March 2026 arXiv papers — page 79

Jayita Lahiri, Gudrid Moortgat-Pick

We investigate CP-violation in the complex singlet extension of the general Two Higgs Doublet Model (2HDM) with Yukawa alignment condition. We first explore the possibility of explicit CP-violation in the extended scalar sector while the 125 GeV Higgs remains exactly Standard Model (SM)-like. We identify an additional source of CP violation in the complex si

Wang Zhou, Boran Duan, Haojun Ai, Ruiqi Lan

Recent vision-language models such as CLIP provide strong cross-modal alignment, but current CLIP-guided ReID pipelines rely on global features and fixed prompts. This limits their ability to capture fine-grained attribute cues and adapt to diverse appearances. We propose ALADIN, an attribute-language distillation network that distills knowledge from a froze

Zhijian Chen, Likai Wang, Lei Chen, Yaguang Dou

Large Language Models (LLMs) have shown promising potential in E-commerce community recommendation. While LLMs and Multimodal LLMs (MLLMs) are widely used to encode notes into implicit embeddings, leveraging their generative capabilities to represent notes with interpretable tags remains unexplored. In the field of tag generation, traditional close-ended met

Hikari Hanaki

The Schur $P$-, $Q$-multiple zeta functions were defined by Nakasuji and Takeda inspired by the tableau representation of Schur $P$-, $Q$-functions. While a product of two Schur $P$-functions expands as a linear combination of Schur $P$-functions, we obtain a similar expansion formula for the Schur $P$-multiple zeta functions by taking summation over the sym

Chandrodoy Chattopadhyay, Robert Maguire, Josh Ott, Thomas Schaefer

We describe numerical simulations of the critical dynamics near the superfluid phase transition. The calculations are based on an implementation of a stochastic hydrodynamic theory known as model F in the classification of Hohenberg and Halperin. This theory is expected to describe dynamic scaling near the lambda transition in liquid $^4$He, Bose-Einstein co

Carlos Borges, Rafael Ceja Ayala, Peter Nekrasov

We study the inverse problem of qualitatively recovering a supported cavity in a thin elastic plate governed by the flexural (biharmonic) wave equation, using far-field pattern measurements. We derive a reciprocity principle and a factorization of the far-field operator for the supported plate boundary conditions, and we analyze its range properties to justi

Junyi Ji, Derek Gloudemans, Gergely Zachár, William Barbour

The real-world potential of stop-and-go wave smoothing at scale remains largely unquantified. Smoothing freeway waves requires opening a gap large enough for them to dissipate, but that gap is often impractically large. We propose a counterfactual wave-smoothing benchmark that reconstructs a smooth, feasible trajectory from each empirical trajectory by solvi

Hehai Lin, Yu Yan, Zixuan Wang, Bo Xu

Automatic Multi-Agent Systems (MAS) generation has emerged as a promising paradigm for solving complex reasoning tasks. However, existing frameworks are fundamentally bottlenecked when applied to knowledge-intensive domains (e.g., healthcare and law). They either rely on a static library of general nodes like Chain-of-Thought, which lack specialized expertis

Terence L. J. Harris

It is shown that Schr\"odinger maximal inequalities over fractals are equivalent to the $L^2$ decay rates of Fourier transforms of fractal measures over the paraboloid. A similar connection is shown between the wave equation and cone averages. One implication is well-known and follows from the Kolmogorov-Seliverstov-Plessner method, but the other implication

Wihan van der Heever, Keane Ong, Ranjan Satapathy, Erik Cambria

This paper proposes a refutation-validated framework for aspect-based sentiment analysis in financial markets, addressing the limitations of correlational studies that cannot distinguish genuine associations from spurious ones. Using X data for the energy sector, we test whether aspect-level sentiment signals show robust, refutation-validated relationships w

Matthias Flach, Achim Krause, Baptiste Morin

We define and study an integral refinement of the inverse of the Bloch-Kato exponential map which we call the de Rham logarithm. Our main tool to analyze the de Rham logarithm is the syntomic logarithm, a certain limit construction based on the theory of filtered prismatic cohomology initiated by Antieau, Krause and Nikolaus. We use the syntomic logarithm to

Shiori Furukawa, Sho Tsugawa

Although beneficial information abounds on social media, the dissemination of harmful information such as so-called ``fake news'' has become a serious issue. Therefore, many researchers have devoted considerable effort to limiting the diffusion of harmful information. A promising approach to limiting diffusion of such information is link deletion methods in

James Bell-Clark, Albert Cheu, Adria Gascon, Jonathan Katz

In this work, we identify a set of side-channels in our Confidential Federated Compute platform that a hypothetical insider could exploit to circumvent differential privacy (DP) guarantees. We show how DP can mitigate two of the side-channels, one of which has been implemented in our open-source library.

Rostyslav Kozhan, Marcus Vaktnäs

We investigate two distinct formulations of Laurent multiple orthogonal polynomials on the unit circle, introduced in arXiv:2410.12094 and arXiv:2601.04783 respectively. For the first formulation, we prove that all zeros lie strictly within the complex open unit disk for any Angelesco or AT system. For the second formulation, we establish normality of all in

M. D. Filipović, Z. J. Smeaton, A. C. Bradley, R. Kothes

We report diffuse extended radio-continuum emission spatially coinciding with the IR source WISEA J094409.17-751012.8, and a semi-variable star, V687 Carinae. We use 944 MHz radio data from the large-scale Evolutionary Map of the Universe (EMU) survey to analyse this diffuse emission (EMU J094412-751016), which we nickname "Anglerfish". We investigate if the

Nakyung Lee, Soobin Cho, Jiwoong Park, Gyuyeong Kim

We present GateANN, an I/O-efficient SSD-based graph ANNS system that supports filtered vector search on an unmodified graph index. Existing SSD-based systems either waste I/O by post-filtering, or require expensive filter-aware index rebuilds. GateANN avoids both by decoupling graph traversal from vector retrieval. Our key insight is that traversing a node

Jason Fulman, Adrian Röllin

The Eulerian number A(n,k) counts permutations of n symbols with exactly k descents. Motivated by problems in cryptography, several authors have studied the proportion of permutations whose number of descents lies in a fixed congruence class mod b, and its convergence to 1/b. We give two proofs of explicit error bounds for this convergence, one using Stein's

Jeehoon Park, Jaewon Yoo

We develop a perturbative algorithm for constructing formal flat $F$-manifold structures on the cohomologies of dGBV (differential Gerstenhaber-Batalin-Vilkovisky) algebras associated with Landau-Ginzburg models. As an application, this approach provides a perturbative construction of formal flat $F$-manifold structures on two important objects: the Jacobian

James Wedgwood, Aashiq Muhamed, Mona T. Diab, Virginia Smith

Preference alignment is usually achieved by weight-updating training on preference data, which adds substantial alignment-stage compute and provides limited mechanistic visibility. We propose Dynamic SAE Steering for Preference Alignment (DSPA), an inference-time method that makes sparse autoencoder (SAE) steering prompt-conditional. From preference triples,

Yubo Li, Ramayya Krishnan, Rema Padman

Patient education materials for solid-organ transplantation vary substantially across U.S. centers, yet no systematic method exists to quantify this heterogeneity at scale. We introduce a framework that grounds the same patient questions in different centers' handbooks using retrieval-augmented language models and compares the resulting answers using a five-

Bernt Tore Jensen, Liam Riordan, Xiuping Su

A class of subcategories GP $B$ of the Grassmannian cluster category CM $C_{k, n}$ was constructed by Jensen--King--Su from certain superorders $B$ of $C_{k, n}$, which they showed are in bijection with Grassmannian positroids of type $(k, n)$. We prove that GP $B$ admits a cluster substructure of CM $C_{k, n}$, giving rise to a cluster algebra $A_{clu}$. Th

Dougal Stewart, Kenneth Duru

A recent study by Gassner et al. [J. Sci. Comput. 90:79 (2022)] demonstrates that local energy stability--that is, ensuring the asymptotic numerical growth rate does not exceed the continuous growth rate--is crucial for achieving accurate numerical simulations of nonlinear conservation laws. While nonlinear entropy stability is necessary for numerical stabil

Xiao Wang, Yiyang Wu, Yuntian Wang, Md Sadman Sakib Rahman

Despite offering high sensitivity, a high signal-to-noise ratio, and a broad spectral range, single-pixel imaging (SPI) is limited by low measurement efficiency and long data-acquisition times. To address this, we propose a wavelength-multiplexed, spatially incoherent diffractive optical processor combined with a compact/shallow digital artificial neural net

Shin-ichi Kimura, Hironao Suwa, Kangle Yuan, Hiroshi Watanabe

The temperature and strain dependences of the optical conductivity spectrum of hexagonal manganese telluride (MnTe) were measured, revealing absorption in the terahertz (THz) region from spin-split bands to acceptor levels. The temperature dependence of the THz absorption peak is consistent with that of a ferromagnetic phase transition, even though MnTe exhi

Tae-Eun Song

LLM coding benchmarks face a credibility crisis: widespread solution leakage and test quality issues undermine SWE-bench Verified, while existing detection methods--paraphrase consistency, n-gram overlap, perplexity analysis--never directly observe whether a model reasons or recalls. Meanwhile, simply repeating verification degrades accuracy: multi-turn revi

Terence Tao

Classical (or ``global'') Bernstein theory establishes sharp control on entire functions of exponential type that are bounded and real-valued on the real axis. We localize some of this theory to rectangular regions $\{ x+iy: x \in I, 0 \leq y \leq y_0 \}$, showing that Bernstein-type bounds with acceptable errors can continue to hold for functions holomorphi

Shuchen Meng, Xupeng Chen

We show that AI-driven investment strategies are inherently self-defeating at scale. As AI adoption rises, three mutually reinforcing channels -- signal crowding, performative signal erosion, and Red Queen competition -- compress excess returns. We derive the alpha half-life $h(ϕ) = \ln 2/[θ+ δ(ϕ)]$, where $θ$ is the natural mean-reversion rate and $δ(ϕ) = N

Nitin Vetcha, Dianbo Liu

Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with primary challenges being concept drift and the high cost of gradient-based adaptation. Traditional fine-tuning (FT) struggles to adapt to non-stationary data streams without resulting in catastrophic for getting or

Hasret Ozan Sevim

On-chain lending has expanded across multiple distributed ledgers as DeFi becomes increasingly multi-chain. This environment introduces novel technical and financial mechanisms, particularly cross-blockchain communication and asset transfer protocols, yet cross-chain elements remain understudied in lending protocol risk management. To address this gap, we ap

Nazmi Yılmaz

We introduce a method for identifying weak periodic components in pre-earthquake seismic waveforms by examining the scale-index response of a driven Duffing chaotic oscillator. This nonlinear setup helps detect and classify subtle deterministic features buried in low-amplitude, noisy seismic records. We apply this approach to seismic data collected before th

Zigui Wang, Minghui Sun, Jiang Shu, Matthew M. Engelhard

Unstructured Electronic Health Record (EHR) data, such as clinical notes, contain clinical contextual observations that are not directly reflected in structured data fields. This additional information can substantially improve model learning. However, due to their unstructured nature, these data are often unavailable or impractical to use when deploying a m

Charles Bickham, Minh Duc Chu, Arianna Yuan, Valerie Lookingbill

Whether genuine communities can form on algorithmically-driven short-form video platforms like TikTok remains an open question, given that user interactions are often brief, dispersed, and difficult to trace. Building on theories of tie strength and online community formation, we examine whether eating disorder (ED) discourse on TikTok exhibits behavioral an

Philipp Girichidis, Erika Rea, Ralf S. Klessen, Michael C. H. Yeung

The Local Bubble (LB) is a hot, low-density cavity in the solar neighborhood, inside which the Solar System is currently located. The X-ray emission from such bubbles is strongly governed by the gas density, temperature, and the effects of line-of-sight column density. Yet the physical processes that control the formation and evolution of this emission remai

Grace Gardella, Mira Varma, Peter Schweitzer

We show that the leading non-analytic terms in the small-t expansion of the energy momentum tensor (EMT) form factors of an electrically charged particle in QED can be correctly derived in a classical model of the electron by Bialynicki-Birula. Based on the lucidity of the employed exactly solvable model, we comment also on the recently proposed concept of a

Rustem Khasanov

The thermodynamic critical field $B_{\rm c}$ provides direct access to the superconducting condensation energy, yet its pressure dependence has been studied much less extensively than that of the transition temperature. Here, muon-spin-rotation/relaxation measurements of the thermodynamic critical field $B_{\rm c}$ of elemental Pb under hydrostatic pressure

Naresh Shyaga, Pankaj Bhardwaj, Rajib Sarkar, Jagadish Rajendran

Among two-dimensional magnetic materials, CrSBr has attracted considerable attention owing to its coexistence of ferromagnetic and antiferromagnetic ordering, which depends sensitively on crystallographic orientation. An additional distinguishing feature of CrSBr is its highly anisotropic Fermi surface in momentum space. In this work, we present a comprehens

The VERITAS Collaboration, A. Archer, P. Bangale, J. T. Bartkoske

Microquasars such as SS 433 are considered potential contributors to cosmic rays up to the knee of the cosmic ray energy spectrum ($\sim4\,\mathrm{PeV}$), where a transition in the dominant acceleration processes is expected. The SS 433 system, located within the W50 supernova remnant, is a Galactic microquasar with relativistic jets interacting with the sur

A. D. Molchanova, L. H. Yin, L. P. Gao, W. H. Song

Out-of-plane and in-plane electric polarization, which rarely coexist in a two-dimensional (2D) ferroelectric material, offer different advantages in ferroelectricity-based devices. Here, we report the coexistence of in-plane and out-of-plane electric dipoles, along with various phase transitions, in 2D van der Waals layered TlGaS2 single crystal. Quantum pa

Naoshi Uchihira

The emergence of generative AI is bringing about a significant transformation in knowledge management. Generative AI has the potential to address the limitations of conventional knowledge management systems, and it is increasingly being deployed in real-world settings with promising results. Related research is also expanding rapidly. However, much of this w

Min Peng, Yuanjun Tang, Dianmeng Dong, Yang Zhang

The ultrawide-bandgap semiconductor $β$-Ga2O3 holds exceptional promise for next-generation power electronics and deep-ultraviolet optoelectronics, yet its widespread application is hindered by the lack of cost-effective, high-quality heteroepitaxial thin films. Here, we demonstrate an interpretable machine learning framework that efficiently navigates the c

Tim Hageman

Standard phase-field fracture methods are rooted in brittle fracture theory and therefore do not inherently prescribe a material strength for crack nucleation, while also struggling to capture cohesive fracture behaviour. Recent eigenstrain-based formulations overcome both limitations by introducing fracture eigenstrains that decouple the strength surface fr

Carlos Contreras, Jose Garrido, Eugene Levin

In this paper we discuss the multiplicity distribution in the deep inelastic processes in the frame work of high energy QCD. We obtained three results. First, we get the new derivation of the equations for the cross sections of productions of $n$-cut Pomerons in the final states ($σ_n$). These equations coincide with the equations that have been derived usin

Luca Giannoni, Frédéric Lange, Ilias Tachtsidis

Since the publication of our review article Hyperspectral imaging solutions for brain tissue metabolic and hemodynamic monitoring: past, current and future developments in 2018, the technological and applicational landscape of the use of hyperspectral imaging (HSI) in brain sciences has evolved and transformed significantly. The number of studies and works w

Bulent Haznedar, Levent Karacan

Transformers have achieved remarkable progress in time series forecasting, yet their reliance on deterministic dot-product attention limits their capacity to model uncertainty and nonlinear dependencies across multivariate temporal dimensions. To address this limitation, we propose FISFormer, a Fuzzy Inference System-driven Transformer that replaces conventi

Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel, Lei Pan

The rapid expansion of the Internet of Things (IoT) and its integration with backbone networks have heightened the risk of security breaches. Traditional centralized approaches to anomaly detection, which require transferring large volumes of data to central servers, suffer from privacy, scalability, and latency limitations. This paper proposes a lightweight

Yi Pang, Robert J. Saskowski

We consider hidden symmetries arising from U-duality in the dimensional reduction of non-maximal higher-derivative supergravities to three dimensions. In particular, we consider the $G_{2(2)}$ symmetry of minimal five-dimensional supergravity and the $O(d+p+1,d+1)$ symmetry of bosonic and heterotic string theory on $T^d$. Using a group theory argument, we sh

Kyla D. Jones, Alexander W. Dowling

We introduce Bayesian Information-Theoretic Sampling for hierarchical GAussian Process Surrogates (BITS for GAPS), a framework enabling information-theoretic experimental design of Gaussian process-based surrogate models. Unlike standard methods, which use fixed or point-estimated hyperparameters in acquisition functions, our approach propagates hyperparamet

Jeffrey Galkowski, Euan A. Spence

We consider the numerical solution of high-frequency scattering problems modeled by the Helmholtz equation with a bounded obstacle. Although the analysis of this problem dates back at least 50 years, over the past decade or so, tools and techniques from $\textit{semiclassical analysis}$ have provided a new perspective and been used to settle several long-sta

Sikai Cheng, Reza Zandehshahvar, Haoruo Zhao, Daniel A. Garcia-Ulloa

Channel state information (CSI) prediction is a promising strategy for ensuring reliable and efficient operation of massive multiple-input multiple-output (mMIMO) systems by providing timely downlink (DL) CSI. While deep learning-based methods have advanced beyond conventional model-driven and statistical approaches, they remain limited in robustness to prac

Akihiko Sekine, Ryo Murakami, Yoshiyasu Doi

The quantum transduction, or equivalently quantum frequency conversion, is vital for the realization of, e.g., quantum networks, distributed quantum computing, and quantum repeaters. The microwave-to-optical quantum transduction is of particular interest in the field of superconducting quantum computing, since interconnecting dilution refrigerators is consid

Naisargi Kanabar, Seiichiro Higashiya, Daniele Cherniak, Devendra Sadana

This study examines the distribution and evolution of lithium in both anode and cathode materials of commercial lithium-ion coin cells subjected to high C-rate cycling, providing insights into the mechanisms of lithium loss, trapping, and plating. Cells were cycled at 1C to 3C rates, and post-mortem analysis was performed using Li nuclear reaction analysis (

M. McEneaney, A. Vossen

The polarization of $Λ$ hyperons is preserved in the angular distribution of their decay products. This property allows one to study the spin structure of the $Λ$. In Semi-Inclusive Deep Inelastic Scattering where a high energy lepton interacts with a nucleon target and one or more hadrons and the scattered lepton are detected in the final state, the probabi

Cong Qi, Hanzhang Fang, Siqi Jiang, Xun Song

Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity, but its complexity, which is marked by high dimensionality, sparsity, and batch effects, which poses major computational challenges. Transformer-based models have made significant advances in this domain but are often limited by their quadratic complexity and s

Christian Alexander Holz, Christian Bader, Markus Enzweiler, Matthias Drüppel

We present a modular, production-ready approach that integrates compact Neural Network (NN) into a Kalmanfilter-based Multi-Object Tracking (MOT) pipeline. We design three tiny task-specific networks to retain modularity, interpretability and eal-time suitability for embedded Automotive Driver Assistance Systems: (i) SPENT (Single-Prediction Network) - predi

Giuliano Rosella, Sara Ugolini

The logico-algebraic study of Lewis's hierarchy of variably strict conditional logics has been essentially unexplored, hindering our understanding of their mathematical foundations, and the connections with other logical systems. This work aims to fill this gap by providing a comprehensive logico-algebraic analysis of Lewis's logics. We begin by intr

Robert Reischke, Dennis Neumann, Klara Antonia Bertmann, Steffen Hagstotz

One of the key limitations of large-scale structure surveys of the current and future generation, such as Euclid, LSST-Rubin or Roman, is the influence of feedback processes on the distribution of matter in the Universe. This effect, called baryonic feedback, modifies the matter power spectrum on non-linear scales much stronger than any cosmological paramete

Ricardo Schiappa, Maximilian Schwick, Noam Tamarin

It was recently shown how to account for all instantons of hermitian matrix models via (anti-) eigenvalue-tunneling -- including both exponentially-suppressed and exponentially-enhanced transseries-transmonomials which are predicted by resurgence. Matrix-model eigenvalue-tunneling corresponds to ZZ-branes. The present work shows how matrix-model anti-eigenva

Naoki Kitazawa

This is a note on the graphs of two smooth real-valued functions in the plane with no intersection and the natural map onto the region surrounded by them with the canonical projection to the line composed, yielding its Reeb space. The Reeb space of a real-valued function on a topological space is the set of all connected components of all level sets and topo

A. Iosevich, A. Mayeli, E. Wyman

We study spectral synthesis for measures supported on thin subsets of compact Riemannian manifolds. We prove that under natural non-concentration conditions, such measures admit quantitative spectral synthesis, with explicit stability bounds. We show that this phenomenon depends strongly on the underlying geometry. On the torus, synthesis holds under broad a

Tom Meyerovitch, Aidan Young

The covering radius of a shift space is a quantity of interest for information-theoretic applications of data transmission over noisy channels. We prove that the covering radius of a primitive sofic shift is a rational number, and describe an algorithm to compute the covering radius from a labeled graph presentation.

Cosimo Spera

We introduce a new paradigm for task-oriented dialogue systems: safety certification as a computational primitive for answer reuse. Current systems treat each turn independently, recomputing answers via retrieval or generation even when they are already derivable from prior state. We show that in capability-based systems, the safety certification step comput

Ehsan Misaghi, Sean T Berkowitz, Bing Yu Chen, Qingyu Chen

Large language models (LLMs) show potential for ophthalmic clinical reasoning, yet individual models risk introducing harm. We evaluated whether multi-agent LLM deliberative councils improve diagnostic performance and mitigate harm compared to individual LLMs. In a comparative cross-sectional study, we assessed 12 individual LLMs and three multi-agent counci

Md Tusher Ahmed, Nikhil Chandra Admal

Strain soliton networks strongly influence the structural and electronic properties of heterodeformed bilayer systems, yet their design remains challenging due to the high dimensionality of heterodeformation space and the absence of a direct map between deformation and network geometry. In this work, we introduce a geometric framework that establishes a one-

Alex Krasnok

Negative and complex numbers are so familiar in modern mathematics, physics, and engineering that it is easy to forget how uncertain their status once was. They did not become established through a single route. This article follows four linked processes in their stabilization: operational use, formal legitimation, pedagogical normalization, and physical nat

Julian Bellavita, Lorenzo Pichetti, Thomas Pasquali, Flavio Vella

The multiplication of two sparse matrices, known as SpGEMM, is a key kernel in scientific computing and large-scale data analytics, underpinning graph algorithms, machine learning, simulations, and computational biology, where sparsity is often highly unstructured. The unstructured sparsity makes achieving high performance challenging because it limits both

Aly Farahat

We develop a practical framework for livelock analysis in self-disabling unidirectional ring protocols. Klinkhamer and Ebnenasir established that livelock detection for parameterized rings is $\Sigma^0_1$-complete and livelock-freedom verification is $\Pi^0_1$-complete, via reduction from the periodic domino problem. We observe that lifting the analysis from

Pierros Ntelis, Jackson Levi Said

We develop a novel analytical dynamical analysis to derive precise energy density ratio evolutions for the $\phi$CDM and $poly\Lambda$CDM models, comparing them to the standard $\Lambda$CDM model and validating against numerical solutions. Analytical solutions for the quintessence, i.e. $\phi$CDM, show sub percent agreement with $\Lambda$CDM with greater rel

Kirill Simonov, Farehe Soheil, Shaily Verma

For a given graph $G$ and a subset of vertices $S$, a \emph{distance preserver} is a subgraph of $G$ that preserves shortest paths between the vertices of $S$. We distinguish between a \emph{subsetwise} distance preserver, which preserves distances between all pairs in $S$, and a \emph{pairwise} distance preserver, which preserves distances only between spec

Boris Kruglikov

We classify all maximal symmetry models of CR dimension 1, depending on their Bloom-Graham and Tanaka types, give coordinate realization to some of those models and prove a general extension principle.

Shuai Wang, Yinan Yu

Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks. Knowledge Base Question Answering (KBQA), which leverages structured Knowledge Graphs (KGs) exemplifies this challenge due to the need for accurate multi-hop reasoning. Existing approaches typically perform sequential

Shuai Wang, Yinan Yu, Earl Barr, Dhasarathy Parthasarathy

Multidisciplinary Software Development (MSD) requires domain experts and developers to collaborate across incompatible formalisms and separate artifact sets. Today, even with AI coding assistants like GitHub Copilot, this process remains inefficient; individual coding tasks are semi-automated, but the workflow connecting domain knowledge to implementation is

Lanbo Xu, Liang Guo, Caigui Jiang, Cheng Wang

Online monocular 3D reconstruction enables dense scene recovery from streaming video but remains fundamentally limited by the stability-adaptation dilemma: the reconstruction model must rapidly incorporate novel viewpoints while preserving previously accumulated scene structure. Existing streaming approaches rely on uniform or attention-based update mechanis

Taejin Park

When organisations adopt commercial AI systems for decision support, they inherit value judgements embedded by vendors that are neither transparent nor renegotiable. The governance puzzle is not whether AI can support decisions but which recommendations the system can actually produce given how its vendor has configured it. I formalise this as a behavioural

Qiaorong S. Yu, Zhaoze Wang, Vijay Balasubramanian

Hippocampal place and time cells encode spatial and temporal aspects of experience. Both have the same neural substrate, but have been modeled as having different functions and mechanistic origins, place cells as continuous attractors, and time cells as leaky integrators. Here, we show that both types emerge from two dynamical regimes of a single recurrent n

Jae Ho Choi, Ian Tice

We study traveling wave solutions to the free boundary problem associated to a generalized Navier-Stokes Fourier system, which models a viscous, incompressible, heat-conducting fluid. The fluid is assumed to occupy a horizontally infinite strip-like domain with flat rigid bottom and moving upper surface. The fluid is acted upon by gravity as well as external

Ziqi Liu, Wei Yu, Sean Victor Hum

This paper presents a physics-based channel modeling and optimization framework for reconfigurable intelligent surface (RIS)-assisted downlink multi-user multiple-input single-output (MU-MISO) communication systems in site-specific environments. A hybrid ray-tracing (RT) and full-wave electromagnetic analysis approach is developed to construct a deterministi

Altamirano-Muñiz Emilio Fernando

This paper presents the development of a documented program capable of solving idealized beam models, such as those commonly used in textbooks and academic exercises, from drawings made by a person. The system is based on computer vision and statistical learning techniques for the detection and visual interpretation of structural elements. Likewise, the main

Antonio López Neumann, Piotr W. Nowak

We establish and explore the correspondence between positive functionals and cocycles in higher unitary cohomology. We generalize the classical cocycle version of the Gelfand-Naimark-Segal construction to higher degrees and apply it to characterize vanishing of higher unitary cohomology as an extension property for positive functionals. We also prove that un

Shuai Wang, Dhasarathy Parthasarathy, Robert Feldt, Yinan Yu

Large language models (LLMs) have shown impressive capabilities in code generation. However, because most LLMs are trained on public domain corpora, directly applying them to real-world software development often yields low success rates, as these scenarios frequently require domain-specific knowledge. In particular, domain-specific tasks usually demand high

Zongqi Hu, Weiqi Meng, Bai Cui

Optimal transmission switching (OTS) determines which transmission lines to remove from service to minimize dispatch costs. Unlike topology design, it alters the operational status of operating lines. Sensitivity-based methods, as advanced optimization techniques, select lines whose outage yields a significant cost reduction. However, these methods overlook

Régulo E. Ávila-Martínez, Luis Rouco, Javier Renedo, Lukas Sigrist

Grid-forming voltage source converters (GFM-VSCs) play a crucial role in the stability of power systems with large amounts of converter-based generation. Transient stability (angle stability under large disturbances) is a critical limiting factor in stressed power systems. Previous studies have proposed control strategies in GFM-VSCs to improve transient sta

Dmytro Humeniuk, Mohammad Hamdaqa, Houssem Ben Braiek, Amel Bennaceur

Extensive simulation-based testing is important for assuring the safety of autonomous driving systems (ADS). However, generating safety-critical traffic scenarios remains challenging because failures often arise from rare, complex interactions with surrounding vehicles. Existing automatic scenario-generation approaches frequently fail to distinguish genuine

Jingchen Sun, Shaobo Han, Deep Patel, Wataru Kohno

Knowledge distillation establishes a learning paradigm that leverages both data supervision and teacher guidance. However, determining the optimal balance between learning from data and learning from the teacher is challenging, as some samples may be noisy while others are subject to teacher uncertainty. This motivates the need for adaptively balancing data

Arundhati Goldar, Nirmalya Kajuri, Rhitaparna Pal

Grinberg and Maldacena showed that heavy thermal one-point functions in AdS/CFT can encode complex geodesics reaching a black hole singularity. We study the de Sitter analogue in three-dimensional Schwarzschild--de Sitter space, restricting to the finite cyclic quotients $\mathrm{dS}_3/\mathbb Z_q$. We define a one-point function through a differentiate dict

Jeanne McClure, Gregg Gerdau

Global corporate AI investment reached $252.3 billion in 2024, yet only 6% of firms report significant earnings impact. This article argues that AI project failure is fundamentally an organizational learning problem rather than a technology deficit. Drawing on a systematic synthesis of 19 large-scale industry and academic sources, including surveys of nearly

Nikolaos Ignatiadis, Ruodu Wang, Aaditya Ramdas

After the seminal Benjamini-Hochberg (BH) procedure for controlling the false discovery rate (FDR) was proposed, dozens of papers have attempted to improve its power by adapting to the unknown proportion of nulls. We observe that most null proportion estimates are simply compound e-values in disguise, and thus most adaptive FDR procedures can be interpreted

Shivani Kamtikar, Kendall Koe, Justin Wasserman, Samhita Marri

As robotic systems increasingly operate in unstructured, cluttered, and previously unseen environments, there is a growing need for manipulators that combine compliance, adaptability, and precise control. This work presents a real-time hybrid rigid-soft continuum manipulator system designed for robust open-world object reaching in such challenging environmen

Kazuhito Mizuyama

We develop a theoretical framework to describe quasiparticle resonance states within the Hartree-Fock-Bogoliubov (HFB) theory by integrating the complex-scaled Jost function method with the Autonne-Takagi factorization. The HFB completeness relation is derived from the analytical properties of the Green's function using contour integration in the complex ene

Robert Viseur, Nicolas Jullien

The rise of generative artificial intelligence (GAI) has led to alarming predictions about its environmental impact. However, these predictions often overlook the fact that the diffusion of innovation is accompanied by the evolution of products and the optimization of their performance, primarily for economic reasons. This can also reduce their environmental

Mariela M. Nina, Caio Veloso Costa, Lilian Berton, Didier A. Vega-Oliveros

Although large language models have transformed natural language processing, their computational costs create accessibility barriers for low-resource languages such as Brazilian Portuguese. This work presents a systematic evaluation of Parameter-Efficient Fine-Tuning (PEFT) and quantization techniques applied to BERTimbau for Question Answering on SQuAD-BR,

Jielin Qiu, Liangwei Yang, Ming Zhu, Wenting Zhao

During live sales calls, customers frequently ask detailed product questions that require representatives to manually search internal databases and CRM systems. This process typically takes 25-65 seconds per query, creating awkward pauses that hurt customer experience and reduce sales efficiency. We present SalesCopilot, a real-time AI-powered assistant that

Gregory M. Ruddell

As large language models are deployed as autonomous agents with tool execution privileges, a critical assumption underpins their security architecture: that model errors are detectable at runtime. We present empirical evidence that this assumption fails for two of three instruction-following models evaluable for conflict detection. We introduce governability

Alba Barka, Eduardo Cristo, Ângela R. G. Santos, Nuno C. Santos

Stellar activity remains one of the main limitations in the detection of Earth-like planets using radial velocity (RV) measurements. The Sun, as the only star for which surface features can be spatially resolved, offers a unique testbed for studying the impact of active regions on RV and photometric variability. Using SOAPv4, we modelled solar RV and photome

Jarod Alper, Daniel Halpern-Leistner

Moduli theory has captured the imagination of algebraic geometers for at least two centuries. Up until the end of the 20th century, moduli spaces were constructed and studied by rigidifying the moduli problem using extrinsic data and applying geometric invariant theory. Over the last several decades, there has been a paradigm shift toward studying moduli pro

Jean-Christophe Pain

Toeplitz matrices arise naturally in harmonic analysis, operator theory, and numerical analysis. In this note we investigate Toeplitz matrices whose coefficients depend on the matrix size through a scaled kernel $a_k=f(k/n)$. We show that the empirical mean of their eigenvalues converges to a weighted integral of $f$, where the weight $1-|x|$ reflects the de

Guang Yang, Ziye Geng, Yihang Chen, Changqing Luo

Adversarial-example-based fingerprinting approaches, which leverage the decision boundary characteristics of deep neural networks (DNNs) to craft fingerprints, have proven effective for model ownership protection. However, a fundamental challenge remains unresolved: how far a fingerprint should be placed from the decision boundary to simultaneously satisfy t

Haodong Zheng, Gabriele M. Caddeo, Andrei C. Jalba, Wijnand A. IJsselsteijn

We present an active tactile exploration framework for joint object recognition and 6D pose estimation. The proposed method integrates wrist force/torque sensing, GelSight tactile sensing, and free-space constraints within a Bayesian inference framework that maintains a belief over object class and pose during active tactile exploration. By combining contact

Kazi Noshin, Sharifa Sultana

While concerns about ChatGPT-induced harms due to sycophancy and other behaviors, including gaslighting, have grown among researchers, how users themselves experience and mitigate these harms remain largely underexplored. We analyze Reddit discussions to investigate what concerns users report and how they address them. Our findings reveal five distinct user-

Haihan Nan, Emmanuel Obeng Frimpong, Zhi Tian, Yue Wang

Radio map estimation (RME), which predicts wireless signal metrics at unmeasured locations from sparse measurements, has attracted growing attention as a key enabler of intelligent wireless networks. The majority of existing RME techniques employ grid-based strategies to process sparse measurements, where the pursuit of accuracy results in significant comput

I. Sebastian Buhai

Extreme economic outcomes are not shaped by tails alone. They are also shaped by unequal access to opportunities. This paper develops a theory of heterogeneous extremes by taking the distribution of opportunity access as the object of study. In a mixed Poisson search setting, normalized maxima admit a Laplace mixture representation that yields order comparis