study non-interactive zero-knowledge proofs (NIZKs) for NP satisfying: 1) statistical soundness, 2) computational zero-knowledge and 3) certified-everlasting zero-knowledge (CE-ZK). The CE-ZK property allows a verifier of a quantum proof to revoke the proof in a way that can be checked (certified) by the prover. Conditioned on successful certification, th

Luca Vota, Luisa Errichiello

Departing from the dominant approach focused on individual and meso-level determinants, this paper develops a macroeconomic formalization of job insecurity within a New Keynesian framework in which the standard IS-NKPC-Taylor rule block is augmented with labor-market frictions. The model features partially informed private agents who receive a noisy signal a

Dev Prakash Jha, Raju K. George

We study memory-type null controllability for linear parabolic equations with hereditary terms and time-dependent control regions. In contrast with classical null controllability, systems with memory require the simultaneous annihilation of both the state and the accumulated memory at the terminal time in order to prevent post-control reactivation of the dyn

Parameshwar R. Pasnoori

In this paper we consider quantum Hamiltonians with time-dependent interaction strengths, and following the recently formulated generalized Bethe ansatz framework [P. R. Pasnoori, Phys. Rev. B 112, L060409 (2025)], we show that constraints imposed by integrability take the same form as the renormalization group flow equations corresponding to the respective

Romain Panis, Bruno Schapira

We consider Bernoulli percolation on $\mathbb Z^d$ with $d>6$. We prove an up-to-constant estimate for the critical two-point function restricted to a half-space. This completes previous results of Chatterjee and Hanson (Commun. Pure Appl. Math., 2021), and Chatterjee, Hanson, and Sosoe (Commun. Math. Phys., 2023), and solves a question asked by Hutchcroft,

Hunter Chen, Junming Guan, Erik van Zwet, Nikolaos Ignatiadis

We develop a statistical framework for empirical Bayes learning from selectively reported confidence intervals, and apply it to provide context for interpreting results published in MEDLINE abstracts. We use a collection of 326,060 z-scores from MEDLINE abstracts (2000-2018) as the input for an empirical Bayes analysis, with publication bias as a key methodo

Olga Aryasova, Ilya Pavlyukevich, Andrey Pilipenko

In this paper, we establish a general convergence theorem for solutions of multivariate stochastic differential equations with countably many singular terms expressed as integrals with respect to local times. The processes under consideration describe diffusions in the presence of semipermeable hyperplane interfaces. These interfaces may become sticky after

Andrew Welter, Ngoc Cuong Nguyen

We present scalable iterative solvers and preconditioning strategies for Hybridizable Discontinuous Galerkin (HDG) discretizations of partial differential equations (PDEs) on graphics processing units (GPUs). The HDG method is implemented using GPU-tailored algorithms in which local element degrees of freedom are eliminated in parallel, and the globally cond

Zefang Liu, Nam H. Nguyen, Yinzhu Quan, Shi-Xiong Zhang

Representing continuous time is a critical and under-explored challenge in modeling temporal event sequences with large language models (LLMs). Various strategies like byte-level representations or calendar tokens have been proposed. However, the optimal approach remains unclear, especially given the diverse statistical distributions of real-world event data

Ankit Sharma, Sayan Roy Gupta

Graph Neural Networks have demonstrated significant success in graph classification tasks, yet they often require substantial computational resources and struggle to capture global graph properties effectively. We introduce LightTopoGAT, a lightweight graph attention network that enhances node features through topological augmentation by incorporating node d

Javier Marín

When retrieval-augmented generation (RAG) systems hallucinate, what geometric trace does this leave in embedding space? We introduce the Semantic Grounding Index (SGI), defined as the ratio of angular distances from the response to the question versus the context on the unit hypersphere $\mathbb{S}^{d-1}$.Our central finding is \emph{semantic laziness}: hall

Laurenz Kremeyer, Bradley J. Siwick, Samuel Huberman

Deviations from diffusive heat transport in high thermal conductivity crystalline insulators are generally understood within the framework of the phonon Boltzmann Transport Equation. However, for low thermal conductivity materials with large primitive cells or strong anharmonicity, the recently developed Wigner Transport Equation is more appropriate as it in

Ali Khalesi, Petros Elia

This work introduces a hypergraph formulation that generalizes the classical paradigm of Bar-Yossef et al. to the multi-sender index coding (MSIC) setting. Central to the model is a 4-regular side-information hypergraph G, a new adjacency representation A_G = [A_1 ... A_N], and a simple fitting criterion for sub-hypergraph validity, in the presence of specia

Kean Chen, Nengkun Yu, Zhicheng Zhang

We study the estimation of an unknown quantum channel $\mathcal{E}$ with input dimension $d_1$, output dimension $d_2$ and Kraus rank at most $r$. We establish a connection between the query complexities in two models: (i) access to $\mathcal{E}$, and (ii) access to a random dilation of $\mathcal{E}$. Specifically, we show that for parallel (possibly coheren

Karl W. Koch, Stephan Krenn, Alexandra Hofer

eSignatures ensure data's authenticity, non-repudiation, and integrity. EU's eIDAS regulation specifies, e.g., advanced and qualified (QES) eSignatures. While eSignatures' concrete legal effects depend on the individual case, QESs constitute the highest level of technical protection and authenticity under eIDAS. QESs are based on a qualified certificate issu

P. L. S. Cambalame, B. J. C. Vieira, J. C. Waerenborgh, P. S. P. da Silva

We successfully synthesized a novel intermetallic compound $\rm CrFe_2Ge_2$ with the $\rm Fe_{13}Ge_{8}$-type crystal structure. A structural study is presented combining single-crystal X-ray diffraction and M\"{o}ssbauer spectroscopy analysis, confirming the presence of two distinct Fe sublattices. $\rm CrFe_2Ge_2$ exhibits a metallic ferromagnetic state wi

Laura B. Balzer, Mark J. van der Laan, Maya L. Petersen

Covariate adjustment is an approach to improve the precision of trial analyses by adjusting for baseline variables that are prognostic of the primary endpoint. Motivated by the SEARCH Universal HIV Test-and-Treat Trial (2013-2017), we tell our story of developing, evaluating, and implementing a machine learning-based approach for covariate adjustment. We pro

Afrah Shaahid, Muzammil Behzad

Underwater images are severely degraded by wavelength-dependent light absorption and scattering, resulting in color distortion, low contrast, and loss of fine details that hinder vision-based underwater applications. To address these challenges, we propose AquaDiff, a diffusion-based underwater image enhancement framework designed to correct chromatic distor

Felix J. Dorfner, Manon A. Dorster, Ryan Connolly, Oscar Gentilhomme

Foundation models have shown promise in medical imaging but remain underexplored for three-dimensional imaging modalities. No foundation model currently exists for Digital Breast Tomosynthesis (DBT), despite its use for breast cancer screening. To develop and evaluate a foundation model for DBT (DBT-DINO) across multiple clinical tasks and assess the impact

Boxin Wang, Chankyu Lee, Nayeon Lee, Sheng-Chieh Lin

Building general-purpose reasoning models with reinforcement learning (RL) entails substantial cross-domain heterogeneity, including large variation in inference-time response lengths and verification latency. Such variability complicates the RL infrastructure, slows training, and makes training curriculum (e.g., response length extension) and hyperparameter

José Luis Montaño Priede, Marek Grzelczak

The management of thermal effects in plasmonic nanostructures is frequently viewed as a detrimental waste rather than a useful, controllable entity. We show that optical coupling of plasmonic nanoparticles enables precise spatiotemporal control over nanoscale heating. Through numerical investigation of experimentally-achievable systems from individual nanopa

Marta Laguna, Juana M. Martínez-Heredia, Manuel G. Satué

Digital/Analog converters based on sigma-delta modulation are simple and unexpensive circuits featuring a signal bandwidth limited by speed constraints. Multi-bit modulators allow balancing complexity and speed by reducing the clock frequency and increasing the number of levels in the quantizer. In this case, the multi-bit digital to analog block (DAC) can r

Jianxiong Gao, Zhaoxi Chen, Xian Liu, Junhao Zhuang

Building video world models upon pretrained video generation systems represents an important yet challenging step toward general spatiotemporal intelligence. A world model should possess three essential properties: controllability, long-term visual quality, and temporal consistency. To this end, we take a progressive approach-first enhancing controllability

David H. Brooks, Deborah Baker, David M. Long. Paola Testa, Harry P. Warren

We discuss the evolution of solar coronal element abundances over an active region lifetime. Magneto-convection drives the complexity of magnetic fields that emerge above the photosphere. This complexity is dissipated, together with that of the overlying pre-existing fields, through dynamic events such as flares. A period of stable "ordinary" coronal heating

Jeongsoo Park, Sang-Wook Cheong, Xianghan Xu

We investigate nonreciprocal electrical transport in bulk single-crystalline Mo3Al2C, a material known to host crystallographic chirality, a polar charge-density-wave instability, and a superconducting transition near 8 K. Using AC transport measurements to analyze the first-harmonic and second-harmonic resistance responses, we observe a distinct nonreciproc

Haoyue Zhang, Meera Chappidi, Erolcan Sayar, Helen Richards

Recent deep learning frameworks in histopathology, particularly multiple instance learning (MIL) combined with pathology foundational models (PFMs), have shown strong performance. However, PFMs exhibit limitations on certain cancer or specimen types due to domain shifts - these cancer types were rarely used for pretraining or specimens contain tissue-based a

Angela Stallone, Ilaria Spassiani

Above the magnitude of completeness - the minimum threshold for which a 100\% detection rate is assumed - earthquake magnitudes are typically modeled as a continuous exponential distribution. In practice, however, earthquake catalogs report magnitudes with finite resolution, resulting in a discrete (geometric) distribution. To determine the magnitude of comp

Daniel Melcer, Qi Chen, Wen-Hao Chiang, Shweta Garg

A well-engineered prompt can increase the performance of large language models; automatic prompt optimization techniques aim to increase performance without requiring human effort to tune the prompts. One leading class of prompt optimization techniques introduces the analogy of textual gradients. We investigate the behavior of these textual gradient methods

Gulzhan Aldan, Igor Bargatin

We present a proof-of-concept study showing that buckled aluminized polyimide films perforated with millimeter-scale cuts can redirect normally incident light obliquely and generate net in-plane force components parallel to the global solar sail surface. We use finite element simulations to obtain the buckled shapes of different periodic unit cell geometries

Sarbari Mitra, Soumya Bhoumik

The cozero-divisor graph of a commutative ring $R$, denoted $\Gamma'(R)$, is the graph whose vertices are the non-zero and non-unit elements of $R$, with two distinct vertices $x$ and $y$ adjacent if and only if $x \notin Ry$ and $y \notin Rx$. This paper studies the structural properties of $\Gamma'(R)$ for the polynomial ring $R = \Z_n[x]/(x^2)$, where $n$

Simon Jacobsson

We consider sets of fixed CP, multilinear, and TT rank tensors, and derive conditions for when (the smooth parts of) these sets are smooth homogeneous manifolds. For CP and TT ranks, the conditions are essentially that the rank is sufficiently low. These homogeneous structures are then used to derive Riemannian metrics whose geodesics are both complete and e

Fu-Yun Wang, Hao Zhou, Liangzhe Yuan, Sanghyun Woo

The slow inference process of image diffusion models significantly degrades interactive user experiences. To address this, we introduce Diffusion Preview, a novel paradigm employing rapid, low-step sampling to generate preliminary outputs for user evaluation, deferring full-step refinement until the preview is deemed satisfactory. Existing acceleration metho

J. Schiappacasse-Ulloa, L. Berni, S. Lucatello, L. Magrini

Globular clusters (GCs) are fundamental tracers of the early assembly of the Milky Way (MW). They formed in diverse environments -- including both our Galaxy and dwarf galaxies -- retaining chemical and dynamical signatures that encode their origins and the merger history of the Galaxy. Although significant progress has been made in characterising GC chemist

Ignacio Huerta, Pablo Monzón

Building on the recent notion of non-uniform complete observability, and on the fact that this property ensures non-uniform exponential detectability, this paper establishes the converse implication under suitable additional assumptions. Specifically, we investigate conditions under which non-uniform exponential detectability guarantees non-uniform complete

Tejas Parasram Singar, Ivan Maggio-Aprile, Genda Gu, Christoph Renner

Understanding how superconductivity competes with other electronic phases in cuprates requires direct access to the hidden non-superconducting low temperature phase, for which Abrikosov vortices provide a unique local probe. We map the doping- and field-dependent evolution of vortex-core states in Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8+\delta}$ across a broad dopin

N. S. Mankoč Borštnik, H. B. Nielsen

Although the internal spaces describing spins and charges of fermions' and bosons' second-quantised fields have such different properties, yet we can all describe them equivalently with the ``basis vectors'' which are a superposition of odd (for fermions) and even (for bosons) products of $\gamma^{a}$'s. In an even-dimensional internal space, as it is $d=(13

Daniyal Ganiuly, Nurzhau Bolatbek, Assel Smaiyl

This paper presents a Secure Edge Gateway Architecture for Wi-Fi-Enabled IoT designed to strengthen local network protection without altering existing infrastructure. The proposed gateway acts as an intermediate control point between Wi-Fi access points and the core network, monitoring traffic, isolating untrusted devices, and preventing common wireless atta

Debasish Borah, Pritam Das, Debajyoti Dutta

The recent results from the JUNO reactor neutrino experiment have significantly improved our knowledge of the solar mixing angle $\theta_{12}$ and the solar mass splitting $\Delta m^2_{21}$. We study the impact of these improved estimates on the validity of texture-zeros in the light neutrino mass matrix by assuming neutrinos to be of Majorana nature. Consid

Jia-Nan Li, Jian Guan, Wei Wu, Chongxuan Li

Autoregressive models (ARMs) are hindered by slow sequential inference. While masked diffusion models (MDMs) offer a parallel alternative, they suffer from critical drawbacks: high computational overhead from precluding Key-Value (KV) caching, and incoherent generation arising from learning dependencies over an intractable space of token combinations. To add

Ivan Damnjanović, Anran Xu, Kexiang Xu

The transmission of a vertex $v$ in a (chemical) graph $G$ is the sum of distances from $v$ to other vertices in $G$. If any two vertices of $G$ have different transmissions, then $G$ is transmission irregular. The Wiener index $W(G)$ of a graph $G$ is the sum of all distances between all unordered pairs of vertices in $G$, which has another formula as the h