December 2025 arXiv papers — page 14

Kalina Mincheva, Naufil Sakran

In this article, we disprove a conjecture of F. Alarc\'on and D. Anderson and give a complete classification of the prime ideals in the one variable polynomial semiring with coefficients in Boolean semifield. We group the prime ideals of $\mathbb{B}[x]$ into three classes, indexed by integers.

Meizheng Fu

Many open conjectures in the representation theory of finite groups can be studied by reducing them to related questions about quasi-simple groups. In such studies, $p$-radical subgroups typically play a critical role. To classify the $p$-radical subgroups of a finite group, we first classify the elementary abelian $p$- subgroups and find their local structu

E. S. Moreira, J. P. A. Paula

We calculate the Feynman propagator at finite temperature in an Einstein universe for a neutral massive scalar field arbitrarily coupled to the Ricci curvature. Then, the propagator is used to determine the mean square fluctuation, the internal energy, and pressure of a scalar blackbody radiation as functions of the curvature coupling parameter $\xi$. By stu

Abolhassan Pishahang, Maryam Badiei

This study investigates how generative AI systems interpret the architectural intelligence embedded in vernacular form. Using the Iranian pigeon tower as a case study, the research tests three diffusion models, Midjourney v6, DALL-E 3, and DreamStudio based on Stable Diffusion XL (SDXL), across three prompt stages: referential, adaptive, and speculative. A f

Kaustubh Dhole

Recent advances in mechanistic interpretability suggest that intermediate attention layers encode token-level hypotheses that are iteratively refined toward the final output. In this work, we exploit this property to generate adversarial examples directly from attention-layer token distributions. Unlike prompt-based or gradient-based attacks, our approach le

Dingmin Wang, Ji Ma, Shankar Kumar

The success of expanded context windows in Large Language Models (LLMs) has driven increased use of broader context in retrieval-augmented generation. We investigate the use of LLMs for retrieval augmented question answering. While longer contexts make it easier to incorporate targeted knowledge, they introduce more irrelevant information that hinders the mo

Himel Ghosh

Automated bias detection in news text is heavily used to support journalistic analysis and media accountability, yet little is known about how bias detection models arrive at their decisions or why they fail. In this work, we present a comparative interpretability study of two transformer-based bias detection models: a bias detector fine-tuned on the BABE da

Bruno Florentino, Camila Sestito, Wellington Cruz, André de Carvalho

This study examines the perceptions of Brazilian K-12 education teachers regarding the use of AI in education, specifically General Purpose AI. This investigation employs a quantitative analysis approach, extracting information from a questionnaire completed by 346 educators from various regions of Brazil regarding their AI literacy and use. Educators vary i

YuYang Miao, Chang Li, Zehua Chen

Time series imputation, i.e., filling the missing values of a time recording, finds various applications in electricity, finance, and weather modelling. Previous methods have introduced generative models such as diffusion probabilistic models and Schrodinger bridge models to conditionally generate the missing values from Gaussian noise or directly from linea

M. Andersson, W. Ranter

We show that if an endomorphism $f:\mathbb{T}^2 \to \mathbb{T}^2$ is absolutely partially hyperbolic, then it has a center foliation. Moreover, the center foliation is leaf conjugate to that of its linearization.

Nicola Garofalo

In this paper we introduce a two-parameter family of Mehler kernels and connect them to a class of Baouendi-Grushin flows in fractal dimension. We also highlight a link with a geometric fully nonlinear equation and formulate two questions.

Oluwatosin Akande, Gabriel P. Langlois, Akwum Onwunta

Inverse problems are important mathematical problems that seek to recover model parameters from noisy data. Since inverse problems are often ill-posed, they require regularization or incorporation of prior information about the underlying model or unknown variables. Proximal operators, ubiquitous in nonsmooth optimization, are central to this because they pr

David Galvin, Phillip Marmorino, Emily McMillon, JD Nir

Given a graph $G$ and a target graph $H$, an $H$-coloring of $G$ is an adjacency-preserving vertex map from $G$ to $H$. The number of $H$-colorings of $G$, $\hom(G,H)$, has been studied for many classes of $G$ and $H$. In particular, extremal questions of maximizing and minimizing $\hom(G,H)$ have been considered when $H$ is a clique or $G$ is a tree. In thi

Jonas Antor, Ben Elias

We classify gradings on the Hecke category that refine the standard integer grading. We also classify object-preserving autoequivalences of the Hecke category. We obtain a natural bigrading on the Hecke category which is related to the Frobenius automorphism. We also obtain an exotic grading in special characteristic that can be used to categorify many Hecke

Vladimir Karas

Dynamics of stellar orbits in dense stellar systems and nuclear star clusters (NSC) with an embedded supermassive black hole (SMBH) is governed a complex interplay of different forces. In particular, star--star gravitational collisions (relaxation), physical collisions between stars, and the hydrodynamical interaction with any surrounding gaseous environment

Sameer Rahil, Zain Abdullah Ahmad, Talha Asif

Federated Learning (FL) enables collaborative model training across decentralized edge devices while preserving data privacy. However, statistical heterogeneity among clients, often manifested as non-IID label distributions, poses significant challenges to convergence and generalization. While Sharpness-Aware Minimization (SAM) has been introduced to FL to s

Valeriya Mykhaylova, Krzysztof Redlich, Chihiro Sasaki

We study the evolution of charm $(c)$ quarks in hot QCD matter with $N_f=2+1(+1)$ quark flavors by analyzing the charm production rate and the time dependence of their abundance. Microscopically, the system is described within a quasiparticle model, in which interactions among dynamical quarks and gluons are encoded in their effective masses with the running

Mahdi Karami, Ali Behrouz, Peilin Zhong, Razvan Pascanu

State-space models (SSMs) have recently attention as an efficient alternative to computationally expensive attention-based models for sequence modeling. They rely on linear recurrences to integrate information over time, enabling fast inference, parallelizable training, and control over recurrence stability. However, traditional SSMs often suffer from limite

Pavel Chernakov, Sasan Jafarnejad, Raphaël Frank

Adverse media screening is a critical component of anti-money laundering (AML) and know-your-customer (KYC) compliance processes in financial institutions. Traditional approaches rely on keyword-based searches that generate high false-positive rates or require extensive manual review. We present an agentic system that leverages Large Language Models (LLMs) w

Michael Andrew Henry

We utilize the structure of quasiautomorphic forms over an arbitrary Hecke triangle group to define a new vector analogue of an automorphic form. We supply a proof of the functional equations that hold for these functions modulo the group generators.

Z. T. Wang, M. Hilke, N. Fong, D. G. Austing

We investigate resonant acoustic phonon scattering in the magneto-resistivity of an ultra-high mobility two-dimensional electron gas system subject to DC current in the temperature range 10 mK to 3.9 K. For a DC current density of $\sim$1.1 A/m, the induced carrier drift velocity $v_{drift}$ becomes equal to the speed of sound $s \sim$ 3 km/s. When $v_{drift

Krzysztof Nowak

A common assumption in the Effective Field Theories of gravity is that their quasi-static weak-field infrared limit yields the well-known second-order Poisson operator. We examine this limit for the universality class of parity-even, symmetric, analytic gravitational theories admitting a local derivative expansion using Lorentzian FRG methods. We find that,

S. Passanante, M. Quintero, A. Zelcer, M. S. Moreno

We combine for the first time the properties of ordered mesoporous thin films and complex oxide nanoparticles in the design of new heterostructures, taking advantage of the accessible tridimensional pores network. In this work, we demonstrate the feasibility of synthesizing La0.88Sr0.12MnO3 inside the pores of a mesoporous SiO2 thin film, using pulsed laser

Surya Rayala, Marcos Quinones-Grueiro, Naveeduddin Mohammed, Ashwin T S

Effective urban warfare training requires situational awareness and muscle memory, developed through repeated practice in realistic yet controlled environments. A key drill, Enter and Clear the Room (ECR), demands threat assessment, coordination, and securing confined spaces. The military uses Synthetic Training Environments that offer scalable, controlled s

Seyed Mohamad Ali Tousi, Adib Bazgir, Yuwen Zhang, G. N. DeSouza

We present a hybrid quantum-classical framework augmented with learned error mitigation for solving the viscous Burgers equation on noisy intermediate-scale quantum (NISQ) hardware. Using the Cole-Hopf transformation, the nonlinear Burgers equation is mapped to a diffusion equation, discretized on uniform grids, and encoded into a quantum state whose time ev

Marco Turchetta, Manuel Linares, Karri Koljonen, Paulo A. Miles-Páez

We present the main results obtained from the COmpact BInary Pulsar search in the low-LAtitude NEighborhood (COBIPLANE), an optical photometric survey designed to find new `spider' binary millisecond pulsars. We conducted observations targeting 30 unidentified sources from the 4FGL-DR3 Fermi Large Area Telescope (Fermi-LAT) catalog, selected for their pulsar

Filip Bělík, Yanlai Chen, Akil Narayan

We investigate model reduction of parametric linear time-invariant (LTI) dynamical systems. When posed in the frequency domain, this problem can be formulated as seeking a low-order rational function approximation of a high-order rational function. We propose to use a standard reduced basis method (RBM) to construct this low-order rational function. Algorith

Amal Alqahtani, Efsun Kayi, Mona Diab

The prevalence of chronic stress represents a significant public health concern, with social media platforms like Twitter serving as important venues for individuals to share their experiences. This paper introduces StressRoBERTa, a cross-condition transfer learning approach for automatic detection of self-reported chronic stress in English tweets. The inves

Itamar Allali, Mudit Jain, Shi Yan

Loops of cosmic string experience a recoil from anisotropic gravitational radiation, known as the rocket effect, which influences the extent to which they are captured by galaxies during structure formation. Analytical studies have reached different conclusions regarding loop capture in galaxies: early treatments argued for efficient capture, while later ana

Muhammad Muneeb, David B. Ascher

Large language models (LLMs) often lack specialized knowledge for complex bioinformatics applications. We present a reproducible pipeline for fine-tuning LLMs on specialized bioinformatics data, demonstrated through two use cases: PRSGPT, focused on polygenic risk score (PRS) tools, and BioStarsGPT, trained on community forum discussions. The nine-step pipel

Samaresh Kumar Singh, Joyjit Roy, Martin So

Recent attacks on critical infrastructure, including the 2021 Oldsmar water treatment breach and 2023 Danish energy sector compromises, highlight urgent security gaps in Industrial IoT (IIoT) deployments. While Federated Learning (FL) enables privacy-preserving collaborative intrusion detection, existing frameworks remain vulnerable to Byzantine poisoning at

Core Team, Dong Zhang, Gang Wang, Jinlong Xue

Existing audio language models typically rely on task-specific fine-tuning to accomplish particular audio tasks. In contrast, humans are able to generalize to new audio tasks with only a few examples or simple instructions. GPT-3 has shown that scaling next-token prediction pretraining enables strong generalization capabilities in text, and we believe this p

Marco Zank

We derive a variational formulation for the scalar wave equation in the second-order formulation on bounded Lipschitz domains and homogeneous initial conditions. We investigate a variational framework in a bounded space-time cylinder $Q$ with a new solution space and the test space $L^2(Q)$ for source terms in $L^2(Q)$. Using existence and uniqueness results

Jacob L. Bourjaily, Michael Plesser, Cristian Vergu

We describe how to construct a spanning set of linearly-independent, automatically orthogonal colour tensors for scattering amplitudes involving coloured particles transforming under arbitrary representations of any gauge theory, sufficient to all orders of perturbation theory (or beyond). These tensors are constructed from any choice of a single, trivalent

Lars van der Laan, Nathan Kallus

Fitted $Q$-evaluation (FQE) is a standard regression-based tool for off-policy evaluation, but existing stability guarantees often rely on Bellman completeness, a strong closure condition that can fail under function approximation. We study an alternative route: changing the norm used in the regression step. The policy-evaluation Bellman operator is contract

Zhendong Li, Akwum Onwunta, Bedřich Sousedík

We develop efficient hierarchical preconditioners for optimal control problems governed by partial differential equations with uncertain coefficients. Adopting a discretize-then-optimize framework that integrates finite element discretization, stochastic Galerkin projection, and advanced time-discretization schemes, the approach addresses challenges of scali

Roman V. Buniy, Thomas W. Kephart

We present here several new exact results for a number of entangled states: the W-state of three qubits and its generalization -- Dicke states for more than three qubits. We derive these results by bounding the expected values of the Bell-Mermin operators. We review the three qubit GHZ Mermin device, make its generalization to four qubits, and then construct

M. A. Ollis

During their investigation of power-sequence terraces, Anderson and Preece briefly mention a construction of a terrace for the cyclic group $\mathbb{Z}_n$ when $n$ is odd and $2n+1$ is prime; it is built using the discrete logarithm modulo $2n+1$. In this short note we see that this terrace gives rise to an orthogonal double cover (ODC) for the complete grap

Zi-Hao Dong, Yi Zhang

The theoretical understanding of conventional superconductivity as the phonon-assisted formation and condensation of two-electron Cooper pairs is a significant triumph in condensed matter physics. Here, we propose many-electron characterizations of higher-charge superconductivity with Cooper pairs consisting of more than two electrons, by implementing transl

Ryan Mays, Predrag Nikolić

We analyze a classical Heisenberg spin model on the simple cubic lattice which is invariant under time reversal and contains multiple chiral spin interactions. The modelled dynamics is appropriate either for local moments coupled to itinerant Weyl electrons, or localized electrons with a strong spin-orbit coupling that would produce a Weyl spectrum away from

Liang Ma, H. Lu

We consider quadratic curvature perturbation to the Myers-Perry black hole in five dimensions at the linear level in the coupling constant. The solution can then be solved order by order in terms of two dimensionless angular momentum parameters up to an arbitrary order. We present the results up to tenth order. The perturbed solution allows us to obtain the

Ana Hudomal, Aiden Daniel, Tiago Santiago do Espirito Santo, Milan Kornjača

Recent advances in quantum simulations have opened access to the real-time dynamics of lattice gauge theories, providing a new setting to explore how quantum criticality influences thermalization and ergodicity far from equilibrium. Using QuEra's programmable Rydberg atom array, we map out the dynamical phase diagram of the spin-1/2 U(1) quantum link model i

Alim Ablat, Sayipjamal Dulat, Marco Guzzi, Joey Huston

We present a new determination of the strong coupling constant $\alpha_s$ from a global QCD analysis CT25 of parton distribution functions (PDFs) that incorporates high-precision experimental measurements from the Run-2 of the Large Hadron Collider together with a large sample of other measurements over a wide interval of energies. This work addresses two ob

Sulagna Bhattacharya, Debajit Bose, Basudeb Dasgupta, Jaya Doliya

The presence of supermassive black holes (SMBHs) at high redshifts ($z>5$), as revealed by James Webb Space Telescope (JWST), challenges standard black hole (BH) formation scenarios. We propose a mechanism in which non-annihilating dark matter (DM) with non-gravitational interactions with the Standard Model (SM) particles accumulates inside Population III (P

Hau-Shiang Shiu, Chin-Yang Lin, Zhixiang Wang, Chi-Wei Hsiao

Diffusion-based video super-resolution (VSR) methods deliver strong perceptual quality but are often unsuitable for latency-sensitive scenarios due to reliance on future frames and expensive multi-step denoising. We propose Stream-DiffVSR, a causally conditioned diffusion framework for efficient online VSR. Operating strictly on past frames, Stream-DiffVSR i

Milosz Matraszek, Wojciech J. Jankowski, Jan Behrends

We identify quantum geometric bounds for observables in non-Hermitian systems. We find unique bounds on non-Hermitian quantum geometric tensors, generalized two-point response correlators, conductivity tensors, and optical weights. We showcase these findings in topological systems with non-Hermitian Chern numbers. We demonstrate that the non-Hermitian geomet

Shashwat Goel, Rishi Hazra, Dulhan Jayalath, Timon Willi

AI co-scientists are emerging as a tool to assist human researchers in achieving their research goals. A crucial feature of these AI co-scientists is the ability to generate a research plan given a set of aims and constraints. The plan may be used by researchers for brainstorming, or may even be implemented after further refinement. However, language models

Saranesh Prembabu, Shu-Heng Shao, Ruben Verresen

Gapless quantum phases can become distinct when internal symmetries are enforced, in analogy with gapped symmetry-protected topological (SPT) phases. However, this distinction does not always lead to protected edge modes, raising the question of how the bulk-boundary correspondence is generalized to gapless cases. We propose that the spatial interface betwee

Shaocong Xu, Songlin Wei, Qizhe Wei, Zheng Geng

Transparent objects remain notoriously hard for perception systems: refraction, reflection and transmission break the assumptions behind stereo, ToF and purely discriminative monocular depth, causing holes and temporally unstable estimates. Our key observation is that modern video diffusion models already synthesize convincing transparent phenomena, suggesti

Sarasija Sudharsan, Anupam Sharma

This study examines the applicability of two leading-edge dynamic stall criteria, namely, the maximum magnitudes of the leading-edge suction parameter (LESP) and the boundary enstrophy flux (BEF), in a moderately compressible flow regime. While previously shown to predict stall onset ahead of dynamic stall vortex (DSV) formation in incompressible and mildly

Huajie Tan, Sixiang Chen, Yijie Xu, Zixiao Wang

The primary obstacle for applying reinforcement learning (RL) to real-world robotics is the design of effective reward functions. While recently learning-based Process Reward Models (PRMs) are a promising direction, they are often hindered by two fundamental limitations: their reward models lack step-aware understanding and rely on single-view perception, le

Michał Eckstein, Tomasz Miller, Ryszard Horodecki, Ravishankar Ramanathan

The study of quantum correlations within relativistic spacetimes, and the consequences of relativistic causality on information processing using such correlations, has gained much attention in recent years. In this paper, we establish a unified framework in the form of operational no-signalling constraints to study both nonlocal and temporal correlations wit

Jing Huang, Shujian Zhang, Lun Wang, Andrew Hard

Identifying specific and often complex behaviors from large language models (LLMs) in conversational settings is crucial for their evaluation. Recent work proposes novel techniques to find natural language prompts that induce specific behaviors from a target model, yet they are mainly studied in single-turn settings. In this work, we study behavior elicitati

Paul Orland, Lara San Martín Suárez, Toby Saunders-A'Court, Josef Svoboda

We explore the topological significance of the Gukov-Manolescu knot series $F_K$. We show that the leading coefficient of $F_K$ is a monomial and express its exponent in terms of the Hopf invariant for all homogeneous braid knots, and for fibered knots up to 12 crossings. As an application, we deduce an explicit formula for the Hopf invariant in terms of col

Hiren Kakkad, Alexander Ochirov, Shijie Zhang

This work is motivated by the recent evidence for a double-copy relationship between open- and closed-string amplitudes in Anti-de Sitter (AdS) space. At present, the evidence has the form of a double-copy relation for string-amplitude building blocks, which are combined using the multiple-polylogarithm (MPL) generating functions. These generate MPLs relevan

Theodoros Lagiotis

We define a once extended non-compact 3-dimensional TQFT $\mathcal{Z}$ from the data of a (potentially) non-semisimple modular tensor category. This is in the framework of generators and relations of [Bartlett et al., arxiv:1509.06811 (2015)], having disallowed generating 2-morphisms whose source is the empty. Moreover, we show that the projective mapping cl

Joon-Hwi Kim

We implement a probe counterpart of Newman-Janis algorithm, which Wick rotates the all-orders geodesic deviation equation into a part of exact spinning-particle equations of motion. Consequently, the gravitational dynamics of the Kerr black hole in its point-particle effective theory is completely constrained in the self-dual sector for a hidden symmetry, im

Jamie Portsmouth, Peter Kutz, Stephen Hill

OpenPBR is a physically based, standardized uber-shader developed for interoperable material authoring and rendering across VFX, animation, and design visualization workflows. This document serves as a companion to the official specification, offering deeper insight into the model's development and more detailed implementation guidance, including code exampl

Egor Makarenkov

Starting from a problem in elastoplasticity, we consider an optimization problem $C(c_1,c_2)=c_1+c_2\to \min$ under constraints $F_R^k(c_1,c_2)=a\cdot F^k(c_1,c_2)+b\cdot R^k(c_1,c_2)\ge 1$ and $F^k(c_1,c_2)\ge 1$, where both $F^k$ and $R^k$ non-linear, $a,b$ are constants, and $i\in\{1,2\}$ is an index. For each $(a,b)$ we determine which of the two values

Lars van der Laan, Nathan Kallus

Reliable long-horizon value prediction is difficult in offline reinforcement learning because fitted value methods combine bootstrapping, function approximation, and distribution shift, while standard guarantees often require Bellman completeness or realizability. We introduce Bellman calibration, a weak reliability criterion requiring that states assigned s

Sky CH-Wang, Justin Svegliato, Helen Appel, Jason Eisner

We present a method and dataset for fine-tuning language models with preference supervision using feedback-driven improvement chains. Given a model response, an annotator provides fine-grained feedback by marking ``liked'' and ``disliked'' spans and specifying what they liked or disliked about them. The base model then rewrites the disliked spans accordingly

Ritoban Datta, Abhijit Majumder

Modified thermal distributions (dispersion relations) are introduced within both the MATTER and LBT event generators used to describe jet modification in a heavy-ion collision, within the JETSCAPE framework. Hard partons, propagating through dense matter, scatter off the partonic substructure of the medium, leading to stimulated emission, accompanied by reco

Mike Walmsley, Steven Bamford, Hugh Dickinson, Tobias Géron

We introduce Galaxy Zoo Evo, a labeled dataset for building and evaluating foundation models on images of galaxies. GZ Evo includes 104M crowdsourced labels for 823k images from four telescopes. Each image is labeled with a series of fine-grained questions and answers (e.g. "featured galaxy, two spiral arms, tightly wound, merging with another galaxy"). Thes

Alaska Subedi

Ba$_2$IrO$_4$ has been refined in the tetragonal $I4/mmm$ phase without octahedral rotations, and its physical properties have been interpreted in this high-symmetry structure. However, the dynamical stability of this undistorted phase has not previously been questioned. It is important to establish whether other lower-symmetry structures are energetically m

Yuxi Cai, An Aloysius Wang, Chao He

A standard procedure to achieve accurate, precise, and fast polarization measurement is to choose analyzing and generating polarization states that yield an $\ell^2$-condition number optimized instrument matrix. This strategy works well for rotating-waveplate systems, where the accessible polarization states trace a curve on the Poincar\'e sphere and the cor

Kundan Singh

We present a software architecture to enable end user driven innovation of web multimedia communication applications. RTC Helper is a simple and easy-to-use software that can intercept WebRTC (web real-time communication) and related APIs in the browser, and change the behavior of web apps in real-time. Such customization can even be driven by the end user o

Deepak Babu Piskala

Automatic Speech Recognition (ASR) in professional settings faces challenges that existing benchmarks underplay: dense domain terminology, formal register variation, and near-zero tolerance for critical entity errors. We present ProfASR-Bench, a professional-talk evaluation suite for high-stakes applications across finance, medicine, legal, and technology. E

Quancheng Liu, Klaus Ziegler

Two-band Hamiltonians provide a typical description of topological band structures, in which the eigenfunctions can be characterized by a %Bloch vector field whose winding number that defines an integer topological invariant. This winding number is quantized and protected against continuous deformations of the Hamiltonian. Here we show that the Bloch vector

Panagiotis Theocharopoulos, Ajinkya Kulkarni, Mathew Magimai. -Doss

Large language models (LLMs) are increasingly considered for use in high-impact workflows, including academic peer review. However, LLMs are vulnerable to document-level hidden prompt injection attacks. In this work, we construct a dataset of approximately 500 real academic papers accepted to ICML and evaluate the effect of embedding hidden adversarial promp

Guillermo Lara, Georg Trenkler, Leonardo G. Trombetta

Black holes beyond General Relativity may carry non-standard charges that impact their phenomenology. We study how the scalar charge that is induced by the scalar-Gauss-Bonnet coupling is affected by the presence of a nontrivial kinetic term $K(X)$ in a test-field approximation. We discuss the corresponding kinetic screening in the asymptotically flat, stati

Dmitri M Orlov, Joseph McClenaghan, Jeff Candy, Jeremy D Lore

Achieving self-consistent performance predictions for ITER requires integrated modeling of core transport and divertor power exhaust under realistic impurity conditions. We present results from the first systematic power-flow and impurity-content study for the ITER 15 MA baseline scenario constrained directly by existing SOLPS-ITER neon-seeded divertor solut

Adam J. Harper

We give a short survey of the phenomenon of better than squareroot cancellation, specifically as it applies to averages of multiplicative character sums (such as $\frac{1}{r-1} \sum_{\chi \; \text{mod} \; r} |\sum_{n \leq x} \chi(n)|^{2q}$) thanks to their connection with so-called multiplicative chaos. We focus on the number theoretic aspects of the argumen

Édouard Bonnet

As the class $\mathcal T_4$ of graphs of twin-width at most 4 contains every finite subgraph of the infinite grid and every graph obtained by subdividing each edge of an $n$-vertex graph at least $2 \log n$ times, most NP-hard graph problems, like Max Independent Set, Dominating Set, Hamiltonian Cycle, remain so on $\mathcal T_4$. However, Min Coloring and k

Gargi Mukherjee

Let $\overline{p}(n)$ denote the overpartition function, and for $j\in \mathbb{N}$, $\Delta^r_j$ denote the $r$-fold applications of the shifted difference operator $\Delta_j$ defined by $\Delta_j(a)(n):=a(n)-a(n-j)$. The main goal of this paper is to derive an asymptotic expansion of $\Delta^r_j(\overline{p})(n)$ with an effective error bound which subseque

Igor Ermakov, Oleg Lychkovskiy

We present a symbolic implementation of recursion method for the dynamics of strongly correlated fermions on one-, two- and three-dimensional lattices. Focusing on two paradigmatic models, interacting spinless fermions and the Hubbard model, we first directly confirm that the universal operator growth hypothesis holds for interacting fermionic systems, manif

Jichen Feng, Yifan Zhang, Chenggong Zhang, Yifu Lu

Language agents increasingly require persistent worlds in which they can act, remember, and learn. Existing approaches sit at two extremes: conventional web frameworks provide reliable but fixed contexts backed by databases, while fully generative world models aim for unlimited environments at the expense of controllability and practical engineering. In this

Arnuv Tandon, Karan Dalal, Xinhao Li, Daniel Koceja

We formulate long-context language modeling as a problem in continual learning rather than architecture design. Under this formulation, we only use a standard architecture -- a Transformer with sliding-window attention. However, our model continues learning at test time via next-token prediction on the given context, compressing the context it reads into its

Rafał Meller

In this paper, we study the expectation of the operator norm of the random matrix (a_{ij} X_{ij}) for i,j <= n, under the assumption that the random variables (X_{ij}) are independent, symmetric and satisfy the moment growth condition ||X_{ij}||{2p} <= C ||X_{ij}||{p} for every p >= 1. We derive an upper bound expressed in terms of quantities that can be exp

Mohammed Baziyad, Manal Al Shohna, Tamer Rabie

Path planning is a fundamental component in autonomous mobile robotics, enabling a robot to navigate from its current location to a desired goal while avoiding obstacles. Among the various techniques, Artificial Potential Field (APF) methods have gained popularity due to their simplicity, real-time responsiveness, and low computational requirements. However,

Tiffany Ding, Isaac Gibbs, Ryan J. Tibshirani

We develop an online method that guarantees calibration of quantile forecasts at multiple quantile levels simultaneously. In this work, a sequence of quantile forecasts is said to be calibrated provided that its $\alpha$-level predictions are greater than or equal to the target value at an $\alpha$ fraction of time steps, for each level $\alpha$. Our procedu

Francesco Piatti, Thomas Cass, William F. Turner

We introduce a training-efficient framework for time-series learning that combines random features with controlled differential equations (CDEs). In this approach, large randomly parameterized CDEs act as continuous-time reservoirs, mapping input paths to rich representations. Only a linear readout layer is trained, resulting in fast, scalable models with st

Shin-ichiro Seki

In this paper, we give a new proof of Hirose--Sato's formula for the expansion of $\zeta(\{2\}^{a_1-1},3,\dots,\{2\}^{a_r-1},3,\{2\}^{c-1},1,\{2\}^{b_1},\dots, 1,\{2\}^{b_s})$ in the Hoffman basis, using the drop 1 relation.

Kang Du, Yirui Guan, Zeyu Wang

Intrinsic image decomposition is fundamental for visual understanding, as RGB images entangle material properties, illumination, and view-dependent effects. Recent diffusion-based methods have achieved strong results for single-view intrinsic decomposition; however, extending these approaches to multi-view settings remains challenging, often leading to sever

Svetlana Churina, Kokil Jaidka, Anab Maulana Barik, Harshit Aneja

The web's information ecosystem demands fact-checking systems that are both scalable and epistemically trustworthy. Automated approaches offer efficiency but often lack transparency, while human verification remains slow and inconsistent. We introduce Althea, a retrieval-augmented system that integrates question generation, evidence retrieval, and structured

Saurav Goyal, Sven-Olaf Moch, Vaibhav Pathak, V. Ravindran

Soft-Collinear Effective Theory is a framework for systematically organizing and resumming the logarithmic contributions that occur in high-energy reactions. It provides a factorized description of cross sections in terms of hard, jet, soft, and beam functions. As the latter are universal, they can be obtained from the well-known perturbative results in quan

Tim Vieira, Ryan Cotterell, Jason Eisner

Much algorithmic research in NLP aims to efficiently manipulate rich formal structures. An algorithm designer typically seeks to provide guarantees about their proposed algorithm -- for example, that its running time or space complexity is upper-bounded as a certain function of its input size. They may also wish to determine the necessary properties of the q

António Antunes, Noé Suchel

Fixed points of $N$ coupled Virasoro minimal models have recently been argued to provide large classes of compact unitary CFTs with $c>1$ and only Virasoro chiral symmetry. In this paper, we vastly increase the set of such potential irrational fixed points by considering couplings that break the maximal $G=S_N$ symmetry into various subgroups $H\subset G$. W

Guy F. de Teramond

Virtuality and coherence determine the limits of applicability of holographic concepts in QCD. In light-front quantization, the invariant mass controls the off-shell behavior of a physical process and thus provides a measure of its virtuality. In impact space, the corresponding quantity is the invariant transverse separation between quarks and gluons, $\zeta

Ali Hossary, Stefano Tomasin

Recent spam email techniques exploit visual effects in text messages, such as poisoning text, obfuscating words, and hidden text salting techniques. These effects were able to evade spam detection techniques based on the text. In this paper, we overcome this limitation by introducing a novel visual-based spam detection architecture, denoted as visual-based s

Tim Huesmann, Michael Klasen, Vishnu P. K

The Krauss-Nasri-Trodden (KNT) model provides a unified framework for addressing the smallness of neutrino masses (by a three-loop radiative mechanism) and the dark matter abundance (via thermal freeze-out) simultaneously. In this work, we investigate the implications of renormalization group effects on the model's parameter space. To this end, we perform a

Alexandre Nominé, Ayyoub El-Kasmi, Danielle Beaulieu, Outhmane Ouahri

Because of the enormous number of possible compositions, comparable to the number of stars in the universe, high-entropy alloys (HEAs) constitute a virtually inexhaustible materials space with highly versatile properties. Among these systems, HEAs are often proposed as potential substitutes for critical elements such as rare earths or platinum group metals.

Liang Li

Over the past two decades, the \textit{Swift} and \textit{Fermi} missions have identified a rare class of ``double-trigger'' gamma-ray bursts (GRBs) that produce two independent trigger events. These events are characterized by a sufficiently long quiescent period during which the on-board trigger system can reset, resulting in the subsequent emission being

Cassandra L. Jacobs, Andrés Buxó-Lugo, Anna K. Taylor, Marie Leopold-Hooke

The primary research questions of this paper center on defining the amount of context that is necessary and/or appropriate when investigating the relationship between language model probabilities and cognitive phenomena. We investigate whether whole utterances are necessary to observe probabilistic reduction and demonstrate that n-gram representations suffic

Masoud H. Nazari, Hamid Varmazyari, Antar Kumar Biswas, Umit Cali

This paper presents a comprehensive review of community-centric power system resilience, emphasizing the integration of community-level resilience considerations and techno-legal governance frameworks with engineering-based resilience enhancement strategies and data-driven approaches to address extreme events. Recent large-scale outages have demonstrated tha

Igor S. Sergeev

It is shown that the minimal depth of an optimal prefix circuit (i.e., a zero-deficiency circuit) on $N$ inputs with fanout bounded by $k$ is ${\log_{\alpha_k} N \pm O(1)}$, where $\alpha_k$ is the unique positive root of the polynomial ${2+x+ x^2+\ldots + x^{k-2}-x^k}$. This bound was previously known in the cases $k=2$ and $k=\infty$.

Emily Lu, Gabriel Perez, Peter Baker, Daniel Irving

Unravelling the complex processes governing battery degradation is critical to the energy transition, yet the efficacy of operando characterisation is severely constrained by a lack of Reliability, Representativeness, and Reproducibility (the 3Rs). Current methods rely on bespoke hardware and passive, pre-programmed methodologies that are ill-equipped to cap

R. J. Spieker, B. Krohnke, D. Zhai, A. Lopez Benet

We present a diffuse neutron and x-ray scattering study of structural, spin- and charge-density-wave fluctuations in the electrical insulator La$_{2-x}$Sr$_x$NiO$_4$. This lamellar nickelate is an isostructural analogue of the high-temperature cuprate superconductor La$_{2-x}$Sr$_x$CuO$_4$, for which recent experiments uncovered evidence for unusual structur

Zvi Bern, Enrico Herrmann, Radu Roiban, Michael S. Ruf

We compute the complete potential-graviton contributions to the conservative radial action and scattering angle for two non-spinning bodies in general relativity, accurate through fifth order in Newton's constant and including second-order self-force (2SF) effects. The calculation is carried out in the scattering-amplitude framework, combining the double cop

Mathew Schmidheiser, Milena Radenkovic

In this paper, we explore the behavior of the Epidemic and Wave DTN routing protocols in a realistic setting where individuals may wish to communicate with others for support regarding an act of questionable legality. We identify situations where using the Epidemic routing protocol may be more advantageous in such a scenario, and situations where using the W

Ahmad Abushattal, Nikolaos Georgakarakos, Mashhoor A. Al-Wardat, Bilal Algnamat

This work analyzes four Sun-like double-lined spectroscopic binary (SB2) systems by combining visual and spectroscopic observational data with Al-Wardat's atmospheric modeling method to accurately determine their fundamental parameters. For each system, we determine stellar masses, orbital parallaxes, effective temperatures, spectral types, semimajor axes, a