April 2026 arXiv papers — page 77

Anjali Singh, Christopher Brooks, Warren Li, Juho Kim

Generating hints for incorrect code is a cognitively demanding task that fosters learning and metacognitive development. This study investigates three designs for personalized, scalable, and reflective hint-writing activities within a data science course: (i) writing a hint independently, (ii) writing a hint with on-demand AI assistance, and (iii) deferred A

Huy Hoang Le, Haoguang Wang, Christian Moya, Marcos Netto

Neural surrogates for stiff differential-algebraic equations (DAEs) face two barriers: soft-constraint methods leave algebraic residuals that stiffness amplifies into errors, and hard-constraint methods require trajectory data from stiff integrators. We introduce an extended Newton implicit layer that enforces algebraic constraints exactly and reduces fast d

Yasser Saleem, Paweł Potasz, Anna Dyrdał, Björn Trauzettel

We study twisted bilayer WSe$_2$ within a continuum moir\'e model and introduce a method for treating finite geometries directly in the continuum framework, overcoming limitations associated with momentum-space formulations and Wannier obstructions. By projecting a confinement potential onto bulk moir\'e eigenstates, we obtain a real-space description of edg

Ryusei R. Kano, Tsutomu T. Takeuchi, Erina R. Kawamoto, Ryosuke S. Asano

Dust plays a crucial role in galaxy evolution by shaping the spectral energy distribution (SED) and star formation history. However, standard models often underestimate the infrared luminosity of high-redshift galaxies ($z \sim 8$), leading to the so-called dust budget crisis. In this work, we modify the theoretical framework by focusing on compact star-form

Tanmay Karmakar, Rosh Roy, Lavkesh Lachhvani, Raju Daniel

We report the experimental observation of highly nonlinear coherent structures in a linear magnettized plasma characterized by a strong background density gradient and significant ExB velocity shear under high ion-neutral collisionality. These structures, identified as drift acoustic waves, exhibit large normalized density fluctuations reaching amplitudes of

Hongnan Ma, Han Wang, Shenglin Wang, Tieyue Yin

Large language models can generate plausible game code, but turning this capability into \emph{iterative creative improvement} remains difficult. In practice, single-shot generation often produces brittle runtime behavior, weak accumulation of experience across versions, and creativity scores that are too subjective to serve as reliable optimization signals.

Matt Franchi, Madiha Zahrah Choksi, Harold Triedman, Helen Nissenbaum

Information handling practices of LLM agents are broadly misaligned with the contextual privacy expectations of their users. Contextual Integrity (CI) provides a principled framework, defining privacy as the appropriate flow of information within context-relative norms. However, existing approaches either double inference cost via supervisor-assistant archit

Shilei Luo, Zhiqi Zhang, Hengchen Dai, Dennis Zhang

AI agents powered by large language models are increasingly acting on behalf of humans in social and economic environments. Prior research has focused on their task performance and effects on human outcomes, but less is known about the relationship between agents and the specific individuals who deploy them. We ask whether agents systematically reflect the b

Kei Noba, José-Luis Pérez

In this paper, we study fluctuation identities for spectrally negative L\'evy processes killed by a general class of additive functionals. We consider positive co-natural additive functionals (PcNAFs), which include as special cases both absolutely continuous functionals and finite mixtures of local times. Our main result shows that the associated fluctuatio

Tanuj Sur, Shashank Tripathi, Nikos Athanasiou, Ha Linh Nguyen

We introduce UniCon3R, a unified feed-forward framework for online human-scene 4D reconstruction from monocular video. Current feed-forward human-scene reconstruction methods suffer from artifacts, where bodies float above the ground or penetrate parts of the scene. A key reason is the lack of effective interaction modelling between the human and the environ

Wangzheng Zhang, Ming-chung Chu, Shihong Liao

Cosmic neutrinos are among the most abundant fermions in the Universe, yet the values of their masses and chemical potentials remain uncertain. In this Letter, we present the first constraints on the total neutrino mass $M_\nu$ and the neutrino asymmetry parameter $\eta^2$ derived from the mean galaxy pairwise peculiar velocity in the quasi-linear and nonlin

Zijie Wang, MohammadHossein Rezaei, Farzana Rashid, Eduardo Blanco

Negation is a common and important semantic feature in natural language, yet Large Language Models (LLMs) struggle when negation is involved in natural language understanding tasks. Commonsense knowledge, on the other hand, despite being a well-studied topic, lacks investigations involving negation. In this work, we show that commonsense knowledge with negat

Damien A. Easson, Tucker Manton

The classical double copy provides a powerful bridge between gravity and gauge theory, but its most explicit realizations remain concentrated in stationary or highly symmetric settings. We show that trapped regions of black-hole geometries furnish an exact setting for time-dependent classical double copy. In the static, spherically symmetric case, each trapp

Jacqueline Blaum Hough, Joshua S. Bloom

Detached eclipsing binaries (DEBs) enable direct inference of stellar and orbital properties across diverse stellar populations. However, inference typically requires computationally intensive forward modeling and radial velocity (RV) measurements, limiting homogeneous analyses to relatively small samples. The growing number of photometrically identified DEB

Donald Liveoak, Tim Hallatt, Sarah Millholland

Recent observational and theoretical work suggests that the sub-Jovian desert (periods ${\lesssim}3$ days, masses ${\sim}10{-}100 \ M_{\oplus}$) hosts the remains of destroyed hot Jupiters (``desert dwellers"). In this work, we explore how differing hot Jupiter destruction mechanisms -- Roche lobe overflow (RLO) vs. tidal disruption during high eccentricity

Sofia Savvidou

Understanding how dust evolves in protoplanetary disks is crucial to constraining the initial conditions of planet formation. The apparent "mass budget problem", which stems from the comparison of the observed disk masses to the ones inferred for exoplanets, remains debated, as it is unclear whether the discrepancy arises from limitations in interpreting dis

Ao Zhang, Wenlei Chen, Manel Errando

The origin of intergalactic magnetic fields (IGMFs) remains one of the key open questions in cosmology. Gamma-ray pair halos produced by electromagnetic cascades from TeV-emitting blazars provide a powerful indirect probe of these fields. In this work, we present a novel search for pair halos that explicitly exploits their expected anisotropic morphology, al

Gijung Lee, Wavid Bowman, Olivia P. Dizon-Paradis, Reiner N. Dizon-Paradis

Federated Learning (FL) is a promising approach for multiparty collaboration as a privacy-preserving technique in hardware assurance, but its security against adversaries with domain-specific knowledge is underexplored. This paper demonstrates a critical vulnerability where available standard cell library layouts (SCLL) can be exploited to compromise the pri

Sophia Abraham, Taiye Chen, Cyril Chhun, Giovanna Jaramillo-Gutierrez

Artificial intelligence systems are now deployed at scale across sectors, accompanied by a growing number of real-world incidents ranging from misinformation and cybercrime to autonomous-system failures. Databases of AI incidents index these events, but they cannot measure ``risk'' (i.e., a joint measure of likelihood and severity) without additional data re

Yuanlei Wang, Xinrui Luo, Binbin Nie, Du Qian

Soliton microcombs provide compact, broadband, coherent light sources for precision metrology, spectroscopy, communications, and microwave photonics. Extending their spectral span while retaining useful output power remains challenging and often requires impractically high pump power. Existing approaches mainly tailor the dispersion and pumping conditions, b

Zhongqi Liang, Jesús Peréz-Ríos

Dipolar fluids are known to exhibit complex self-assembly at low temperatures, yet a compact thermodynamic description of their aggregate statistics has remained elusive. Using molecular dynamics simulations of Stockmayer particles with a purely repulsive WCA core, we confirm that over broad regions of the ($ρ$, $T$) phase space the chain-size distribution f

Luis M. Briceño-Arias, José A. Carrillo, Dante Kalise, Francisco J. Silva

Variational methods based on optimization strategies are proposed to numerically solve a large family of nonlinear partial differential equations. They are all particular instances of gradient flows with general costs, including the $p$-Laplace equation and flux-limited equations such as the relativistic heat equation. This is achieved by computing explicit

Jaswanthi Mandalapu, Andrew Thangaraj

We compare three secrecy-coding schemes for the degraded wiretap binary symmetric channel (BSC) in the finite-blocklength regime: (i) polar wiretap coset codes, (ii) PAC codes used as wiretap coset codes, and (iii) the invertible-extractor (IE) framework of Bellare-Tessaro. Our comparison is empirical and uses a common semantic-secrecy metric (distinguishing

K. L. Wood, W. A. Terrano

We present a new class of control pulses designed to transfer co-located ensembles without relying on frequency selectivity, thereby allowing much faster state-transitions. A geometric approach allows us to construct sequences which are robust to changes in the background magnetic field along multiple axes, and errors in the pulse area. \red{These pulses are

Yun He, Kelin Yu, Matthias Zwicker

Recent agentic frameworks for 3D scene synthesis have advanced realism and diversity by integrating heterogeneous generation and editing tools. These tools are organized into workflows orchestrated by an off-the-shelf LLM. Current approaches typically adopt an execute-review-reflect loop: at each step, the orchestrator executes a tool, renders intermediate r

Karl F. A. Friebel, Jascha A. Ohlmann, Jeronimo Castrillon

Compilers for general-purpose languages have been shown to be at a disadvantage when it comes to specialized application domains as opposed to their Domain-Specific Language (DSL) counterparts. However, the field of DSL compilers features little consolidation in terms of compiler frameworks and adjacent software ecosystems. As a result, considerable work is

Sidong Feng, Dingbang Wang, Nikola Tomic, Tingting Yu

Bug reports play a critical role in software maintenance by helping users convey encountered issues to developers. Recently, GUI screen capture videos have gained popularity as a bug reporting artifact due to their ease of use and ability to retain rich contextual information. However, automatically reproducing bugs from such recordings remains a significant

Parthasarathi Khirwadkar, Robin Rajamäki, Piya Pal

This paper introduces a subspace-coding perspective to millimeter-wave channel sensing with a single RF chain when the complex channel gain is unknown. We show that in this case, candidate directions-of-arrival (DoAs) map naturally to subspaces through their beamspace responses, revealing an intrinsic Grassmannian geometry. This motivates beamspace Grassmann

Sheikh Junaid Fayaz, Nestor D. Montiel-Bohorquez, Wilson Ricardo Leal da Silva, Shashank Bishnoi

Cement production is among the largest contributors to industrial air pollution, emitting ~3 Mt NOx/year. The industry-standard mitigation approach, selective non-catalytic reduction (SNCR), exhibits low NH3 utilization efficiency, resulting in operational inefficiencies and increased reagent costs. Here, we develop a data-driven framework for emission contr

Zijie Li, Yichun Shi, Jingxiang Sun, Ye Wang

We present MMCORE, a unified framework designed for multimodal image generation and editing. MMCORE leverages a pre-trained Vision-Language Model (VLM) to predict semantic visual embeddings via learnable query tokens, which subsequently serve as conditioning signals for a diffusion model. This streamlined design effectively transfers the rich understanding a

Can Lei, Valerio Franchi, Hayat Rajani, Nuno Gracias

Side-scan sonar (SSS) images are susceptible to motion-induced geometric distortion, which degrades their reliability for seabed interpretation and downstream tasks. Existing correction methods either exploit image-domain consistency without adequately preserving global geometric referencing, or rely on navigation-based geocoding whose effectiveness is limit

Carolyn M. V. Pethrick, Siva Nadarajah

We present a high-order space-time discretization equipped with fully-discrete entropy stability properties for general choices of volume and surface quadrature rules. The formulation uses flux reconstruction (FR) in the spatial dimension paired with a discontinuous Galerkin (DG) method in the temporal dimension. The result is a fully-implicit system using p

Gabriel Iturra-Bocaz, Petra Galuscakova

Recently, Retrieval Augmented Generation (RAG) has shifted focus to multi-retrieval approaches to tackle complex tasks such as multi-hop question answering. However, these systems struggle to decide when to stop searching once enough information has been gathered. To address this, \citet{zhou2024metacognitive} introduced Metacognitive Retrieval Augmented Gen

Emmanuel Pedon

For an integer $n\geq 1$, consider the $n$-th metallic number $\phi_n=\frac{n+\sqrt{n^2+4}}{2}$ (e.g. $\phi_1$ is the golden number) and denote by $[\phi_n]_q$ its $q$-deformation in the sense of S. Morier-Genoud and V. Ovsienko. This is an algebraic continued fraction which admits an expansion into a power series $[\phi_n]_q =\sum_{l=0}^{+\infty} \kappa_l(\

P. P. Deka, N. Gupta, J-. K. Krogager, S. A. Balashev

We present results from a search of cold neutral gas associated with radio-loud active galactic nuclei (AGNs) at $z < 0.5$ using HI 21-cm absorption measurements from the MeerKAT Absorption Line Survey (MALS). Cross-matching the MALS 1006 MHz and SDSS DR18 catalogs yields 1908 radio sources at $z < 0.5$. Of these, 613 are classified as AGNs using BPT diagnos

Mohamed Afane, Emily Robitschek, Derek Ouyang, Daniel E. Ho

A well-known limitation of AI systems is presumptuousness: the tendency of AI systems to provide confident answers when information may be lacking. This challenge is particularly acute in legal applications, where a core task for attorneys, judges, and administrators is to determine whether evidence is sufficient to reach a conclusion. We study this problem

Gyanti Prakash Moharana, Diptikanta Swain, Hanuma Kumar Dara, Debendra Prasad Panda

We report structural, magnetic, and Raman studies of the disordered double perovskite GdSrCoMnO$_{6}$~(GSCM). DC magnetization shows a ferromagnetic transition at $T_{C} \approx 153$~K. The inverse susceptibility exhibits a downturn above $T_{C}$ and is consistent with a Griffiths-like regime extending up to $T_{G} \approx 172$~K. Raman measurements show a d

David E. J. van Wijk, Tamas G. Molnar, Samuel Coogan, Manoranjan Majji

Guaranteeing the safety of controllers is vital for real-world applications, but is markedly difficult when the states are not perfectly known and when the control inputs are bounded. Backup control barrier functions (bCBFs) use predictions of the flow under a prescribed controller to achieve safety in the presence of bounded inputs and perfect state informa

Gijung Lee, Wavid Bowman, Olivia P. Dizon-Paradis, Reiner N. Dizon-Paradis

Federated Learning (FL) is an emerging solution to the data scarcity problem for training deep learning models in hardware assurance. While FL is designed to enhance privacy by not sharing raw data, it remains vulnerable to Membership Inference Attacks (MIAs) that can leak sensitive intellectual property (IP). Traditional MIAs are often impractical in this d

Erwin Eko Wahyudi, Yan Solihin, Qian Lou

Fully homomorphic encryption (FHE) enables computation on encrypted data without decryption, making it central to privacy-preserving applications. However, no existing scheme efficiently supports both arithmetic and comparison operations in a unified framework. Prior approaches such as scheme switching and polynomial approximation face serious limitations: s

Hugo Lóio, Jacopo De Nardis, Tony Jin

We develop a recently introduced representation of quantum dynamics based on sampling negative Markov chain processes. By introducing particles and antiparticles, this formalism maps generic quantum dynamics onto a Markov process defined over an exponentially large configuration space. Within this framework, quantum complexity arises from the proliferation o

Pavan Kumar Sharma, Pranamesh Chakraborty

Driver gaze estimation is essential for understanding the driver's situational awareness of surrounding traffic. Existing gaze estimation models use driver facial information to predict the Point-of-Gaze (PoG) or the 3D gaze direction vector. We propose a benchmark dataset, Urban Driving-Face Scene Gaze (UD-FSG), comprising synchronized driver-face and traff

Giorgia Gulino, Manuel Petrucci

Depression is one of the most prevalent and debilitating mental health conditions worldwide, frequently underdiagnosed and undertreated. The proliferation of social media platforms provides a rich source of naturalistic linguistic signals for the automated monitoring of psychological well-being. In this work, we propose a system based on Large Language Model

Anil Maheshwari, Karthik Murali, Michiel Smid

Spanning trees are fundamental for efficient communication in networks. For fault-tolerant communication, it is desirable to have multiple spanning trees to ensure resilience against failures of nodes and edges. To this end, various notions of disjoint or independent spanning trees have been studied, including edge-disjoint, node/edge-independent, and comple

Rotem Ben Zeev, Anirudh Deb, Hee-Cheol Kim, Shlomo S. Razamat

We elaborate on the relation between the generalized Schur index of $N=2$ SCFTs in four dimensions and the non-relativistic limit of the elliptic Ruijsenaars-Schneider model. In particular we discuss explicitly how to express generalized Schur indices of theories of class $S$ in terms of elliptic Jack functions. For example, in the $A_1$ case the indices are

Chenxi Zhou, Pengfei Cao, Jiang Li, Bohan Yu

Post-Training Quantization (PTQ) is critical for the efficient deployment of Large Language Models (LLMs). While 4-bit quantization is widely regarded as an optimal trade-off, reducing the precision to 2-bit usually triggers a catastrophic ``performance cliff.'' It remains unclear whether the underlying mechanisms differ fundamentally. Consequently, we condu

Amarnath, Yogesh Maan

The study of quasi-period microstructures in pulsars offers valuable insights into the underlying emission mechanism. However, identifying these features through manual inspection of the intensity time series, often containing thousands to millions of pulses, is both laborious and time-consuming. To address this challenge, we have developed a Python-based so

Tan Phuong Dong Le, Giang Tran, Hans De Sterck

We present a comprehensive study of radial basis function (RBF) approximations for elliptic and obstacle-type boundary value problems under a variational formulation. Our focus is on practical accuracy, robustness and efficiency. To address ill-conditioning in dense systems, we apply truncated singular value decomposition (TSVD) and investigate its effect on

Vedran Brdar, Samiur R. Mir

Neutrino telescopes have detected astrophysical neutrinos with energies up to ${O}(100)$ PeV. Several current and proposed experiments aim to observe neutrinos at even higher energies, with the goal of detecting cosmogenic neutrinos. This increase in neutrino energy makes tests of Lorentz invariance violation (LIV) particularly appealing, since the effects o

M. Dyndal, L. A. Harland-Lang

In this Letter we explore the modelling of hadron production in electromagnetic ion dissociation (EMD) processes in high-energy ultraperipheral collisions at LHC energies. Since EMD can accompany exclusive particle production in these interactions, we demonstrate that the resulting hadrons can break the exclusivity vetos typically imposed by experiments. As

A. Traficante, M. J. Jimenez-Donaire, R. Indebetouw, T. Wong

The fragmentation properties of parsec-scales clumps play a fundamental role in shaping the dense gas condensations known as cores, the immediate progenitor of stars. The distribution of core masses, the so-called core mass function, is the precursor of the stellar initial mass function, which governs the distribution of stellar masses and, consequently, the

SLAM Labs, :, Oleksiy Ostapenko, Raymond Li

We release Super Apriel, a 15B-parameter supernet in which every decoder layer provides four trained mixer choices -- Full Attention (FA), Sliding Window Attention (SWA), Kimi Delta Attention (KDA), and Gated DeltaNet (GDN). A placement selects one mixer per layer; placements can be switched between requests at serving time without reloading weights, enablin

Shiyong Guo, Brian Swingle

We employ the Multiscale Entanglement Renormalization Ansatz (MERA) tensor network to investigate a critical line of continuous quantum phase transitions of the $\mathbb{Z}_3$ chiral clock model. This critical line is believed to be described by a slow renormalization group flow from the 3-state Potts fixed point to another fixed point that features anisotro

Mustafa Yücel, Karim Achouri

Electromagnetic invisibility, defined as reflectionless transmission with zero phase delay, imposes strict constraints on metasurface designs that go beyond conventional reflection suppression based on the Kerker effect. This condition can be viewed as a metasurface analogue of radiationless states such as anapole excitations. Here, we show that invisibility

Mahaveer Prasad, Ahana Chakraborty, Thomas Iadecola, Manas Kulkarni

In classical dynamical systems, stochastic feedback can stabilize otherwise unstable periodic orbits, giving rise to distinct controlled and uncontrolled phases as the rate of control application is varied. In this work, we apply these control protocols in classical, semiclassical, and quantum regimes to the kicked top, a paradigmatic model of quantum chaos.

Michael L. Graesser, R. Andrew Gustafson

A dark matter sector composed of magnetic monopoles of a dark U(1) symmetry having a small kinetic mixing with the Standard Model photon has a rich and interesting phenomenology. The model in itself is also of theoretical interest. Based on the temperature of the dark sector and scale of spontaneous symmetry breaking for this U(1), three phenomenologically d

Chia-Yu Chang, Fulvio Gesmundo, Jeroen Zuiddam

We determine the border subrank of higher order structure tensors of several families of algebras, and in particular obtain the following results. (1) We determine tight bounds on the border subrank of $k$-fold matrix multiplication and $k$-fold upper triangular matrix multiplication for all $k$. (2) We determine the border subrank of the higher order struct

Rohan S. Kumar, Takahiro Tsunoda, Sophia H. Xue, Dantong Li

Near-term quantum workloads demand error management, yet the two lightest-weight techniques, Quantum Error Detection (QED) and Probabilistic Error Cancellation (PEC), have complementary cost profiles whose joint architectural design space remains unexplored. QED encodes logical qubits and discards error-flagged runs, filtering noise with low qubit overhead b

Aman Kumar, Sogoud Sherif, Veit Elser, Hitesh J. Changlani

It is generally believed that quantum fluctuations collaborate with thermal fluctuations, effectively reducing transition temperatures (e.g. for melting of charge order). We show that this is not always the case and that the interplay between quantum and thermal fluctuations can be competitive. We find excellent motivation for addressing this thanks to the d

Lukas Burgholzer, Marcel Walter, Patrick Hopf, Álvaro Caride-Tabarés Sánchez

Quantum computers are moving into HPC centers, and the main challenge is now integration rather than pure hardware access. Many current software paths still depend on vendor-specific adapter chains between user SDKs, schedulers, and backend APIs. This pattern makes operations more complex than necessary and slows the transition from pilots to production work

Brett Oertel, Ian Moult, Sabrina Pasterski

It has been shown that there are an infinite set of asymptotic symmetries in quantum gravity and QED, and this has been extended to dressed states in some cases. Here we rederive these statements in terms of detectors in order to clarify, confirm, and generalize these results to include external hard gravitons. Using detectors and including the full t depend

J. C. S. Pierce, F. Sweijen, M. J. Hardcastle, L. K. Morabito

Feedback from radio AGN jets is regularly implemented into contemporary models of galaxy evolution to offset radiative cooling in the large-scale environments in which they typically reside. While previous studies suggest that the total kinetic power output from radio AGN is sufficient for this purpose, many have relied on jet-power estimation from radio lum

Carlos Henrique de Lima, David McKeen, Maximilian Swiatlowski

We propose a search at the LHC for GeV-scale particles coupling predominantly to light quarks based on low-multiplicity jets. The search targets production in association with a hard photon and uses the feature that a light gauge-singlet can only decay into a small number of hadronic channels, yielding jets with anomalously low charged-track multiplicity and

Christopher R. Mankovich, Alex B. Akins, Dustin Buccino, Ravit Helled

The shapes of fluid planets bear the signatures of rotational flattening and atmospheric flows. Precise knowledge of their shapes and wind profiles may therefore reveal their interior rotation rates. We re-examine this idea for the ice giants, where missions like the Uranus Orbiter and Probe could use radio occultations to measure atmospheric heights near 1

Minjae Cho, Colin Oscar Nancarrow, Petar Tadić, Yuan Xin

We demonstrate that combining the positivity of density matrices with steady-state conditions yields a systematic bootstrap method for studying open quantum many-body systems governed by Lindblad master equations on infinite lattices, which exhibit absorbing phase transitions. As a concrete example, we apply this method to the quantum contact process with an

César A. Agón, Pablo Bueno, Adem Deniz Piskin, Guido van der Velde

The vacuum mutual information (MI) of subregion algebras provides a universal window into the data of general conformal field theories (CFTs). Exploiting the geometric nature of the modular flow associated to ball-shaped regions and the operator product expansion of twist operators implementing the replica symmetry in an $n$-fold version of a CFT, it is poss

Mengting Chen, Zhengrui Chen, Yongchao Du, Zuan Gao

Recent advances in image generation and editing have opened new opportunities for virtual try-on. However, existing methods still struggle to meet complex real-world demands. We present Tstars-Tryon 1.0, a commercial-scale virtual try-on system that is robust, realistic, versatile, and highly efficient. First, our system maintains a high success rate across

Yutian Chen, Shi Guo, Renbiao Jin, Tianshuo Yang

Sparse-view 3D reconstruction is essential for modeling scenes from casual captures, but remain challenging for non-generative reconstruction. Existing diffusion-based approaches mitigates this issues by synthesizing novel views, but they often condition on only one or two capture frames, which restricts geometric consistency and limits scalability to large

Kene Anumba, David O. Jones, Richard Kessler, Daniel Scolnic

In the coming years, the Vera Rubin Observatory's Legacy Survey of Space and Time (Rubin-LSST) and the Nancy Grace Roman Space Telescope's (Roman) High Latitude Time Domain Survey (HLTDS) are expected to discover more than a million Type Ia supernovae (SNe Ia), several orders of magnitude more than current samples and with a tighter control on systematic unc

B. Hadzhiyska, S. Ferraro, F. J. Qu, B. Ried Guachalla

We present the first high-significance spectroscopic stacked kinetic Sunyaev-Zel'dovich (kSZ) measurements of circumgalactic gas profiles for both Bright Galaxy Survey (BGS) and Emission Line Galaxy (ELG) tracers, combining DESI Data Release 2 with ACT Data Release 6. Using reconstructed line-of-sight velocities from the DESI galaxies and high-resolution ACT

F. J. Qu, B. Ried Guachalla, E. Schaan, B. Hadzhiyska

We present the most precise measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect around luminous red galaxies to date, detecting the signal at $18\sigma$ significance in both harmonic and configuration space. Our analysis cross-correlates 2.4 million spectroscopic LRGs from the Dark Energy Spectroscopic Instrument (DESI) DR2 sample with Data Release 6

Zhiyuan Peng, Wei Tao, Xin Yin, Chenhao Ying

Large language models (LLMs) have achieved strong results in code generation, but their ability to generate GUI applications, especially games, remains insufficiently studied. Existing benchmarks mainly evaluate correctness through test cases, which are inadequate for GUI applications because these systems are interactive, event-driven, and require correct s

Venus Team, Sunhao Dai, Yong Deng, Jinzhen Lin

Edge-scale deep research agents based on small language models are attractive for real-world deployment due to their advantages in cost, latency, and privacy. In this work, we study how to train a strong small deep research agent under limited open-data by improving both data quality and data utilization. We present DR-Venus, a frontier 4B deep research agen

Mario Tuci, Caner Korkmaz, Umut Şimşekli, Tolga Birdal

Training modern neural networks often relies on large learning rates, operating at the edge of stability, where the optimization dynamics exhibit oscillatory and chaotic behavior. Empirically, this regime often yields improved generalization performance, yet the underlying mechanism remains poorly understood. In this work, we represent stochastic optimizers

Chaojie Mao, Chen-Wei Xie, Chongyang Zhong, Haoyou Deng

We present Wan-Image, a unified visual generation system explicitly engineered to paradigm-shift image generation models from casual synthesizers into professional-grade productivity tools. While contemporary diffusion models excel at aesthetic generation, they frequently encounter critical bottlenecks in rigorous design workflows that demand absolute contro

Hugo Aimar, Ivana Gómez, Joaquín Toledo

We introduce a natural bilinear fractional integral type operator induced by a third order hypermetric on Ahlfors regular quasi-metric spaces. Given a quasi-metric space $(X,d)$ the function $\rho(x,y,z)$, defined as the distance, in $X^3$, of $(x,y,z)$ to the diagonal $\bigtriangleup_3=\{(x,x,x)\in X^3:x\in X\}$ is said to be a third order hypermetric in $X

Simmaco Di Lillo, Leonardo Maini, Domenico Marinucci

We establish central and non-central limit theorems for sequences of functionals of the Gaussian output of an infinitely-wide random neural network on the d-dimensional sphere . We show that the asymptotic behaviour of these functionals as the depth of the network increases depends crucially on the fixed points of the covariance function, resulting in three

Austin Coursey, Abel Diaz-Gonzalez, Marcos Quinones-Grueiro, Gautam Biswas

Reinforcement learning (RL) offers a compelling data-driven paradigm for synthesizing controllers for complex systems when accurate physical models are unavailable; however, most existing control-oriented RL methods assume stationarity and, therefore, struggle in real-world non-stationary deployments where system dynamics and operating conditions can change

Zirong Li, Siyuan Mei, Weiwen Wu, Andreas Maier

Conditional medical image generation plays an important role in many clinically relevant imaging tasks. However, existing methods still face a fundamental challenge in balancing inference efficiency, patient-specific fidelity, and distribution-level plausibility, particularly in high-dimensional 3D medical imaging. In this work, we propose GDM, a generative

Sahil Khan, Sayam Sethi, Kaavya Sahay, Yingjia Lin

Recent advancements in neutral atom platforms have enabled exploration of early fault-tolerant (FT) architectures for applications with quantum advantage, such as quantum dynamics simulations. An efficient fault-tolerant architecture has both spatially efficient quantum error correction codes (low qubit overhead), and efficient methodologies (transversal bas

Boyu Chen, Yi Chen, Lu Qiu, Jerry Bai

Scaling humanoid foundation models is bottlenecked by the scarcity of robotic data. While massive egocentric human data offers a scalable alternative, bridging the cross-embodiment chasm remains a fundamental challenge due to kinematic mismatches. We introduce UniT (Unified Latent Action Tokenizer via Visual Anchoring), a framework that establishes a unified

Alexander Ponomarenko

We analyze greedy routing in a random graph G_n constructed on the vertex set V = {1, 2, ..., n} embedded in Z. Vertices are inserted according to a uniform random permutation pi, and each newly inserted vertex connects to its nearest already-inserted neighbors on the left and right (if they exist). This work addresses a conjecture originating from empirical

Luigi De Rosa, Utku Kemal Yuzbasioglu

We consider the dissipative generalized Surface Quasi-Geostrophic equation with dissipation given by any fractional power of the Laplacian. In the inviscid limit, it is proved that anomalous dissipation of the Hamiltonian is prevented by the strong compactness of the solutions in the lowest norm that makes the nonlinearity well-defined. In fact, only the dyn

Prakul Sunil Hiremath, Harshit R. Hiremath

We propose Sensitivity-Uncertainty Alignment (SUA), a framework for analyzing failures of large language models under adversarial and ambiguous inputs. We argue that adversarial sensitivity and ambiguity reflect a common issue: misalignment between prediction instability and model uncertainty. A reliable model should express higher uncertainty when its predi

Perry Dong, Alexander Swerdlow, Dorsa Sadigh, Chelsea Finn

Some of the most performant reinforcement learning algorithms today can be prohibitively expensive as they use test-time scaling methods such as sampling multiple action candidates and selecting the best one. In this work, we propose FASTER, a method for getting the benefits of sampling-based test-time scaling of diffusion-based policies without the computat

Abdulmoneam Ali, Ahmed Arafa

Personalized Federated Learning (PFL) aims to learn multiple task-specific models rather than a single global model across heterogeneous data distributions. Existing PFL approaches typically rely on iterative optimization-such as model update trajectories-to cluster users that need to accomplish the same tasks together. However, these learning-dynamics-based

Jean Mercat, Sedrick Keh, Kushal Arora, Isabella Huang

We present VLA Foundry, an open-source framework that unifies LLM, VLM, and VLA training in a single codebase. Most open-source VLA efforts specialize on the action training stage, often stitching together incompatible pretraining pipelines. VLA Foundry instead provides a shared training stack with end-to-end control, from language pretraining to action-expe

Bo Ning

For a graph $G$, let $f_o(G)$ denote the maximum order of an induced subgraph of $G$ all of whose vertices have odd degree, and let $\chi(G)$ denote the chromatic number of $G$. Scott (CPC, 1992) proved that $f_o(G) \ge |V(G)|/(2\chi(G))$ for every graph without isolated vertices, and conjectured that the factor $2$ can be removed. Wang and Wu (JGT, 2024) sh

Zihan Wang, Huanyuan Shan

Self-interacting dark matter (SIDM) is the leading framework resolving small-scale cold dark matter (CDM) crises, yet high-redshift SIDM constraints are fundamentally limited by degeneracies between dark matter microphysics and galaxy formation astrophysics. We demonstrate that the UV luminosity function alone cannot constrain SIDM: star formation suppressio

Jiaming Zhang, Meng Ding, Shaopeng Fu, Jingfeng Zhang

Despite the remarkable success of Vision Transformers (ViTs) across a wide range of vision tasks, recent studies have revealed that they remain vulnerable to adversarial examples, much like Convolutional Neural Networks (CNNs). A common empirical defense strategy is adversarial training, yet the theoretical underpinnings of its robustness in ViTs remain larg

Jake Lee

The discretization of continuous numerical attributes remains a persistent computational bottleneck in the induction of decision trees, particularly as dataset dimensions scale. Building upon the recently proposed MSD-Splitting technique -- which bins continuous data using the empirical mean and standard deviation to dramatically improve the efficiency and a

Tony Zeng

Juniper Green is a simple combinatorial game invented by Rob Porteous and popularized by Ian Stewart. It was originally designed to familiarize school children with the concepts of multiplication and division. We analyze this elementary game through a completely different lens and show that it recovers the Gallai-Edmonds decomposition of the divisibility gra

Zhengwentai Sun, Keru Zheng, Chenghong Li, Hongjie Liao

Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-view data. Existing methods often address these factors separately, resulting in limited controllability or reduced visual quality. We revisit this problem from an image-first perspective, where high-quality

Henning Fernau, Pamela Fleischmann, Kevin Mann, Silas Cato Sacher

In this work, we introduce a new notion for representing graph classes with formal languages. In contrast to the seminal work by Kitaev and Pyatkin to represent graphs by words, we use formal binary languages in order to have a set of patterns (given by the languages' words) defining the edges in the graph. In particular, we investigate famous languages like

Mark Fornace, Christina Wuyan Wang, Michael Lindsey

Nucleic acid sequence design via codon optimization is a fundamental task with applications across synthetic biology, mRNA therapeutics, and vaccine design. Given a target protein, it is a major open challenge to navigate the combinatorially large design space of codon sequences mapping to its amino acid sequence. Computational approaches generally seek to o

Arianne Meijer-van de Griend

In this paper, we give a mathematical proof that bounds the number of CNOT gates required to synthesize an $n$ qubit phase polynomial with $g$ terms to be at least $O(\frac{gn}{\max (\log g, 1)})$ and at most $O(gn)$. However, when targeting restricted hardware, not all CNOTs are allowed. If we were to use SWAP-based methods to route the qubits on the archit

Feihao Fang, My T. Thai, Yuanyuan Lei

Large Language Models (LLMs) still struggle with multi-step logical reasoning. Existing approaches either purely refine the reasoning chain in natural language form or attach a symbolic solver as an external module. In this work, we instead ask whether LLMs contain a shared internal logical subspace that simultaneously aligns natural-language and symbolic-la

Houchao Gan

Distribution networks with high penetration of Distributed Energy Resources (DERs) increasingly rely on communication networks to coordinate grid-interactive control. While many distributed control schemes have been proposed, they are often evaluated under idealized communication assumptions, making it difficult to assess their performance under realistic ne

Nathan Pagliaroli, Carlos I. Pérez-Sánchez, Brayden Smith

This work proposes a bootstrapping with positivity methodology to study random $U(N)^{D}$ invariant tensors in the large $N$ limit. As has been done for $U(N)$ invariant random matrices, we combine the Dyson-Schwinger equations and positivity constraints of moments to approximate the moments of such tensor models. As examples, we bootstrap the quartic and tw

Renzo Cavalieri, Damiano Fulghesu

We compute a presentation for the integral Chow rings of the moduli stacks of degree $2$ maps from smooth rational curves to projective space $\mathbb{P}^r$, as a quotient of a three-variable polynomial ring. The relations as $r$ varies have rich combinatorial structure: all non-trivial relations are encoded by two generating functions which are rational fun