March 2026 arXiv papers — page 112

Le-Jiang Yu, Jia Zheng, Kun Pu, Chao Gao

In the context of Rydberg anti-blockade, this paper proposes a new scheme for a high-fidelity controlled-unitary gate based on non-adiabatic holonomic quantum computation. Under specific detuning and interaction conditions, the scheme achieves a suitable evolution path for non-adiabatic holonomic quantum computation through reverse engineering of pulse param

Yaze Zhao, Yixiong Zou, Yuhua Li, Ruixuan Li

Cross-Domain Few-Shot Learning (CDFSL) adapts models trained with large-scale general data (source domain) to downstream target domains with only scarce training data, where the research on vision-language models (e.g., CLIP) is still in the early stages. Typical downstream domains, such as medical diagnosis, require fine-grained visual cues for interpretabl

Jialong Liu, Dehan Shen, Yanbo Wen, Zeyu Jiang

Extreme legged parkour demands rapid terrain assessment and precise foot placement under highly dynamic conditions. While recent learning-based systems achieve impressive agility, they remain fundamentally fragile to perceptual degradation, where even brief visual noise or latency can cause catastrophic failure. To overcome this, we propose Robust Extreme Ag

Kun Wang, Meng Chen, Junhao Wang, Yuli Wu

With the widespread deployment of deep-learning-based speech models in security-critical applications, backdoor attacks have emerged as a serious threat: an adversary who poisons a small fraction of training data can implant a hidden trigger that controls the model's output while preserving normal behavior on clean inputs. Existing inference-time defenses ar

Chaokang Jiang, Desen Zhou, Jiuming Liu, Kevin Li Sun

Closed-loop evaluation of autonomous-driving policies requires interactive simulation beyond log replay. However, existing generative world models often degrade in closed loop due to (i) history-free initialization that mismatches policy inputs, (ii) multi-step sampling latency that violates real-time budgets, and (iii) compounding kinematic infeasibility ov

Tae Eun Choi, Sumin Shim, Junhyeok Kim, Seong Jae Hwang

Generative inbetweening (GI) seeks to synthesize realistic intermediate frames between the first and last keyframes beyond mere interpolation. As sequences become sparser and motions larger, previous GI models struggle with inconsistent frames with unstable pacing and semantic misalignment. Since GI involves fixed endpoints and numerous plausible paths, this

Ahmed Mohammed Cherif, Kaddour Zegga

This note introduces an extension to the definition of symphonic maps, denoted as $\varphi:(M,g)\longrightarrow(N,h)$, by exploring variations in the bi-energy functional associated with the pullback metric $\varphi^*h$ between two Riemannian manifolds.

Holger P. Petersson, Maneesh Thakur

Freudenthal algebras over a field are basically the same as Jordan algebras of degree $3$ remaining simple under all base field extensions. These algebras are intimately linked, via their automorphism groups and structure groups, to simple algebraic groups over arbitrary fields. Our main concern here will be the question of when these algebras are homogeneou

Sanja Aaramaa, Sandun Dasanayake, Markku Oivo, Jouni Markkula

Requirements volatility is a major issue in software (SW) development, causing problems such as project delays and cost overruns. Even though there is a considerable amount of research related to requirement volatility, the majority of it is inclined toward project management aspects. The relationship between SW architecture design and requirements volatilit

Dongqiang Gou, Xuming He

Grounding natural language questions to functionally relevant regions in 3D objects -- termed language-driven 3D affordance grounding -- is essential for embodied intelligence and human-AI interaction. Existing methods, while progressing from label-based to language-driven approaches, still face challenges in open-vocabulary generalization, fine-grained geom

Weibo Qiu, Yinhao Xiao, Runyu Pan

Large Language Models (LLMs) have demonstrated significant potential in various engineering tasks, including software development, digital logic generation, and companion document maintenance. However, their ability to perform board-level circuit design is understudied, as this task requires a synergized understanding of real-world physics and Integrated Cir

J. Balibrea-Correa, J. Lerendegui-Marco, C. Domingo-Pardo, V. Babiano-Suarez

Isotopic measurements of presolar silicon carbide grains from dying stars have revealed a puzzling overabundance of $^{94}$Mo that stellar nucleosynthesis models have failed to reproduce for two decades. This discrepancy challenged our understanding of the slow neutron-capture process ($s$-process) that forges approximately half of the elements heavier than

Feng Liu, Shuang Sun, Yan Wang

A graph is $\mathrm{ISK}_4$-free if it contains no induced subdivision of $K_4$. L\'ev\^eque et al. [\emph{J. Combin. Theory Ser. B} \textbf{102} (2012) 924--947] conjectured that all $\mathrm{ISK}_4$-free graphs are 4-colorable. Chen et al. [\emph{J. Graph Theory} \textbf{96} (2021) 554--577] proved that $\{\mathrm{ISK}_4, \mathrm{diamond}, \mathrm{bowtie}\

Alexey Dubinsky

We study grey-body factors for a massless scalar field in the spacetime of regular black holes arising in four-dimensional non-polynomial quasi-topological gravity. We consider two representative metrics that capture the typical features of regular geometries. Using the WKB method, we compute the transmission probabilities and analyze their dependence on the

Zhuoyi Cheng, Steven Houben

Sensemaking is an important preceding step for activities like consensus building and decision-making. When groups of people make sense of large amounts of information, their understanding gradually evolves from vague to clear. During this process when reaching a conclusion is still premature, if people are presented with others' insights, they may be direct

Mohammed Rahman Sherif Khan Mohammad, Ardhendu Behera, Sandip Pradhan, Swagat Kumar

Recent adapter-based CLIP tuning (e.g., Tip-Adapter) is a strong few-shot learner, achieving efficiency by caching support features for fast prototype matching. However, these methods rely on global uni-modal feature vectors, overlooking fine-grained patch relations and their structural alignment with class text. To bridge this gap without incurring inferenc

Dinesh Parthasarathy, Wayne Mitchell, Arjun Gambhir, Harald Köstler

Although multigrid is asymptotically optimal for solving many important partial differential equations, its efficiency relies heavily on the careful selection of the individual algorithmic components. In contrast to recent approaches that can optimize certain multigrid components using deep learning techniques, we adopt a complementary strategy, employing ev

Kirill Kuroptev, Florian Steinke, Efthymios Karangelos

This paper examines defending the power grid against load-altering attacks using electric vehicle charging. It proposes to preventively segment the cyber infrastructure that charging station operators (CSOs) use to communicate with and control their charging stations, thereby limiting the impact of successful cyber-attacks. Using real German charging station

Yuntong Zhang, Sungmin Kang, Ruijie Meng, Marcel Böhme

Agentic AI has been a topic of great interest recently. A Large Language Model (LLM) agent involves one or more LLMs in the back-end. In the front end, it conducts autonomous decision-making by combining the LLM outputs with results obtained by invoking several external tools. The autonomous interactions with the external environment introduce critical secur

Diptaranjan Das, Ezra Kassa, Hiroki Takahashi

We explore the stability of a high-finesse optical cavity at 493 nm in vacuum for cavity QED with Barium ions. A high-finesse Fabry-Perot cavity is built using mirrors with high-reflectivity (HR) coatings that are implemented by stacking multiple thin films of low-loss dielectrics on substrates. Applications of such HR mirrors in the near ultraviolet (UV) ra

Aleksander Ogonowski, Konrad Klimaszewski, Przemysław Rokita

We present DSS-GAN, the first generative adversarial network to employ Mamba as a hierarchical generator backbone for noise-to-image synthesis. The central contribution is Directional Latent Routing (DLR), a novel conditioning mechanism that decomposes the latent vector into direction-specific subvectors, each jointly projected with a class embedding to prod

Jonathan Mannaert, Marta Messia, Ferdinando Zullo

Linearized Reed-Solomon (LRS) codes form an important family of maximum sum-rank distance (MSRD) codes that generalize both Reed--Solomon codes and Gabidulin codes. In this paper we study the equivalence problem for LRS codes and determine the number of inequivalent codes within this family. Using the correspondence between sum-rank metric codes and systems

F. Elson, M. Nayak, A. A. Eberharter, M. Skoulatos

Quantum magnets in two dimensions display strong quantum interaction effects even when magnetically ordered. Using the metal-organic framework material CuF$_2$(D$_2$O)$_2$(pyz), we investigate the field-dependent spin dynamics of the $S = 1/2$ square-lattice Heisenberg antiferromagnet by high-resolution inelastic neutron scattering to applied fields beyond o

Siyuan Li, Chengyuan Liu, Wen-Hua Chen

This paper presents a hierarchical decision-making framework for autonomous systems operating under uncertainty, demonstrated through autonomous driving as a representative application. Surrounding agents are modeled using Hybrid Markov Decision Processes (HMDPs) that jointly capture maneuver-level and dynamic-level uncertainties, enabling the multi-modal en

Liang Shi, Jiarui Lu, Junqi Liu, Chence Shi

Understanding the dynamic behavior of biomolecules is fundamental to elucidating biological function and facilitating drug discovery. While Molecular Dynamics (MD) simulations provide a rigorous physical basis for studying these dynamics, they remain computationally expensive for long timescales. Conversely, recent deep generative models accelerate conformat

Lars Bartels, Amon Lahr, Andrea Carron, Melanie N. Zeilinger

Learning-based model predictive control (MPC) can enhance control performance by correcting for model inaccuracies, enabling more precise state trajectory predictions than traditional MPC. A common approach is to model unknown residual dynamics as a Gaussian process (GP), which leverages data and also provides an estimate of the associated uncertainty. Howev

Krishna Kumar Balaraman, Venkat Ram Reddy Ganuthula

This paper presents a theoretical framework examining how artificial intelligence (AI) transforms organizational structures, introducing an "hourglass" configuration that emerges as AI assumes traditional middle management functions. The analysis identifies three key mechanisms algorithmic coordination, structural fluidity, and hybrid agency that demonstrate

Sinan Ibrahim, Grégoire Ouerdane, Hadi Salloum, Henni Ouerdane

The objective comparison of Reinforcement Learning (RL) algorithms is notoriously complex as outcomes and benchmarking of performances of different RL approaches are critically sensitive to environmental design, reward structures, and stochasticity inherent in both algorithmic learning and environmental dynamics. To manage this complexity, we introduce a rig

Veronica Bitonti, Lukas Michel, Alex Scott

A classical result by Otter shows that the complete graph has an exponential number of non-isomorphic spanning trees. This was recently extended by Lee to every almost regular graph of sufficiently large degree. In this paper, we consider graphs of large minimum degree. We show that every connected graph $G$ with $n$ vertices and minimum degree $d$ has at le

Adithya L J, Suraj S Hegde, Chandrakala Meena

Postselection of quantum trajectories is known effectively introduce nonlinearity into dynamics of open quantum systems. We study the effect of such non-linearity in continuous-time quantum walks (CTQWs) on networks with homogeneous and heterogeneous degree distributions. Using the recently proposed nonlinear Lindblad master equation (NLME), we investigate t

Suryasis Jana, Abhik Ghosh

Neural networks are central to modern artificial intelligence, yet their training remains highly sensitive to data contamination. Standard neural classifiers are trained by minimizing the categorical cross-entropy loss, corresponding to maximum likelihood estimation under a multinomial model. While statistically efficient under ideal conditions, this approac

Kundan Thota, Thorsten Schlachter, Veit Hagenmeyer

Determining the age distribution of the urban building stock is crucial for sustainable municipal heat planning and upgrade prioritization. However, existing approaches often rely on datasets gathered via sensors or remote sensing techniques, leaving inconsistencies and gaps in data. We present a multi-agent LLM system comprising three key agents, the Zensus

Xinze Li, Pengxu Chen, Yiyuan Wang, Weifeng Su

Feed-forward 3D foundation models face a key challenge: the quadratic computational cost introduced by global attention, which severely limits scalability as input length increases. Concurrent acceleration methods, such as token merging, operate at the token level. While they offer local savings, the required nearest-neighbor searches introduce undesirable o

Andor Diera, Ansgar Scherp

Understanding whether large language models (LLMs) capture structured meaning requires examining how they represent concept relationships. In this work, we study three models of increasing scale: Pythia-70M, GPT-2, and Llama 3.1 8B, focusing on four semantic relations: synonymy, antonymy, hypernymy, and hyponymy. We combine linear probing with mechanistic in

Zirui Gong, Leo Yu Zhang, Yanjun Zhang, Viet Vo

Federated Learning (FL) enables collaborative model training by sharing model updates instead of raw data, aiming to protect user privacy. However, recent studies reveal that these shared updates can inadvertently leak sensitive training data through gradient inversion attacks (GIAs). Among them, active GIAs are particularly powerful, enabling high-fidelity

Zihao Zhou, Zhaolin Wang, Yuanwei Liu

A novel generative site-specific beamforming (GenSSBF) approach, termed fast beam-brainstorm (F-BBS), is proposed to address the practical bottlenecks of slow beam generation and fixed channel probing lengths in existing GenSSBF. To accelerate beam generation, F-BBS utilizes a two-stage distillation strategy that learns an average velocity field, instead of

Haoyu Jiang, Zhenjun Dong, Zhiwen Zhou, Yong Zeng

Recently a novel multi-antenna architecture termed ray antenna array (RAA) was proposed, where several simple uniform linear arrays (sULAs) are arranged in a ray-like structure to enhance communication and sensing performance. By eliminating the need for phase shifters, it also significantly reduces hardware costs. However, RAA is prone to signal blockage an

Antoun Yaacoub, Zainab Assaghir, Anuradha Kar

The rapid adoption of generative artificial intelligence (AI) in educational assessment has created new opportunities for scalable item creation, personalized feedback, and efficient formative evaluation. However, despite advances in taxonomy alignment and automated question generation, the absence of transparent, explainable, and certifiable mechanisms limi

Johanna P. Carbone, Jakob Baumsteiger, Cesare Franchini

Two-dimensional (2D) magnets offer a rich platform for exploring emergent spin phenomena due to their unique and diverse magnetic properties. Beyond intrinsic magnetism, external manipulation$\unicode{x2013}$such as defect engineering, molecular adsorption, or charge doping$\unicode{x2013}$offers powerful routes to control their magnetic behavior. In this wo

Caiyun Liu, Siyang Pei, Qingfeng Yu, Jie Xiong

Seismic full-waveform inversion is a core technology for obtaining high-resolution subsurface model parameters. However, its highly nonlinear characteristics and strong dependence on the initial model often lead to the inversion process getting trapped in local minima. In recent years, generative diffusion models have provided a way to regularize full-wavefo

Takao Inoué

This survey-style note reviews constructive versions of the Peter--Weyl theorem in the Bishop--Coquand--Spitters line. Its main purpose is to clarify which parts of the classical Peter--Weyl package admit constructive reformulations, which parts survive only in weaker or reorganized form, and which questions still appear to remain open. The term ``constructi

David Farr, Stephen Prochaska, Jack Moody, Lynnette Hui Xian Ng

Comprehending the information environment (IE) during crisis events is challenging due to the rapid change and abstract nature of the domain. Many approaches focus on snapshots via classification methods or network approaches to describe the IE in crisis, ignoring the temporal nature of how information changed over time. This work presents a system-oriented

Nikola Zlatanov, Damir Salakhov

Conventional hybrid beamforming architectures are often compared with one another and with the fully-digital architecture under the same \emph{radiated} antenna power. However, the physically relevant budget is the power injected by the RF-chain outputs into the passive analog RF network, which is then usually transferred to the antenna ports in a contractiv

Justo Pastor Lambare

In this comment, we demonstrate that the claim by Spavieri et al., asserting that Wang et al.'s interferometric experiment disproves the special theory of relativity by revealing that simultaneity must be an absolute concept independent of the observer's state of motion, is based on circular reasoning and therefore constitutes a logical fallacy.

Benjamin Marsh, Alejandro Ranchal-Pedrosa

Sedna is a coded multi-proposer consensus protocol in which a sender shards a transaction payload into rateless symbols and disseminates them across parallel proposer lanes, providing high throughput and ``until decode'' privacy. This paper studies a sharp incentive failure in such systems. A cartel of lane proposers can withhold the bundles addressed to its

Yaoxiang Wang, Qi Shi, ShangZhan Li, Qingguo Hu

LLMs have recently demonstrated strong capabilities in automatic RTL code generation, achieving high syntactic and functional correctness. However, most methods focus on functional correctness while overlooking critical physical design objectives, including Power, Performance, and Area. In this work, we propose a PPA-aware, tool-integrated multi-agent framew

Victor P. Goncalves, Luana Santana, Wolfgang Schäfer

The inclusive photoproduction of heavy mesons in ultraperipheral $pPb$ and $PbPb$ collisions at the LHC energies is investigated considering the color dipole $S$-matrix formalism and assuming distinct models for the unintegrated gluon distribution, based on different assumptions for the description of the QCD dynamics. In particular, predictions for the $B^0

André de Figueiredo Stabile, Aurélien Grolet, Alessandra Vizzaccaro, Cyril Touzé

The parametrisation method for invariant manifolds is a powerful technique for deriving reduced-order models in the context of nonlinear vibrating systems, allowing accurate computations of nonlinear normal modes. Thanks to arbitrary order asymptotic expansions, converged results are within reach and directly applicable to finite element structures. However,

Cai Xu, Changhao Sun, Ziyu Guan, Wei Zhao

Multi-view learning primarily aims to fuse multiple features to describe data comprehensively. Most prior studies implicitly assume that different views share similar dimensions. In practice, however, severe dimensional disparities often exist among different views, leading to the unbalanced multi-view learning issue. For example, in emotion recognition task

C. Pinto, M. Del Santo, A. D'Aì, F. Pintore

In previous work, it was reported that the Galactic black hole candidate MAXI J1810-222 exhibited a notable absorption spectral feature at around 1 keV in low-resolution X-ray spectra of CCD-like detectors. The feature was correlated with the spectral state of the source, being stronger in the soft states, as it occurs in the typical Fe K winds of X-ray bina

Florian Raßhofer, Erwin Frey

Phase separation in passive systems leads to uncontrolled droplet growth, limiting structural control in soft materials and cells. We identify a generic mechanism to arrest coarsening based on chemical interconversion between molecular species with different diffusivities. Sharp-interface theory and simulations show that when the faster-diffusing species bec

Dimitrios Irodotou, Shihong Liao, Theodoros Nakas, Geoffrey Compère

In this third study of the 'Resolving supermAssive Black hole Binaries In galacTic hydrodynamical Simulations' (RABBITS) series we develop and implement a geometrically thin relativistic accretion disc model, which self-consistently evolves the mass and spin vector of black holes via analytically modelling the structure of steady-state accretion discs. The m

Nishant Kumar, Franck Kerhervé, Lionel Agostini, Laurent Cordier

Climate change and the rapid growth of urban populations are intensifying environmental stresses within cities, making the behavior of urban atmospheric flows a critical factor in public health, energy use, and overall livability. This study targets to develop fast and accurate models of urban pollutant dispersion to support decision-makers, enabling them to

Yaxu Xie, Abdalla Arafa, Alireza Javanmardi, Christen Millerdurai

Achieving unified 3D perception and reasoning across tasks such as segmentation, retrieval, and relation understanding remains challenging, as existing methods are either object-centric or rely on costly training for inter-object reasoning. We present a novel framework that constructs a hierarchical language-distilled Gaussian scene and its 3D semantic scene

Jean-Stefan Koskivirta, Lorenzo La Porta

For an abelian type Shimura variety and an odd prime $p$ of good reduction, we characterize the regularity in codimension one of Zariski closures of Ekedahl--Oort strata in terms of the Frobenius action on the root datum. We give an algorithm that detects codimension one singularities for arbitrary Ekedahl--Oort strata. When the Shimura datum is of split typ

Yan Liang, Ziyuan Yang, Zhuxin Lei, Mengyu Sun

Efficiently managing and utilizing large-scale medical imaging datasets with limited resources presents significant challenges. While coreset selection helps reduce computational costs, its effectiveness in medical data remains limited due to inherent complexity, such as large intra-class variation and high inter-class similarity. To address this, we revisit

Rebecca M. Crossley, Carles Falco, Ruth E. Baker

Travelling wave solutions of reaction-diffusion equations are widely used to model the spatial spread of populations and other phenomena in biology and physics. In this article, we reinterpret the classical variational principle approach through an optimal control formulation, in order to obtain a lower bound on the invasion speed of travelling wave solution

Molla Basir Aahmed, Partha Pratim Roy

Let $\mathcal{A}$ denote the class of functions $f$ that are analytic in the open unit disk $\mathbb{D}$ and satisfy the normalization conditions $f(0) = 0$ and $f'(0) = 1$. This paper investigates the inverse logarithmic coefficients $\Gamma_n$, which are defined by the expansion $\log(f^{-1}(w)/w) = 2\sum_{n=1}^{\infty} \Gamma_n w^n$. We establish sharp up

Pierre Catoire, Robin Genuer, Cecile Proust-Lima

Conditions ensuring optimal parameter estimation in the presence of missing data are well established in inference, typically relying on the Missing-at-Random (MAR) assumption. In prediction, similar principles are often assumed to apply. However, methods considered biased in inference, such as pattern sub-modelling or unconditional imputation, have been sho

D. Juher, F. Mañosas, D. Rojas

In this paper we give a fully combinatorial description of the zero entropy periodic patterns on trees. Unlike previously known characterizations of such patterns, our criterion is independent of any particular topological realization of the pattern and provides, thus, a practical and fast algorithm to test zero entropy. As an application, consider a $k$-sta

Benedict Lane, Anushka Mittal, Ariana Torres-Knoop

Along with the increased availability and capabilities of quantum computers comes the core question: how can access to quantum computing be allocated in a responsible way? This report introduces a general legal-ethical framework that providers of access to quantum computing can apply to develop robust access policies tailored to their specific context. We de

Ashot Minasyan

We prove that every virtually free group $G$ has property (LR) of Long and Reid: each finitely generated subgroup of $G$ is a retract of a finite index subgroup. The main ingredient in the proof is a new embedding result stating that every countable virtually free group embeds in a double of a finite group. As a corollary, we show that any group commensurabl

Sarojini Mohapatra, Hiranmoy Pal

We investigate fractional revival in graphs with respect to the adjacency, Laplacian, and signless Laplacian matrices. We observe that, under certain conditions, fractional revival is preserved under graph complementation. Then we establish a connection between fractional revival in a graph and in its double cover, and obtain a complete characterization of p

Sofía Aguilar-Valdez, Stefania Degaetano-Ortlieb

While context embeddings produced by LLMs can be used to estimate conceptual change, these representations are often not interpretable nor time-aware. Moreover, bias augmentation in historical data poses a non-trivial risk to researchers in the Digital Humanities. Hence, to model reliable concept trajectories in evolving scholarship, in this work we develop

Zhe Pan, Qi Xu, Ruixiang Wang, Zhenghao Jin

Parallel-wound no-insulation (PW-NI) high-temperature superconducting (HTS) coils significantly reduce charging delay while maintaining excellent self-protection capability, demonstrating great potential for high-field applications. Existing models that couple the T-A formulation with equivalent circuits have demonstrated high accuracy in electromagnetic ana

Christos Koutsiaris

This paper describes the design, implementation, and evaluation of a browser extension that provides contextual help to users who hover over technological acronyms and abbreviations on web pages. The extension combines a curated technical dictionary with OpenAI's large language model (LLM) to deliver on-demand definitions through lightweight tooltip overlays

Yingpeng Qi, Jianmin Yang, Zhihui Zhou, Qing Xu

Defects, fluctuations, degenerate states and correlated interactions facilitate the emergence of exotic properties in condensed matter systems while also inducing atomic-scale local correlated structures that deviate from the average long-range order. Establishing the structure-property relationship from the perspective of these atomic-scale local correlated

Matthew Hyde

Suppose $X$ is an $\rm{RCD}(K,N)$ space with $K \in \mathbb{R}$ and $N \in (1,\infty)$. We obtain a characterisation of the Newtonian-Sobolev space $N^{1,2}(X)$ in terms of a quantity which measures to what extent a function is locally (across all scales and locations) well-approximated by harmonic functions. A similar characterisation is obtained which furt

Hiroshi Okada, Jia-Jun Wu

We propose our framework as an effective field theory valid below the cut-off scale $\Lambda$, in which we explain the tiny scale of neutrino masses by integrating a non-invertible symmetry with the dynamical determination of the cut-off scale. In our model, we introduce three families of SU(2)$_L$ quintet fermions ($\Sigma_R$) and a quartet scalar ($\phi_4$

Stefan Groote, Arpan Chatterjee, Maria Naeem

In accordance to the aim of the constituing meeting of the COST action CA24159 ``Structure and Spectroscopy of Hadrons Research Project'' to introduce the different groups to the action, in this talk we give an overview over the subjects dealt with by the working group in Tartu related to hadron physics. We deal with the production and the nonleptonic decays

Pengfei Hou, Yumiao Tian, Zifeng Liu, Junwen Duan

High-pressure experiments using diamond anvils have revealed novel properties and phase behavior of H2O under extreme conditions. When contained in diamond-anvil cells, the H2O samples are usually in direct contact with the diamond anvil. However, the extent to which this interface affects measured pressure-induced properties and behavior, including coexiste

Huimin Yu

This paper investigates the asymptotic behavior of a hyperbolic relaxation system designed for homogeneous two-phase flows in the limit of vanishing relaxation time. The governing equations comprise conservation laws for mixture mass and momentum, supplemented by a transport equation for the gas phase mass that includes a stiff relaxation source term. This s

Seongrae Noh, SeungWon Seo, Gyeong-Moon Park, HyeongYeop Kang

Editing a 3D indoor scene from natural language is conceptually straightforward but technically challenging. Existing open-vocabulary systems often regenerate large portions of a scene or rely on image-space edits that disrupt spatial structure, resulting in unintended global changes or physically inconsistent layouts. These limitations stem from treating ed

Arianna Stropeni, Fabrizio Genilotti, Francesco Borsatti, Manuel Barusco

Visual Anomaly Detection (VAD) is essential for industrial quality control, enabling automatic defect detection in manufacturing. In real production lines, VAD systems must satisfy strict real-time and privacy requirements, necessitating a shift from cloud-based processing to local edge deployment. However, processing data locally on edge devices introduces

Prateek P. Kulkarni

We introduce list privacy amplification (LPA), a relaxation of the final step of quantum key distribution (QKD) in which Alice and Bob extract a list of $L$ candidate keys from a raw string correlated with an eavesdropper Eve, with the guarantee that at least one key is perfectly secret while Eve cannot identify which. This parallels list decoding in error-c

Reza Karimpour, Matteo Gori, Alexandre Tkatchenko

Quantum-matter theory (QMT), based on the Schr\"odinger or Dirac equations, is firmly established for both intra- and intermolecular interactions. However, there are two key issues with QMT. First, its applicability to large molecular complexes is hindered by the relatively high computational cost of the calculations required to achieve high accuracy. Second

P. Arrighi, D. Bakircioglu, N. L. Houyet

We take quantum theory and replace $\mathbb{C}$ by $\mathbb{C}[\varepsilon]$ where $\varepsilon^2=0$, i.e. we extend quantum theory to the ring of dual complex numbers. The aim is to develop a common language in which to treat continuous quantum physics and discrete quantum models in a unified manner, including their symmetries. Since quantum theory is linea

Soumya Ranjan Sahoo, Gagan N., Sanand Sasidharan, Divya Bharti

Large Language Models (LLMs) have demonstrated strong capabilities in biomedical question answering, yet their tendency to generate plausible but unverified claims poses serious risks in clinical settings. To mitigate these risks, the TREC 2025 BioGen track mandates grounded answers that explicitly surface contradictory evidence (Task A) and the generation o

Wenhan Cao, Keyu Yan, Lin Zhao

We present a drifting-based framework for amortized sampling of Boltzmann distributions defined by energy functions. The method trains a one-step neural generator by projecting samples along a Gaussian-smoothed score field from the current model distribution toward the target Boltzmann distribution. For targets specified only up to an unknown normalization c

Takahiro Suzuki, Michele Aleandri, Stefano Moretti

Ranking individuals based on their performance in different coalitions is a problem emerging in various domains (teams sports, scientific evaluation, argumentation, etc.). Often, for practical reasons, the number of comparable coalitions is limited. Therefore, the foundational principles of ranking solutions must support realistic interpretations in contexts

Thomas Borrett, Licong Xu, Andy Nilipour, Boris Bolliet

We present an agent-driven approach to the construction of parameter inference pipelines for scientific data analysis. Our method leverages a multi-agent system, Cmbagent (the analysis system of the AI scientist Denario), in which specialized agents collaborate to generate research ideas, write and execute code, evaluate results, and iteratively refine the o

Md Maruf Hossain, Tim Katzke, Simon Klüttermann, Emmanuel Müller

We propose SYRAN, an unsupervised anomaly detection method based on symbolic regression. Instead of encoding normal patterns in an opaque, high-dimensional model, our method learns an ensemble of human-readable equations that describe symbolic invariants: functions that are approximately constant on normal data. Deviations from these invariants yield anomaly

Zihao Zheng, Zhihao Mao, Sicheng Tian, Maoliang Li

Vision-Language-Action (VLA) Models have become the mainstream solution for robot control, but suffer from slow inference speeds. Speculative Decoding (SD) is a promising acceleration method which can be divided into two categories: drafter-based SD and retrieval-based SD. Each of the two methods demonstrates complementary advantages and limitations when app

Norihisa Namura, Hiroya Nakao

We present a formulation of an optimal control problem for a two-dimensional diffusion process governed by a Fokker-Planck equation to achieve a nonequilibrium steady state with a desired circulation while accelerating convergence toward the stationary distribution. To achieve the control objective, we introduce costs for both the probability density functio

Yijing Guo, Mengjun Chao, Luo Wang, Tianyang Zhao

Panoramic imagery offers a full 360{\deg} field of view and is increasingly common in consumer devices. However, it introduces non-pinhole distortions that challenge joint pose estimation and 3D reconstruction. Existing feed-forward models, built for perspective cameras, generalize poorly to this setting. We propose PanoVGGT, a permutation-equivariant Transf

Ciprian Paduraru, Petru-Liviu Bouruc, Alin Stefanescu

In Agentic AI, Large Language Models (LLMs) are increasingly used in the orchestration layer to coordinate multiple agents and to interact with external services, retrieval components, and shared memory. In this setting, failures are not limited to incorrect final outputs. They also arise from long-horizon interaction, stochastic decisions, and external side

Deliang Wen, Ke Sun, Yu Wang

Affective judgment in real interaction is rarely a purely local prediction problem. Emotional meaning often depends on prior trajectory, accumulated context, and multimodal evidence that may be weak, noisy, or incomplete at the current moment. Although multimodal emotion recognition (MER) has improved the integration of text, speech, and visual signals, many

Simon Klüttermann, Tim Katzke, Phuong Huong Nguyen, Emmanuel Müller

Tabular foundation models, specifically Prior-Data Fitted Networks (PFNs), have revolutionized outlier detection (OD) by enabling unsupervised zero-shot adaptation to new datasets without training. However, despite their predictive power, these models typically function as opaque black boxes, outputting scalar outlier scores that lack the operational context

Sooyoung Ryu, Mathieu Salzmann, Saqib Javed

Post-training quantization (PTQ) is a practical path to deploy large diffusion models, but quantization noise can accumulate over the denoising trajectory and degrade generation quality. We propose Q-Drift, a principled sampler-side correction that treats quantization error as an implicit stochastic perturbation on each denoising step and derives a marginal-

Nil Ayday, Lingchu Yang, Debarghya Ghoshdastidar

Graph transformers are the state-of-the-art for learning from graph-structured data and are empirically known to avoid several pitfalls of message-passing architectures. However, there is limited theoretical analysis on why these models perform well in practice. In this work, we prove that attention-based architectures have structural benefits over graph con

M. Das, S. P. Littlefair, S. G. Parsons, V. S. Dhillon

We present high-speed photometry of the eclipsing cataclysmic variable CSS131106 J052412+004148. We determine the system parameters by modelling the eclipse lightcurve using the photometric eclipse method, in which the mass ratio is determined from the relative timings of the white dwarf and bright spot eclipses. Despite the blended white dwarf and bright sp

Luigi Celona, Simone Bianco, Raimondo Schettini

The widespread sharing of face images on social media platforms and in large-scale datasets raises pressing privacy concerns, as biometric identifiers can be exploited without consent. Face anonymization seeks to generate realistic facial images that irreversibly conceal the subject's identity while preserving their usefulness for downstream tasks. However,

Haoxuan Yin, Chen Tang, Yangfan Wang, Lian Yan

Fine-tuning large language models (LLMs) with high-quality knowledge has been shown to enhance their performance effectively. However, there is a paucity of research on the depth of domain-specific knowledge comprehension by LLMs and the application of targeted active learning to improve their expertise. To address this gap, we introduce the Knowledge-Aware

P. Chirico, G. Di Bello, G. De Filippis, C. A. Perroni

Understanding relaxation dynamics in open quantum systems is a central problem in nonequilibrium quantum physics. Here we investigate the quantum Mpemba effect in the spin boson model. In the weak coupling Markovian regime we show that the occurrence of the effect strongly depends on the choice of distance measure at low temperature: while it appears in the

Qianpu Chen, Giulio Barbero, Mike Preuss, Derya Soydaner

We introduce Emergent Trust Learning (ETL), a lightweight, trust-based control algorithm that can be plugged into existing AI agents. It enables these to reach cooperation in competitive game environments under shared resources. Each agent maintains a compact internal trust state, which modulates memory, exploration, and action selection. ETL requires only i

Jonathan Grée, Qiuyue Liang, Elisa G. M. Ferreira

The pulsar timing array systems have reported a detection of a nanohertz-band stochastic gravitational wave background in our galaxy. It is of interest to use this observation to probe modified gravity and to forecast the sensitivity with which certain deviations can be tested in the coming years. In this paper, we focus on the modified dispersion relation o

A. I. Komech, E. A. Kopylova

The article concerns damped driven Jaynes-Cummings equation which describes quantised one-mode Maxwell field coupled to a two-level molecule. We consider a broad class of damping and pumping which are polynomial in the creation and annihilation operators, and their structures correspond to the theory of completely positive and trace preserving generators (CP

Mario Menichella

We compile a systematic mass inventory of the Solar System excluding the Sun, drawing on spacecraft measurements, planetary ephemerides, and population surveys of small-body populations including main-belt asteroids and trans-Neptunian objects. Using a Monte Carlo simulation with 100,000 realisations, and treating poorly constrained components (scattered dis

Alison M. W. Mitchell, Samuel T. Spencer

Pulsar wind nebulae (PWNe), formed when the wind originating from a rapidly rotating neutron star flows out into its surroundings, have now been observed across the electromagnetic spectrum from the radio to the PeV gamma-ray regime. For most of these sources, leptonic processes, where electrons interacting with background photon fields produce high-energy p

Christian Bernert, Joshua Shaw

We show that, for any given $k \ge 2$, every sufficiently large number appears as the Steiner--Wiener $k$ index of a graph.