Tootfinder

BenchECG and xECG: a benchmark and baseline for ECG foundation models
Riccardo Lunelli, Angus Nicolson, Samuel Martin Pr\"oll, Sebastian Johannes Reinstadler, Axel Bauer, Clemens Dlaska
https://arxiv.org/abs/2509.10151

BenchECG and xECG: a benchmark and baseline for ECG foundation models
Electrocardiograms (ECGs) are inexpensive, widely used, and well-suited to deep learning. Recently, interest has grown in developing foundation models for ECGs - models that generalise across diverse downstream tasks. However, consistent evaluation has been lacking: prior work often uses narrow task selections and inconsistent datasets, hindering fair comparison. Here, we introduce BenchECG, a standardised benchmark comprising a comprehensive suite of publicly available ECG datasets and versati…

CaR1: A Multi-Modal Baseline for BEV Vehicle Segmentation via Camera-Radar Fusion
Santiago Montiel-Mar\'in, Angel Llamazares, Miguel Antunes-Garc\'ia, Fabio S\'anchez-Garc\'ia, Luis M. Bergasa
https://arxiv.org/abs/2509.10139

CaR1: A Multi-Modal Baseline for BEV Vehicle Segmentation via Camera-Radar Fusion
Camera-radar fusion offers a robust and cost-effective alternative to LiDAR-based autonomous driving systems by combining complementary sensing capabilities: cameras provide rich semantic cues but unreliable depth, while radar delivers sparse yet reliable position and motion information. We introduce CaR1, a novel camera-radar fusion architecture for BEV vehicle segmentation. Built upon BEVFusion, our approach incorporates a grid-wise radar encoding that discretizes point clouds into structured…

Polarization Denoising and Demosaicking: Dataset and Baseline Method
Muhamad Daniel Ariff Bin Abdul Rahman, Yusuke Monno, Masayuki Tanaka, Masatoshi Okutomi
https://arxiv.org/abs/2509.10098

Polarization Denoising and Demosaicking: Dataset and Baseline Method
A division-of-focal-plane (DoFP) polarimeter enables us to acquire images with multiple polarization orientations in one shot and thus it is valuable for many applications using polarimetric information. The image processing pipeline for a DoFP polarimeter entails two crucial tasks: denoising and demosaicking. While polarization demosaicking for a noise-free case has increasingly been studied, the research for the joint task of polarization denoising and demosaicking is scarce due to the lack o…

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[5/5]:
- BenchECG and xECG: a benchmark and baseline for ECG foundation models
Lunelli, Nicolson, Pr\"oll, Reinstadler, Bauer, Dlaska

@… seems like it’s not *quite* baseline yet (for the flaws baseline has, seems useful to note here)

HalluDetect: Detecting, Mitigating, and Benchmarking Hallucinations in Conversational Systems
Spandan Anaokar, Shrey Ganatra, Harshvivek Kashid, Swapnil Bhattacharyya, Shruti Nair, Reshma Sekhar, Siddharth Manohar, Rahul Hemrajani, Pushpak Bhattacharyya
https://arxiv.org/abs/2509.11619

HalluDetect: Detecting, Mitigating, and Benchmarking Hallucinations in Conversational Systems
Large Language Models (LLMs) are widely used in industry but remain prone to hallucinations, limiting their reliability in critical applications. This work addresses hallucination reduction in consumer grievance chatbots built using LLaMA 3.1 8B Instruct, a compact model frequently used in industry. We develop HalluDetect, an LLM-based hallucination detection system that achieves an F1 score of 69% outperforming baseline detectors by 25.44%. Benchmarking five chatbot architectures, we find that…

Discovering Flow Separation Control Strategies in 3D Wings via Deep Reinforcement Learning
R. Montal\`a, B. Font, P. Su\'arez, J. Rabault, O. Lehmkuhl, R. Vinuesa, I. Rodriguez
https://arxiv.org/abs/2509.10185

Discovering Flow Separation Control Strategies in 3D Wings via Deep Reinforcement Learning
In this work, deep reinforcement learning (DRL) is applied to active flow control (AFC) over a threedimensional SD7003 wing at a Reynolds number of Re = 60,000 and angle of attack of AoA = 14 degrees. In the uncontrolled baseline case, the flow exhibits massive separation and a fully turbulent wake. Using a GPU-accelerated CFD solver and multi-agent training, DRL discovers control strategies that enhance lift (79%), reduce drag (65%), and improve aerodynamic efficiency (408%). Flow visualizatio…

Theory uncertainties of the irreducible background to VBF Higgs production
Xuan Chen, Silvia Ferrario Ravasio, Yacine Haddad, Stefan H\"oche, Joey Huston, Tomas Jezo, Jia-Sheng Liu, Christian T. Preuss, Ahmed Tarek, Jan Winter
https://arxiv.org/abs/2509.10368

Theory uncertainties of the irreducible background to VBF Higgs production
Higgs boson production through gluon fusion in association with two jets is an irreducible background to Higgs boson production through vector boson fusion, one of the most important channels for analyzing and understanding the Higgs boson properties at the Large Hadron Collider. Despite a range of available simulation tools, precise predictions for the corresponding final states are notoriously hard to achieve. Using state-of-the-art fixed-order calculations as the baseline for a comparison, w…

Chandra Large Project Observations of the Supernova Remnant N132D: Measuring the Expansion of the Forward Shock
Xi Long, Paul P. Plucinsky, Terrance J. Gaetz, Vinay L. Kashyap, Aya Bamba, William P. Blair, Daniel Castro, Adam R. Foster, Charles J. Law, Dan Milisavljevic, Eric Miller, Daniel J. Patnaude, Manami Sasaki, Hidetoshi Sano, Piyush Sharda, Benjamin F. Williams, Brian J. Williams, Hiroya Yamaguchi

Chandra Large Project Observations of the Supernova Remnant N132D: Measuring the Expansion of the Forward Shock
We present results from the Chandra X-ray Observatory Large Project (878 ks in 28 observations) of the Large Magellanic Cloud supernova remnant N132D. We measure the expansion of the forward shock in the bright southern rim to be $0.\!^{\prime\prime}10 \pm 0.\!^{\prime\prime}02$ over the $\sim14.5$ yr baseline, which corresponds to a velocity of $1620\pm400~\mathrm{km\,s^{-1}}$ after accounting for several instrumental effects. We measure an expansion of $0.\!^{\prime\prime}23 \pm 0.\!^{\prime\…

Pump-driven droplet electrohydrodynamics: deformation, pinch-off and recoalescence
Yuzhe Qin, Huaxiong Huang, Zilong Song, Shixin Xu
https://arxiv.org/abs/2509.09834 https://

Pump-driven droplet electrohydrodynamics: deformation, pinch-off and recoalescence
We investigate pump-driven droplet electrohydrodynamics with an emphasis on deformation, pinch-off, and recoalescence. A thermodynamically consistent phase-field framework is developed that couples Nernst--Planck--Poisson electrodiffusion with incompressible Navier--Stokes--Cahn--Hilliard flow, and incorporates interfacial ionic pumps as prescribed surface fluxes. In the pump-free baseline, applied fields merely polarise the droplet and deformation is negligible. By contrast, surface-localised …

Active galactic nuclei do not exhibit stably periodic brightness variations
Kareem El-Badry, David W. Hogg, Hans-Walter Rix
https://arxiv.org/abs/2509.10601 https://

Active galactic nuclei do not exhibit stably periodic brightness variations
Periodic variability in active galactic nuclei (AGN) light curves has been proposed as a signature of close supermassive black hole (SMBH) binaries. Recently, 181 candidate SMBH binaries were identified in Gaia DR3 based on periodicity in their $\sim$1000-day light curves. By supplementing Gaia photometry with longer-baseline light curves from the Zwicky Transient Facility (ZTF) and the Catalina Real Time Transient Survey (CRTS), we test whether the reported periodic signals persist beyond the …

Exploring Expert Specialization through Unsupervised Training in Sparse Mixture of Experts
Strahinja Nikolic, Ilker Oguz, Demetri Psaltis
https://arxiv.org/abs/2509.10025 https:…

Exploring Expert Specialization through Unsupervised Training in Sparse Mixture of Experts
Understanding the internal organization of neural networks remains a fundamental challenge in deep learning interpretability. We address this challenge by exploring a novel Sparse Mixture of Experts Variational Autoencoder (SMoE-VAE) architecture. We test our model on the QuickDraw dataset, comparing unsupervised expert routing against a supervised baseline guided by ground-truth labels. Surprisingly, we find that unsupervised routing consistently achieves superior reconstruction performance. T…

Co-Alignment: Rethinking Alignment as Bidirectional Human-AI Cognitive Adaptation
Yubo Li, Weiyi Song
https://arxiv.org/abs/2509.12179 https://arxiv.org/pd…

Co-Alignment: Rethinking Alignment as Bidirectional Human-AI Cognitive Adaptation
Current AI alignment through RLHF follows a single directional paradigm that AI conforms to human preferences while treating human cognition as fixed. We propose a shift to co-alignment through Bidirectional Cognitive Alignment (BiCA), where humans and AI mutually adapt. BiCA uses learnable protocols, representation mapping, and KL-budget constraints for controlled co-evolution. In collaborative navigation, BiCA achieved 85.5% success versus 70.3% baseline, with 230% better mutual adaptation an…

@… the crash course is 4 steps:
1. Limited availability
2. Baseline Newly Available (with the year it’s Newly Available)
3. Wait 30 months
4. Baseline Widely Available

A Baseline $T\log^2 T$ Upper Bound for KL-Regularized Prime--Zero Optimal Transport
Zhejun Yang (University of Sydney)
https://arxiv.org/abs/2509.07329 https://

A Baseline $T\log^2 T$ Upper Bound for KL-Regularized Prime--Zero Optimal Transport
We prove that $\mathsf{OT}_η(T)\ll T\log^2 T$ unconditionally via a band-limited test scheme with Fejér averaging. The approach normalizes $\|\widehat f\|_1=Θ(T^{-1})$ to ensure $\|h\|_1\asymp T$ and $\|\widehat h\|_1\ll 1$, and applies an $L^1$-controlled smoothed explicit formula to bound the error terms. As a result, the prime--zero optimal transport distance admits the baseline $T\log^2 T$ upper bound without additional assumptions.

Establishing a Baseline of Software Supply Chain Security Task Adoption by Software Organizations
Laurie Williams, Sammy Migues
https://arxiv.org/abs/2509.08083 https://

Establishing a Baseline of Software Supply Chain Security Task Adoption by Software Organizations
Software supply chain attacks have increased exponentially since 2020. The primary attack vectors for supply chain attacks are through: (1) software components; (2) the build infrastructure; and (3) humans (a.k.a software practitioners). Software supply chain risk management frameworks provide a list of tasks that an organization can adopt to reduce software supply chain risk. Exhaustively adopting all the tasks of these frameworks is infeasible, necessitating the prioritized adoption of tasks.…

Project Severe Weather Archive of the Philippines (SWAP) Part 2: Baseline Climatology of Close Proximity Soundings in Hailstorm Environments across Luzon, Philippines
Generich H. Capuli
https://arxiv.org/abs/2510.09530

Project Severe Weather Archive of the Philippines (SWAP) Part 2: Baseline Climatology of Close Proximity Soundings in Hailstorm Environments across Luzon, Philippines
The environments of severe thunderstorms that produced hail were examined using 171 proximity soundings (2005-2024) archived in the 3rd Data Release of Project SWAP. These soundings were categorized based on their geographical occurrence into three hail-prone environments across Luzon, Philippines. For each case, key parameters describing instability, vertical wind structure, and moisture were calculated to assess their relationship to hail formation. The probability of hail occurrence, express…

On the Propagation and Damping of Alfvenic Fluctuations in the Outer Solar Corona and Solar Wind
Nikos Sioulas, Marco Velli, Chen Shi, Trevor A. Bowen, Alfred Mallet, Andrea Verdini, B. D. G. Chandran, Anna Tenerani, Jean-Baptiste Dakeyo, Stuart D. Bale, Davin Larson, Jasper S. Halekas, Lorenzo Matteini, Victor R\'eville, C. H. K. Chen, Orlando M. Romeo, Mingzhe Liu, Roberto Livi, Ali Rahmati, P. L. Whittlesey

On the Propagation and Damping of Alfvenic Fluctuations in the Outer Solar Corona and Solar Wind
We analyze \textit{Parker Solar Probe} and \textit{Solar Orbiter} observations to investigate the propagation and dissipation of Alfvénic fluctuations from the outer corona to 1~AU. Conservation of wave-action flux provides the theoretical baseline for how fluctuation amplitudes scale with the Alfvén Mach number $M_a$, once solar-wind acceleration is accounted for. Departures from this scaling quantify the net balance between energy injection and dissipation. Fluctuation amplitudes follow wav…

Dual Band Receiver Design for the Black Hole Explorer (BHEX) Mission
Cheukyu Edward Tong, Keara Carter, Paul Grimes, Eugene Lauria, Dan Marrone, Gabriella Montano, Matthew Morgan, Yoshirnori Uzawa, Lingzhen Zeng
https://arxiv.org/abs/2510.10789

Dual Band Receiver Design for the Black Hole Explorer (BHEX) Mission
A dual band receiver has been designed for the Black Hole Explorer (BHEX) mission, which is a space Very-Long Baseline Interferometry (VLBI) mission concept, aimed at unveiling the photon ring of black holes. The cryogenic receiver comprises a 228-320 GHz Superconductor-Insulator Superconductor (SIS) receiver, paired with a 76-106.7 GHz HEMT receiver. The details of the design are described in this talk. A novel comb generator, which will be used for delay tracking, has been designed and tested.

A Verified High-Performance Composable Object Library for Remote Direct Memory Access (Extended Version)
Guillaume Ambal, George Hodgkins, Mark Madler, Gregory Chockler, Brijesh Dongol, Joseph Izraelevitz, Azalea Raad, Viktor Vafeiadis
https://arxiv.org/abs/2510.10531

A Verified High-Performance Composable Object Library for Remote Direct Memory Access (Extended Version)
Remote Direct Memory Access (RDMA) is a memory technology that allows remote devices to directly write to and read from each other's memory, bypassing components such as the CPU and operating system. This enables low-latency high-throughput networking, as required for many modern data centres, HPC applications and AI/ML workloads. However, baseline RDMA comprises a highly permissive weak memory model that is difficult to use in practice and has only recently been formalised. In this paper, we i…

Entanglement Assisted Non-local Optical Interferometry in a Quantum Network
P. -J. Stas, Y. -C. Wei, M. Sirotin, Y. Q. Huan, U. Yazlar, F. Abdo Arias, E. Knyazev, G. Baranes, B. Machielse, S. Grandi, D. Riedel, J. Borregaard, H. Park, M. Lon\v{c}ar, A. Suleymanzade, M. D. Lukin
https://arxiv.org/abs/2509.09464

Entanglement Assisted Non-local Optical Interferometry in a Quantum Network
The sensitivity of non-local optical measurements at low light intensities, such as those involved in long baseline telescope arrays, can be improved by using remote entanglement. Here, we demonstrate the use of entangled quantum memories in a quantum network of Silicon-vacancy centers in diamond nano-cavities to experimentally perform such non-local phase measurements. Specifically, we combine the generation of event-ready remote quantum entanglement, photon mode erasure that hides the "which-…

Eye Movement Feature-Guided Signal De-Drifting in Electrooculography Systems
Lianming Hu, Xiaotong Zhang, Kamal Youcef-Toumi
https://arxiv.org/abs/2509.07416 https://

Eye Movement Feature-Guided Signal De-Drifting in Electrooculography Systems
Electrooculography (EOG) is widely used for gaze tracking in Human-Robot Collaboration (HRC). However, baseline drift caused by low-frequency noise significantly impacts the accuracy of EOG signals, creating challenges for further sensor fusion. This paper presents an Eye Movement Feature-Guided De-drift (FGD) method for mitigating drift artifacts in EOG signals. The proposed approach leverages active eye-movement feature recognition to reconstruct the feature-extracted EOG baseline and adaptiv…

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Searching for screened scalar forces with long-baseline atom interferometers
Hannah Banks, John Carlton, Benjamin Elder, Thomas Hird, Christopher McCabe

Robust and Efficient Semiparametric Inference for the Stepped Wedge Design
Fan Xia, K. C. Gary Chan, Emily Voldal, Avi Kenny, Patrick J. Heagerty, James P. Hughes
https://arxiv.org/abs/2510.08972

Robust and Efficient Semiparametric Inference for the Stepped Wedge Design
Stepped wedge designs (SWDs) are increasingly used to evaluate longitudinal cluster-level interventions but pose substantial challenges for valid inference. Because crossover times are randomized, intervention effects are intrinsically confounded with secular time trends, while heterogeneity across clusters, complex correlation structures, baseline covariate imbalances, and small numbers of clusters further complicate inference. We propose a unified semiparametric framework for estimating possi…

Energy loss baseline for light hadrons in oxygen-oxygen collisions at $\sqrt{s_\mathrm{NN}}=5.36\,\text{TeV}$
Aleksas Mazeliauskas
https://arxiv.org/abs/2509.07008 https://

Energy loss baseline for light hadrons in oxygen-oxygen collisions at $\sqrt{s_\mathrm{NN}}=5.36\,\text{TeV}$
I present predictions for inclusive charged hadron spectra in minimum-bias proton-proton and oxygen-oxygen collisions at a centre-of-mass energy of $\sqrt{s_\mathrm{NN}} = 5.36\,\text{TeV}$, assuming no final-state interactions. Using next-to-leading order perturbative QCD matrix elements, along with state-of-the-art (nuclear) parton distribution and fragmentation functions, I establish a baseline for the nuclear modification factor $R^h_\text{AA}$ in oxygen-oxygen collisions in the absence of …

GRPO-GCC: Enhancing Cooperation in Spatial Public Goods Games via Group Relative Policy Optimization with Global Cooperation Constraint
Zhaoqilin Yang, Chanchan Li, Tianqi Liu, Hongxin Zhao, Youliang Tian
https://arxiv.org/abs/2510.08607

GRPO-GCC: Enhancing Cooperation in Spatial Public Goods Games via Group Relative Policy Optimization with Global Cooperation Constraint
Inspired by the principle of self-regulating cooperation in collective institutions, we propose the Group Relative Policy Optimization with Global Cooperation Constraint (GRPO-GCC) framework. This work is the first to introduce GRPO into spatial public goods games, establishing a new deep reinforcement learning baseline for structured populations. GRPO-GCC integrates group relative policy optimization with a global cooperation constraint that strengthens incentives at intermediate cooperation l…

Revisiting FRB 20121102A: milliarcsecond localisation and a decreasing dispersion measure
M. P. Snelders, J. W. T. Hessels, J. Huang, N. Sridhar, B. Marcote, A. M. Moroianu, O. S. Ould-Boukattine, F. Kirsten, S. Bhandari, D. M. Hewitt, D. Pelliciari, L. Rhodes, R. Anna-Thomas, U. Bach, E. K. Bempong-Manful, V. Bezrukovs, J. D. Bray, S. Buttaccio, I. Cognard, A. Corongiu, R. Feiler, M. P. Gawro\'nski, M. Giroletti, L. Guillemot, R. Karuppusamy, M. Lindqvist, K. Nimmo, A. Possenti, W…

Revisiting FRB 20121102A: milliarcsecond localisation and a decreasing dispersion measure
FRB 20121102A is the original repeating fast radio burst (FRB) source and also the first to be localised to milliarcsecond precision using very-long-baseline interferometry (VLBI). It has been active for over 13 years and resides in an extreme magneto-ionic environment in a dwarf host galaxy at a distance of ~1 Gpc. In this work, we use the European VLBI Network (EVN) to (re-)localise FRB 20121102A and its associated persistent radio source (PRS). We confirm that the two are co-located -- impro…

@… I think Baseline Widely Available is the one I usually think of as “stable”.

Water Maser Disk and a Supermassive Black Hole at the Nucleus of the Active Galaxy NGC 7738
Rinka Ito, Yusuke Miyamoto, Naomasa Nakai, Aya Yamauchi, Yuichi Terashima
https://arxiv.org/abs/2510.10354

Water Maser Disk and a Supermassive Black Hole at the Nucleus of the Active Galaxy NGC 7738
We present the results of very long baseline interferometry (VLBI) observations of water vapor masers in the nucleus of the LINER galaxy NGC 7738. The red- and blue-shifted and newly detected systemic maser features show an almost edge-on disk located at a distance of ${0.031}\mbox{-}{0.222}$ pc from the galactic center and rotating with a velocity of $324\mbox{-}454$ km s$^{-1}$ . The velocity field of the disk indicates sub-Keplerian rotation, suggesting a non-negligible disk mass. The Mestel…

An Active Fault-Tolerant Online Control Allocation Scheme for a Dual-System UAV in Transition Flight
Junfeng Cai, Marco Lovera
https://arxiv.org/abs/2510.04853 https://

An Active Fault-Tolerant Online Control Allocation Scheme for a Dual-System UAV in Transition Flight
A novel active fault-tolerant control (AFTC) scheme for a dual-system vertical takeoff and landing (VTOL) unmanned aerial vehicle (UAV) during transition flight is proposed in this paper. The AFTC scheme is composed of a baseline control law and an online control reallocation module. First, the structured $H_{\infty}$ baseline control law is able to guarantee the stability of closed-loop systems without being reconfigured under simultaneous actuator fault conditions. Second, compared to the exi…

SBND-PRISM: Sampling Off-Axis Neutrino Fluxes with the Short-Baseline Near Detector
P. Abratenko, R. Acciarri, C. Adams, L. Aliaga-Soplin, O. Alterkait, R. Alvarez-Garrote, D. Andrade Aldana, C. Andreopoulos, A. Antonakis, L. Arellano, J. Asaadi, S. Balasubramanian, A. Barnard, V. Basque, J. Bateman, A. Beever, E. Belchior, M. Betancourt, A. Bhat, M. Bishai, A. Blake, B. Bogart, D. Brailsford, A. Brandt, S. Brickner, M. B. Brunetti, L. Camilleri, D. Caratelli, D. Carber, B. Carlson, M.…

SBND-PRISM: Sampling Off-Axis Neutrino Fluxes with the Short-Baseline Near Detector
The Short-Baseline Near Detector (SBND), the near detector in the Short-Baseline Neutrino Program at Fermi National Accelerator Laboratory, is located just 110 m from the Booster Neutrino Beam target. Thanks to this close proximity, relative to its 4 m $\times$ 4 m front face, neutrinos enter SBND over a range of angles from $0^{\circ}$ to approximately $1.6^{\circ}$, enabling the detector to sample variations in the neutrino flux as a function of angle-a technique known as PRISM, referred to h…

Low Resource Audio Codec Challenge Baseline Systems
Yusuf Ziya Isik, Rafa{\l} {\L}aganowski
https://arxiv.org/abs/2510.00264 https://arxiv.org/pdf/2510.002…

Low Resource Audio Codec Challenge Baseline Systems
The Low-Resource Audio Codec (LRAC) Challenge aims to advance neural audio coding for deployment in resource-constrained environments. The first edition focuses on low-resource neural speech codecs that must operate reliably under everyday noise and reverberation, while satisfying strict constraints on computational complexity, latency, and bitrate. Track 1 targets transparency codecs, which aim to preserve the perceptual transparency of input speech under mild noise and reverberation. Track 2 …

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[5/8]:
- A Human Behavioral Baseline for Collective Governance in Software Projects
Mobina Noori, Mahasweta Chakraborti, Amy X Zhang, Seth Frey

This recent working paper by Robert Metcalfe e.a. for Centre for Net Zero (part of Octopus Group) shows how effective automated EV smart charging is:
"42% reduction in household electricity demand during peak hours, with 100% of this demand shifted to low-cost, low-emission off-peak periods."
Working paper and summary:

High Resolution ALMA Data of the Fomalhaut Debris Disk Confirms Apsidal Width Variation
Jay S. Chittidi (Department of Physics and Astronomy, John Hopkins University, Department of Astrophysical and Planetary Sciences, University of Colorado, Boulder), Meredith A. MacGregor (Department of Physics and Astronomy, John Hopkins University), Joshua Bennett Lovell (Center for Astrophysics, Harvard and Smithsonian), Gaspard Duchene (Astronomy Department, University of California, Berkeley, Un…

High Resolution ALMA Data of the Fomalhaut Debris Disk Confirms Apsidal Width Variation
We present long-baseline observations of the Fomalhaut outer debris disk at 223 GHz (1.3 mm) from ALMA Cycle 5, which we use along with archival short-baseline observations to produce a 0".57 resolution mosaic of the disk at a sensitivity of 7 $μ$Jy/bm. We use radial profiles to measure the disk at the ansae and find that the southeast (SE) side of the disk is 4 AU wider than the northwest (NW) side as observed by ALMA. We also find that the peak brightness of the NW ansa is $21\pm1\%$ brighte…

SegMASt3R: Geometry Grounded Segment Matching
Rohit Jayanti, Swayam Agrawal, Vansh Garg, Siddharth Tourani, Muhammad Haris Khan, Sourav Garg, Madhava Krishna
https://arxiv.org/abs/2510.05051

SegMASt3R: Geometry Grounded Segment Matching
Segment matching is an important intermediate task in computer vision that establishes correspondences between semantically or geometrically coherent regions across images. Unlike keypoint matching, which focuses on localized features, segment matching captures structured regions, offering greater robustness to occlusions, lighting variations, and viewpoint changes. In this paper, we leverage the spatial understanding of 3D foundation models to tackle wide-baseline segment matching, a challengi…

A million-solar-mass object detected at cosmological distance using gravitational imaging
D. M. Powell, J. P. McKean, S. Vegetti, C. Spingola, S. D. M. White, C. D. Fassnacht
https://arxiv.org/abs/2510.07382

A million-solar-mass object detected at cosmological distance using gravitational imaging
Structure on sub-galactic scales provides important tests of galaxy formation models and the nature of dark matter. However, such objects are typically too faint to provide robust mass constraints. Here, we report the discovery of an extremely low-mass object detected via its gravitational perturbation to a thin lensed arc observed with milli-arcsecond-resolution very long baseline interferometry (VLBI). The object was identified using a non-parametric gravitational imaging technique and confir…

Free Elections in the Free State: Ensemble Analysis of Redistricting in New Hampshire
Atticus McWhorter, Daryl DeFord
https://arxiv.org/abs/2509.07328 https://

Free Elections in the Free State: Ensemble Analysis of Redistricting in New Hampshire
The process of legislative redistricting in New Hampshire, along with many other states across the country, was particularly contentious during the 2020 census cycle. In this paper we present an ensemble analysis of the enacted districts to provide mathematical context for claims made about these maps in litigation. Operationalizing the New Hampshire redistricting rules and algorithmically generating a large collection of districting plans allows us to construct a baseline for expected behavior…

»Importing vs fetching JSON:
This year, JSON module imports became baseline 'newly available', meaning they're implemented across browser engines.«
— by @…
Although I don't know for what and in what context to use in the browser, but it's good that I now know about this.
🧑‍💻

Importing vs fetching JSON
They behave differently, so make sure you pick the right one.

Medium Access for Multi-Cell ISAC through Scheduling of Radar and Communication Tasks
Jo\~ao Henrique Inacio de Souza, Fabio Saggese, Kun Chen-Hu, Petar Popovski
https://arxiv.org/abs/2510.05821

Medium Access for Multi-Cell ISAC through Scheduling of Radar and Communication Tasks
This paper focuses on communication, radar search, and tracking task scheduling in multi-cell integrated sensing and communication (ISAC) networks under quality of service (QoS) constraints. We propose a medium access control framework multiplexing the tasks while optimizing radar scan patterns through an interference-aware assignment formulation. Simulations show that our solution guarantees target QoS with improved resource efficiency over baseline schemes, highlighting the benefits of coordi…

CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting
Julia Gastinger, Christian Meilicke, Heiner Stuckenschmidt
https://arxiv.org/abs/2509.09474 https…

CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting
We address the task of temporal knowledge graph (TKG) forecasting by introducing a fully explainable method based on temporal rules. Motivated by recent work proposing a strong baseline using recurrent facts, our approach learns four simple types of rules with a confidence function that considers both recency and frequency. Evaluated on nine datasets, our method matches or surpasses the performance of eight state-of-the-art models and two baselines, while providing fully interpretable predictio…

Lightweight Prompt Engineering for Cognitive Alignment in Educational AI: A OneClickQuiz Case Study
Antoun Yaacoub, Zainab Assaghir, J\'er\^ome Da-Rugna
https://arxiv.org/abs/2510.03374

Lightweight Prompt Engineering for Cognitive Alignment in Educational AI: A OneClickQuiz Case Study
The rapid integration of Artificial Intelligence (AI) into educational technology promises to revolutionize content creation and assessment. However, the quality and pedagogical alignment of AI-generated content remain critical challenges. This paper investigates the impact of lightweight prompt engineering strategies on the cognitive alignment of AI-generated questions within OneClickQuiz, a Moodle plugin leveraging generative AI. We evaluate three prompt variants-a detailed baseline, a simple…

"By 2100, unchecked climate change could slash global GDP per capita by up to 24%"
#Climate #ClimateChange
https://

By 2100, unchecked climate change could slash global GDP per capita by up to 24%
Nearly a quarter of the global GDP per capita could be lost by 2100 compared to a "no further warming" baseline, if climate change continues to escalate unchecked, according to a study published in PLOS Climate by Kamiar Mohaddes and Mehdi Raissi from the University of Cambridge climaTRACES Lab.

Demonstrating Improved Contrast on the Roman Coronagraph with Spatial Linear Dark Field Control
Thayne Currie, Olivier Guyon, Ruslan Belikov, Dan Sirbu, Mona El Morsy
https://arxiv.org/abs/2509.08905

Demonstrating Improved Contrast on the Roman Coronagraph with Spatial Linear Dark Field Control
The baseline contrast floor from the Roman Coronagraph's High-Order Wavefront Sensing and Control strategy likely degrades over the course of time, requiring periodic recalibration of the dark hole. Here, we propose to consider spatial linear dark field control (sLDFC) on a one-sided deep-contrast region of the focal plane as a potential test. Implementing sLDFC on CGI will likely require some unique data acquisition strategies given the EMCCD's high flux sensitivity in long exposures/high gain…

Crosslisted article(s) found for math.CA. https://arxiv.org/list/math.CA/new
[1/1]:
- A Baseline $T\log^2 T$ Upper Bound for KL-Regularized Prime--Zero Optimal Transport
Zhejun Yang (University of Sydney)

Crosslisted article(s) found for nucl-ex. https://arxiv.org/list/nucl-ex/new
[1/1]:
- Energy loss baseline for light hadrons in oxygen-oxygen collisions at $\sqrt{s_\mathrm{NN}}=5.36\...
Aleksas Mazeliauskas

Difference in Neoclassical Edge Flows Between Strongly Negative and Positive Triangularities in the XGC Gyrokinetic Simulation
S. Ku, C. S. Chang, R. Hager, L. W. Schmitz, A. O. Nelson
https://arxiv.org/abs/2510.05287

Difference in Neoclassical Edge Flows Between Strongly Negative and Positive Triangularities in the XGC Gyrokinetic Simulation
The neoclassical baseline study of a strongly negative triangularity (NT) plasma and the corresponding positive triangularity plasma is performed using the edge-specialized, total-f gyrokinetic code XGC. A DIII-D-like plasma is used, based on the negative triangularity discharge of DIII-D \#193793. An artificial positive triangularity (PT) equilibrium has been constructed to compare the edge rotation physics at the same triangularity strength, but with opposite sign, while keeping the same elon…

Gold-Switch: Training-Free Superposition of Slow- and Fast- Thinking LLMs
Jaeseong Lee, Dayoung Kwon, seung-won hwang
https://arxiv.org/abs/2510.06750 https://

Gold-Switch: Training-Free Superposition of Slow- and Fast- Thinking LLMs
Large Reasoning Models (LRMs) excel in structured tasks by emulating deliberate human reasoning but often suffer from overthinking, degrading performance and wasting resources. One possible baseline is to deploy both LLM and LRM, then route input by predicting whether it requires reasoning and may cause overthinking. However, deploying multiple models can be costly or impractical. We propose a superposed deployment strategy with a lightweight, training-free regulation to optimize inference by s…

AIRwaves at CheckThat! 2025: Retrieving Scientific Sources for Implicit Claims on Social Media with Dual Encoders and Neural Re-Ranking
Cem Ashbaugh, Leon Baumg\"artner, Tim Gress, Nikita Sidorov, Daniel Werner
https://arxiv.org/abs/2509.19509

AIRwaves at CheckThat! 2025: Retrieving Scientific Sources for Implicit Claims on Social Media with Dual Encoders and Neural Re-Ranking
Linking implicit scientific claims made on social media to their original publications is crucial for evidence-based fact-checking and scholarly discourse, yet it is hindered by lexical sparsity, very short queries, and domain-specific language. Team AIRwaves ranked second in Subtask 4b of the CLEF-2025 CheckThat! Lab with an evidence-retrieval approach that markedly outperforms the competition baseline. The optimized sparse-retrieval baseline(BM25) achieves MRR@5 = 0.5025 on the gold label bli…

Accretion-Regulated Type Transitions in Changing-Look AGNs: Evidence from Two-Epoch Spectral Analysis
Yu-Heng Shen, Kai-Xing Lu, Wei-Jian Guo, Sha-Sha Li, Hai-Cheng Feng, Zhang Yue, Wen-Zhe Xi, Jian-Guo Wang, Jin-Ming Bai
https://arxiv.org/abs/2510.08868

Accretion-Regulated Type Transitions in Changing-Look AGNs: Evidence from Two-Epoch Spectral Analysis
The changing-look active galactic nucleus (CL-AGN), an extraordinary subpopulation of supermassive black holes, has attracted growing attention for understanding its nature. We present an analysis of the spectral properties of 203 low-redshift CL-AGNs ($z<0.35$) using two-epoch spectra from SDSS DR16 and DESI DR1 with time baseline ranging from $\sim$1000 to 8000 days, based on spectral fitting and decomposition. The sample consists of 11.3\% Type 1.0, 26.6\% Type 1.2, 43.1\% Type 1.5, and 19\%…

Feasibility-Guided Fair Adaptive Offline Reinforcement Learning for Medicaid Care Management
Sanjay Basu, Sadiq Y. Patel, Parth Sheth, Bhairavi Muralidharan, Namrata Elamaran, Aakriti Kinra, Rajaie Batniji
https://arxiv.org/abs/2509.09655

Feasibility-Guided Fair Adaptive Offline Reinforcement Learning for Medicaid Care Management
We introduce Feasibility-Guided Fair Adaptive Reinforcement Learning (FG-FARL), an offline RL procedure that calibrates per-group safety thresholds to reduce harm while equalizing a chosen fairness target (coverage or harm) across protected subgroups. Using de-identified longitudinal trajectories from a Medicaid population health management program, we evaluate FG-FARL against behavior cloning (BC) and HACO (Hybrid Adaptive Conformal Offline RL; a global conformal safety baseline). We report of…

A new open letter urging the EU to stick to hard climate targets was signed by nearly 2200 international scientists: https://zenodo.org/records/17399532
Please spread the word widely and send towards your representatives for the upcoming decision.

Hybrid Quantum-Classical Policy Gradient for Adaptive Control of Cyber-Physical Systems: A Comparative Study of VQC vs. MLP
Aueaphum Aueawatthanaphisut, Nyi Wunna Tun
https://arxiv.org/abs/2510.06010

Hybrid Quantum-Classical Policy Gradient for Adaptive Control of Cyber-Physical Systems: A Comparative Study of VQC vs. MLP
The comparative evaluation between classical and quantum reinforcement learning (QRL) paradigms was conducted to investigate their convergence behavior, robustness under observational noise, and computational efficiency in a benchmark control environment. The study employed a multilayer perceptron (MLP) agent as a classical baseline and a parameterized variational quantum circuit (VQC) as a quantum counterpart, both trained on the CartPole-v1 environment over 500 episodes. Empirical results dem…

#Science #ClimateChange Open letter by Scientists: #Climate Neutrality is Europe's Greatest Economic Opportunity

Crosslisted article(s) found for nucl-th. https://arxiv.org/list/nucl-th/new
[1/1]:
- Energy loss baseline for light hadrons in oxygen-oxygen collisions at $\sqrt{s_\mathrm{NN}}=5.36\...
Aleksas Mazeliauskas

Frequency Standard Contributions to Limitations on the Signal-to-Noise Ratio in Very Long Baseline Interferometric (VLBI) Observations
Eric Burt, Todd Ely, Geoff Bower, Joe Lazio, Marin Anderson, Sonia Hernandez
https://arxiv.org/abs/2508.19123

Frequency Standard Contributions to Limitations on the Signal-to-Noise Ratio in Very Long Baseline Interferometric (VLBI) Observations
Since its observation in 2019, the first image of a super-massive black hole using Very Long Baseline Interferometry (VLBI) with an Earth-scale baseline has generated much scientific and public interest, including the possible extension of the baseline into space to obtain higher image resolution. Operating one or more VLBI nodes in space will require the use of frequency standards that are space qualified, greatly reducing the number of options available. The coherence function C(T) is the met…

Impact of Labeling Inaccuracy and Image Noise on Tooth Segmentation in Panoramic Radiographs using Federated, Centralized and Local Learning
Johan Andreas Balle Rubak, Khuram Naveed, Sanyam Jain, Lukas Esterle, Alexandros Iosifidis, Ruben Pauwels
https://arxiv.org/abs/2509.06553

Impact of Labeling Inaccuracy and Image Noise on Tooth Segmentation in Panoramic Radiographs using Federated, Centralized and Local Learning
Objectives: Federated learning (FL) may mitigate privacy constraints, heterogeneous data quality, and inconsistent labeling in dental diagnostic AI. We compared FL with centralized (CL) and local learning (LL) for tooth segmentation in panoramic radiographs across multiple data corruption scenarios. Methods: An Attention U-Net was trained on 2066 radiographs from six institutions across four settings: baseline (unaltered data); label manipulation (dilated/missing annotations); image-quality man…

ReeMark: Reeb Graphs for Simulating Patterns of Life in Spatiotemporal Trajectories
Anantajit Subrahmanya, Chandrakanth Gudavalli, Connor Levenson, Umang Garg, B. S. Manjunath
https://arxiv.org/abs/2510.03152

ReeMark: Reeb Graphs for Simulating Patterns of Life in Spatiotemporal Trajectories
Accurately modeling human mobility is critical for urban planning, epidemiology, and traffic management. In this work, we introduce Markovian Reeb Graphs, a novel framework for simulating spatiotemporal trajectories that preserve Patterns of Life (PoLs) learned from baseline data. By combining individual- and population-level mobility structures within a probabilistic topological model, our approach generates realistic future trajectories that capture both consistency and variability in daily l…

A Nonparametric Discrete Hawkes Model with a Collapsed Gaussian-Process Prior
Trinnhallen Brisley, Gordon Ross, Daniel Paulin
https://arxiv.org/abs/2509.21996 https://

A Nonparametric Discrete Hawkes Model with a Collapsed Gaussian-Process Prior
Hawkes process models are used in settings where past events increase the likelihood of future events occurring. Many applications record events as counts on a regular grid, yet discrete-time Hawkes models remain comparatively underused and are often constrained by fixed-form baselines and excitation kernels. In particular, there is a lack of flexible, nonparametric treatments of both the baseline and the excitation in discrete time. To this end, we propose the Gaussian Process Discrete Hawkes …

PWFA linear collider improvements -- from previous concepts to HALHF
Erik Adli, Carl A. Lindstr{\o}m
https://arxiv.org/abs/2509.07910 https://arxiv.org/pdf…

PWFA linear collider improvements -- from previous concepts to HALHF
This note summarizes the major design changes from the plasma wakefield linear collider concept presented at Snowmass 2013 to the most recent HALHF 2.0 baseline.

Effective Field Theory in Long-Baseline Neutrino Oscillation Experiments
Joachim Kopp, Zahra Tabrizi, Salvador Urrea
https://arxiv.org/abs/2509.21537 https://

Effective Field Theory in Long-Baseline Neutrino Oscillation Experiments
We study the phenomenology of physics beyond the Standard Model in long-baseline neutrino oscillation experiments using the most general parametrisation of heavy new physics in the framework of Standard Model Effective Theory (SMEFT), as well as its counterpart below the electroweak scale, Weak Effective Field Theory (WEFT). We compute neutrino production, oscillation, and detection rates in these frameworks, consistently accounting for renormalisation group running as well as SMEFT/WEFT matchi…

A Statistical Method for Attack-Agnostic Adversarial Attack Detection with Compressive Sensing Comparison
Chinthana Wimalasuriya, Spyros Tragoudas
https://arxiv.org/abs/2510.02707

A Statistical Method for Attack-Agnostic Adversarial Attack Detection with Compressive Sensing Comparison
Adversarial attacks present a significant threat to modern machine learning systems. Yet, existing detection methods often lack the ability to detect unseen attacks or detect different attack types with a high level of accuracy. In this work, we propose a statistical approach that establishes a detection baseline before a neural network's deployment, enabling effective real-time adversarial detection. We generate a metric of adversarial presence by comparing the behavior of a compressed/uncompr…

Team Xiaomi EV-AD VLA: Caption-Guided Retrieval System for Cross-Modal Drone Navigation - Technical Report for IROS 2025 RoboSense Challenge Track 4
Lingfeng Zhang, Erjia Xiao, Yuchen Zhang, Haoxiang Fu, Ruibin Hu, Yanbiao Ma, Wenbo Ding, Long Chen, Hangjun Ye, Xiaoshuai Hao
https://arxiv.org/abs/2510.02728…

Team Xiaomi EV-AD VLA: Caption-Guided Retrieval System for Cross-Modal Drone Navigation - Technical Report for IROS 2025 RoboSense Challenge Track 4
Cross-modal drone navigation remains a challenging task in robotics, requiring efficient retrieval of relevant images from large-scale databases based on natural language descriptions. The RoboSense 2025 Track 4 challenge addresses this challenge, focusing on robust, natural language-guided cross-view image retrieval across multiple platforms (drones, satellites, and ground cameras). Current baseline methods, while effective for initial retrieval, often struggle to achieve fine-grained semantic…

Towards Unified Multimodal Misinformation Detection in Social Media: A Benchmark Dataset and Baseline
Haiyang Li, Yaxiong Wang, Lianwei Wu, Lechao Cheng, Zhun Zhong
https://arxiv.org/abs/2509.25991

Towards Unified Multimodal Misinformation Detection in Social Media: A Benchmark Dataset and Baseline
In recent years, detecting fake multimodal content on social media has drawn increasing attention. Two major forms of deception dominate: human-crafted misinformation (e.g., rumors and misleading posts) and AI-generated content produced by image synthesis models or vision-language models (VLMs). Although both share deceptive intent, they are typically studied in isolation. NLP research focuses on human-written misinformation, while the CV community targets AI-generated artifacts. As a result, e…

BaseReward: A Strong Baseline for Multimodal Reward Model
Yi-Fan Zhang, Haihua Yang, Huanyu Zhang, Yang Shi, Zezhou Chen, Haochen Tian, Chaoyou Fu, Haotian Wang, Kai Wu, Bo Cui, Xu Wang, Jianfei Pan, Haotian Wang, Zhang Zhang, Liang Wang
https://arxiv.org/abs/2509.16127

BaseReward: A Strong Baseline for Multimodal Reward Model
The rapid advancement of Multimodal Large Language Models (MLLMs) has made aligning them with human preferences a critical challenge. Reward Models (RMs) are a core technology for achieving this goal, but a systematic guide for building state-of-the-art Multimodal Reward Models (MRMs) is currently lacking in both academia and industry. Through exhaustive experimental analysis, this paper aims to provide a clear ``recipe'' for constructing high-performance MRMs. We systematically investigate eve…

Transformer Classification of Breast Lesions: The BreastDCEDL_AMBL Benchmark Dataset and 0.92 AUC Baseline
Naomi Fridman (Ariel University), Anat Goldstein (Ariel University)
https://arxiv.org/abs/2509.26440

Transformer Classification of Breast Lesions: The BreastDCEDL_AMBL Benchmark Dataset and 0.92 AUC Baseline
The error is caused by special characters that arXiv's system doesn't recognize. Here's the cleaned version with all problematic characters replaced: Breast magnetic resonance imaging is a critical tool for cancer detection and treatment planning, but its clinical utility is hindered by poor specificity, leading to high false-positive rates and unnecessary biopsies. This study introduces a transformer-based framework for automated classification of breast lesions in dynamic contrast-enhanced MR…

DIPSY: A new Disc Instability Population SYnthesis, II. The Populations of Companions Formed Through Disc Instability
O. Schib, C. Mordasini, A. Emsenhuber, R. Helled
https://arxiv.org/abs/2510.02437

DIPSY: A new Disc Instability Population SYnthesis, II. The Populations of Companions Formed Through Disc Instability
We applied the global end-to-end model described in Paper~I of this series to perform a population synthesis of companions formed via disc instability (DI). By using initial conditions compatible with both observations and hydrodynamical simulations, and by studying a large range of primary masses (0.05-5 Msol), we can provide quantitative predictions of the outcome of DI. In the baseline population, we find that ~10 % of the discs fragment, and about half of these end up with a surviving com…

Demonstration of a next-generation wavefront actuator for gravitational-wave detection
Tyler Rosauer, Huy Tuong Cao, Mohak Bhattacharya, Peter Carney, Luke Johnson, Shane Levin, Cynthia Liang, Xuesi Ma, Luis Martin Gutierrez, Michael Padilla, Liu Tao, Aiden Wilkin, Aidan Brooks, Jonathan W. Richardson
https://arxiv.org/abs/2509.08766

Demonstration of a next-generation wavefront actuator for gravitational-wave detection
In the last decade, the Laser Interferometer Gravitational-Wave Observatory (LIGO) and the European Virgo observatory have opened a new observational window on the universe. These cavity-enhanced laser interferometers sense spacetime strain, generated by distant astrophysical events such as black hole mergers, to an RMS fluctuation of a few parts in $10^{21}$ over a multi-kilometer baseline. Optical advancements in laser wavefront control are key to advancing the sensitivity of current detector…

Replaced article(s) found for hep-ph. https://arxiv.org/list/hep-ph/new
[1/2]:
- Probing the Higgs Portal at the Fermilab Short-Baseline Neutrino Experiments
Brian Batell, Joshua Berger, Ahmed Ismail

Enhancing Credit Risk Prediction: A Meta-Learning Framework Integrating Baseline Models, LASSO, and ECOC for Superior Accuracy
Haibo Wang, Lutfu S. Sua, Jun Huang, Figen Balo, Burak Dolar
https://arxiv.org/abs/2509.22381

Enhancing Credit Risk Prediction: A Meta-Learning Framework Integrating Baseline Models, LASSO, and ECOC for Superior Accuracy
Effective credit risk management is fundamental to financial decision-making, necessitating robust models for default probability prediction and financial entity classification. Traditional machine learning approaches face significant challenges when confronted with high-dimensional data, limited interpretability, rare event detection, and multi-class imbalance problems in risk assessment. This research proposes a comprehensive meta-learning framework that synthesizes multiple complementary mod…

An adaptive design for optimizing treatment assignment in randomized clinical trials
Wei Zhang, Zhiwei Zhang, Aiyi Liu
https://arxiv.org/abs/2509.00429 https://

An adaptive design for optimizing treatment assignment in randomized clinical trials
The treatment assignment mechanism in a randomized clinical trial can be optimized for statistical efficiency within a specified class of randomization mechanisms. Optimal designs of this type have been characterized in terms of the variances of potential outcomes conditional on baseline covariates. Approximating these optimal designs requires information about the conditional variance functions, which is often unavailable or unreliable at the design stage. As a practical solution to this dilem…

A Robust Neural Control Design for Multi-drone Slung Payload Manipulation with Control Contraction Metrics
Xinyuan Liang, Longhao Qian, Yi Lok Lo, Hugh H. T. Liu
https://arxiv.org/abs/2510.01489

A Robust Neural Control Design for Multi-drone Slung Payload Manipulation with Control Contraction Metrics
This paper presents a robust neural control design for a three-drone slung payload transportation system to track a reference path under external disturbances. The control contraction metric (CCM) is used to generate a neural exponentially converging baseline controller while complying with control input saturation constraints. We also incorporate the uncertainty and disturbance estimator (UDE) technique to dynamically compensate for persistent disturbances. The proposed framework yields a modu…

An extended and extremely thin gravitational arc from a lensed compact symmetric object at redshift 2.059
J. P. McKean, C. Spingola, D. M. Powell, S. Vegetti
https://arxiv.org/abs/2510.07386

An extended and extremely thin gravitational arc from a lensed compact symmetric object at redshift 2.059
Compact symmetric objects (CSOs) are thought to be short-lived radio sources with two lobes of emission that are separated by less than a kpc in projection. However, studies of such systems at high redshift is challenging due to the limited resolution of present-day telescopes, and can be biased to the most luminous objects. Here we report imaging of a gravitationally lensed CSO at a redshift of 2.059 using very long baseline interferometry at 1.7 GHz. The data are imaged using Bayesian forward…

FASTColor -- Full-color Amplitude Surrogate Toolkit for QCD
Javier Mari\~no Villadamigo, Rikkert Frederix, Tilman Plehn, Timea Vitos, Ramon Winterhalder
https://arxiv.org/abs/2509.07068

FASTColor -- Full-color Amplitude Surrogate Toolkit for QCD
High-multiplicity events remain a bottleneck for LHC simulations due to their computational cost. We present a ML-surrogate approach to accelerate matrix element reweighting from leading-color (LC) to full-color (FC) accuracy, building on recent advancements in LC event generation. Comparing a variety of modern network architectures for representative QCD processes, we achieve speed-up of around a factor two over the current LC-to-FC baseline. We also show how transformers learn and exploit und…

DMS:Diffusion-Based Multi-Baseline Stereo Generation for Improving Self-Supervised Depth Estimation
Zihua Liu, Yizhou Li, Songyan Zhang, Masatoshi Okutomi
https://arxiv.org/abs/2508.13091

DMS:Diffusion-Based Multi-Baseline Stereo Generation for Improving Self-Supervised Depth Estimation
While supervised stereo matching and monocular depth estimation have advanced significantly with learning-based algorithms, self-supervised methods using stereo images as supervision signals have received relatively less focus and require further investigation. A primary challenge arises from ambiguity introduced during photometric reconstruction, particularly due to missing corresponding pixels in ill-posed regions of the target view, such as occlusions and out-of-frame areas. To address this …

Adaptive Learning Strategies for Mitotic Figure Classification in MIDOG2025 Challenge
Biwen Meng, Xi Long, Jingxin Liu
https://arxiv.org/abs/2509.02640 https://

Adaptive Learning Strategies for Mitotic Figure Classification in MIDOG2025 Challenge
Atypical mitotic figures (AMFs) are clinically relevant indicators of abnormal cell division, yet their reliable detection remains challenging due to morphological ambiguity and scanner variability. In this work, we investigated three variants of adapting the pathology foundation model UNI2-h for the MIDOG2025 Track 2 challenge. Starting from a LoRA-based baseline, we found that visual prompt tuning (VPT) substantially improved generalization, and that further integrating test-time augmentation…

Quantile Advantage Estimation for Entropy-Safe Reasoning
Junkang Wu, Kexin Huang, Jiancan Wu, An Zhang, Xiang Wang, Xiangnan He
https://arxiv.org/abs/2509.22611 https://

Quantile Advantage Estimation for Entropy-Safe Reasoning
Reinforcement Learning with Verifiable Rewards (RLVR) strengthens LLM reasoning, but training often oscillates between {entropy collapse} and {entropy explosion}. We trace both hazards to the mean baseline used in value-free RL (e.g., GRPO and DAPO), which improperly penalizes negative-advantage samples under reward outliers. We propose {Quantile Advantage Estimation} (QAE), replacing the mean with a group-wise K-quantile baseline. QAE induces a response-level, two-regime gate: on hard queries …

Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct
Haoyang Zheng, Xinyang Liu, Cindy Xiangrui Kong, Nan Jiang, Zheyuan Hu, Weijian Luo, Wei Deng, Guang Lin
https://arxiv.org/abs/2509.25035

Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct
Fast generation of language texts is the holy grail that people pursue in the AI era. In this work, we introduced Discrete Diffusion Divergence Instruct (DiDi-Instruct), a training-based method that leads to fast language generation models by initializing from a pre-trained (masked) discrete diffusion language model (dLLM). The resulting DiDi-Instruct model outperforms the dLLM counterparts and the GPT-2 baseline with 64x acceleration. In the theoretical part of the paper, we build the foundati…

Quantum-Enhanced Natural Language Generation: A Multi-Model Framework with Hybrid Quantum-Classical Architectures
Chi-Sheng Chen, En-Jui Kuo
https://arxiv.org/abs/2508.21332 htt…

Quantum-Enhanced Natural Language Generation: A Multi-Model Framework with Hybrid Quantum-Classical Architectures
This paper presents a comprehensive evaluation of quantum text generation models against traditional Transformer/MLP architectures, addressing the growing interest in quantum computing applications for natural language processing. We conduct systematic experiments comparing five distinct models: Transformer (baseline), Quantum Kernel Self-Attention Network (QKSAN), Quantum RWKV (QRWKV), and Quantum Attention Sequence Architecture (QASA) across five diverse datasets including simple sentences, s…

Multi-band Spectral and Astrometric Characterization of the HIP 99770 b Planet with SCExAO/CHARIS and Gaia
Danielle Bovie, Thayne Currie, Mona El Morsy, Brianna Lacy, Masayuki Kuzuhara, Jeffrey Chilcote, Taylor Tobin, Olivier Guyon, Tyler Groff, Julien Lozi, Sebastien Vievard, Vincent Deo, Frantz Martinache, Yiting Li, Motohide Tamura
https://

Multi-band Spectral and Astrometric Characterization of the HIP 99770 b Planet with SCExAO/CHARIS and Gaia
We present and analyze follow-up, higher resolution ($R$ $\sim$ 70) $H$ and $K$ band integral field spectroscopy of the superjovian exoplanet HIP 99770 b with SCExAO/CHARIS. Our new data recover the companion at a high signal-to-noise ratio in both bandpasses and more than double the astrometric baseline for its orbital motion. Jointly modeling HIP 99770 b's position and the star's astrometry from \textit{Hipparcos} and \textit{Gaia} yields orbital parameters consistent with those from the disc…

Heavy Field Effects on Inflationary Models in Light of ACT Data
Shuntaro Aoki, Hajime Otsuka, Ryota Yanagita
https://arxiv.org/abs/2509.06739 https://arxiv…

Heavy Field Effects on Inflationary Models in Light of ACT Data
Recent results from the Atacama Cosmology Telescope (ACT), when combined with Planck and DESI datasets, indicate a scalar spectral index $n_s$ larger than that reported in the Planck 2018 baseline, thereby challenging conventional Starobinsky-type ($α$-attractor) inflationary scenarios at the $2σ$ level. In addition, the positive running of the spectral index $α_s$ implied by the data provides strong constraints on these models. In this paper, we explore the possibility that the presence of …

Baseline-Aware Dependence fitting for DAmping Timescales (BADDAT): A Nearly Unbiased Approach to Constraining Optical Variability Dependence on Physical Properties of Active Galactic Nuclei
Ruisong Xia, Zhen-Yi Cai, Yongquan Xue, Xian-Liang Lu, Guowei Ren, Shuying Zhou, Mouyuan Sun, Shifu Zhu, Zhen-Bo Su, Hao Liu
https://arxiv.org/abs/2509…

Baseline-Aware Dependence fitting for DAmping Timescales (BADDAT): A Nearly Unbiased Approach to Constraining Optical Variability Dependence on Physical Properties of Active Galactic Nuclei
Active galactic nuclei (AGNs) exhibit stochastic optical variability, commonly characterized by a damped random walk. The damping timescale is of particular interest because it is related to fundamental properties of the central black hole, such as its mass and accretion rate. However, the systematic underestimation of damping timescales caused by limited observational baselines makes it difficult to exhaustively utilize all available data. Many previous efforts have relied on strict selection …

Advancing Real-World Parking Slot Detection with Large-Scale Dataset and Semi-Supervised Baseline
Zhihao Zhang, Chunyu Lin, Lang Nie, Jiyuan Wang, Yao Zhao
https://arxiv.org/abs/2509.13133

Advancing Real-World Parking Slot Detection with Large-Scale Dataset and Semi-Supervised Baseline
As automatic parking systems evolve, the accurate detection of parking slots has become increasingly critical. This study focuses on parking slot detection using surround-view cameras, which offer a comprehensive bird's-eye view of the parking environment. However, the current datasets are limited in scale, and the scenes they contain are seldom disrupted by real-world noise (e.g., light, occlusion, etc.). Moreover, manual data annotation is prone to errors and omissions due to the complexity o…

Autoregressive End-to-End Planning with Time-Invariant Spatial Alignment and Multi-Objective Policy Refinement
Jianbo Zhao, Taiyu Ban, Xiangjie Li, Xingtai Gui, Hangning Zhou, Lei Liu, Hongwei Zhao, Bin Li
https://arxiv.org/abs/2509.20938

Autoregressive End-to-End Planning with Time-Invariant Spatial Alignment and Multi-Objective Policy Refinement
The inherent sequential modeling capabilities of autoregressive models make them a formidable baseline for end-to-end planning in autonomous driving. Nevertheless, their performance is constrained by a spatio-temporal misalignment, as the planner must condition future actions on past sensory data. This creates an inconsistent worldview, limiting the upper bound of performance for an otherwise powerful approach. To address this, we propose a Time-Invariant Spatial Alignment (TISA) module that le…

Promptable Longitudinal Lesion Segmentation in Whole-Body CT
Yannick Kirchhoff, Maximilian Rokuss, Fabian Isensee, Klaus H. Maier-Hein
https://arxiv.org/abs/2509.00613 https://

Promptable Longitudinal Lesion Segmentation in Whole-Body CT
Accurate segmentation of lesions in longitudinal whole-body CT is essential for monitoring disease progression and treatment response. While automated methods benefit from incorporating longitudinal information, they remain limited in their ability to consistently track individual lesions across time. Task 2 of the autoPET/CT IV Challenge addresses this by providing lesion localizations and baseline delineations, framing the problem as longitudinal promptable segmentation. In this work, we exte…

ALMA-IMF XX: Core fragmentation in the W51 high-mass star-forming region
T. Yoo, A. Ginsburg, J. Braine, N. Budaiev, F. Louvet, F. Motte, A. M. Stutz, B. Thomasson, M. Armante, M. Bonfand, S. Bontemps, L. Bronfman, G. Busquet, T. Csengeri, N. Cunningham, J. Di Francesco, D. J. D\'iaz-Gonz\'alez, M. Fern\'andez-Lopez, R. Galv\'an-Madrid, C. Goddi, A. Gusdorf, N. Kessler, A. Koley, H. -L Liu, T. Nony, F. Olguin, P. Sanhueza, M. Valeille-Manet, L. A. Zapata, Q. Zhang
…

ALMA-IMF XX: Core fragmentation in the W51 high-mass star-forming region
We present a study of core fragmentation in the W51-E and W51-IRS2 protoclusters in the W51 high-mass star-forming region. The identification of core fragmentation is achieved by the spatial correspondence of cores and compact sources which are detected in the short (low resolution) and the long baseline (high resolution) continuum images with the Atacama Large Millimeter/submillimeter Array (ALMA) in Bands 3 (3 mm) and 6 (1.3 mm), respectively. We characterize the compact sources found in the …

ICL Optimized Fragility
Serena Gomez Wannaz
https://arxiv.org/abs/2510.00300 https://arxiv.org/pdf/2510.00300

ICL Optimized Fragility
ICL guides are known to improve task-specific performance, but their impact on cross-domain cognitive abilities remains unexplored. This study examines how ICL guides affect reasoning across different knowledge domains using six variants of the GPT-OSS:20b model: one baseline model and five ICL configurations (simple, chain-of-thought, random, appended text, and symbolic language). The models were subjected to 840 tests spanning general knowledge questions, logic riddles, and a mathematical oly…

nCTEQ global analysis of nuclear PDFs
M. Klasen
https://arxiv.org/abs/2510.05880 https://arxiv.org/pdf/2510.05880…

nCTEQ global analysis of nuclear PDFs
We review the series of specific nCTEQ analyses of nuclear parton distribution functions (PDFs) published since 2020 and present preliminary results of a new global analysis. Building on a modern proton baseline without nuclear data and extending the kinematic range, it combines and updates the previous separate analyses that focused on Jefferson Lab neutral-current deep-inelastic scattering (DIS), neutrino DIS and dimuon production, and the currently available CERN LHC data, in particular on W…

Implementing the PRIDE technique for the JUICE mission at the University of Tasmania
Oliver James White, Guifr\'e Molera Calv\'es, Jasper Edwards
https://arxiv.org/abs/2509.02888

Implementing the PRIDE technique for the JUICE mission at the University of Tasmania
The Jupiter Icy Moons Explorer (JUICE) spacecraft is a European Space Agency (ESA) mission to study the Jovian system, currently undergoing an eight-year cruise phase. The Planetary Radio Interferometric and Doppler Experiment (PRIDE) is one of eleven experiments contributing to the JUICE mission. PRIDE aims to conduct radio science experiments using ground-based radio telescopes, through both single dish and Very Long Baseline Interferometry (VLBI) observations. The University of Tasmania (UTA…

HST Proper Motions of Andromeda V and VI
Dana I. Casetti-Dinescu, Marcel S. Pawlowski, Terrence M. Girard, Kosuke J. Kanehisa, Max Martone, Alexander Petroski
https://arxiv.org/abs/2509.06215

HST Proper Motions of Andromeda V and VI
We measure the absolute proper motions of Andromeda V (And V) and Andromeda VI/Pegasus (And VI) dwarf galaxies, satellites of M31 located near its galactic plane. And VI is located the farthest from M31 among the six satellites with currently measured proper motions. A combination of ACS/WFC and WFPC2 exposures are utilized, spanning a 20-year time baseline. The WFPC2 exposures are processed using a recently developed deep-learning centering procedure as well as the most up-to-date astrometri…

DiFFPO: Training Diffusion LLMs to Reason Fast and Furious via Reinforcement Learning
Hanyang Zhao, Dawen Liang, Wenpin Tang, David Yao, Nathan Kallus
https://arxiv.org/abs/2510.02212

DiFFPO: Training Diffusion LLMs to Reason Fast and Furious via Reinforcement Learning
We propose DiFFPO, Diffusion Fast and Furious Policy Optimization, a unified framework for training masked diffusion large language models (dLLMs) to reason not only better (furious), but also faster via reinforcement learning (RL). We first unify the existing baseline approach such as d1 by proposing to train surrogate policies via off-policy RL, whose likelihood is much more tractable as an approximation to the true dLLM policy. This naturally motivates a more accurate and informative two-sta…

Anatomy-DT: A Cross-Diffusion Digital Twin for Anatomical Evolution
Moinak Bhattacharya, Gagandeep Singh, Prateek Prasanna
https://arxiv.org/abs/2509.25280 https://

Anatomy-DT: A Cross-Diffusion Digital Twin for Anatomical Evolution
Accurately modeling the spatiotemporal evolution of tumor morphology from baseline imaging is a pre-requisite for developing digital twin frameworks that can simulate disease progression and treatment response. Most existing approaches primarily characterize tumor growth while neglecting the concomitant alterations in adjacent anatomical structures. In reality, tumor evolution is highly non-linear and heterogeneous, shaped not only by therapeutic interventions but also by its spatial context an…

Automated Modeling with AAP-Imfit: Astrometry and Photometry via CASA
Alfredo Amador-Portes, Eva Palafox, V\'ictor M. Pati\~no-\'Alvarez, Vahram Chavushyan, Andrei P. Lobanov, Sergio A. Dzib
https://arxiv.org/abs/2510.00119

Automated Modeling with AAP-Imfit: Astrometry and Photometry via CASA
Very Long Baseline Interferometry (VLBI) provides the highest-resolution radio intensity maps, crucial for detailed studies of compact sources like active galactic nuclei (AGN) and their relativistic jets. Analyzing jet components in these maps traditionally involves manual Gaussian fitting, a time-consuming bottleneck for large datasets. To address this, we present an automated batch-processing tool, based on the Gaussian fitting capabilities of CASA, designed to streamline VLBI jet component …

Probing Beyond the Standard Model Scenarios in Long-baseline and Astrophysical Neutrino Experiments
Sudipta Das
https://arxiv.org/abs/2509.20348 https://ar…

Probing Beyond the Standard Model Scenarios in Long-baseline and Astrophysical Neutrino Experiments
Over the past few decades, outstanding progress in the neutrino experiment frontier has greatly advanced our understanding of the flavor oscillations of active neutrinos. The remaining key questions such as the neutrino mass ordering, the presence of CP violation in the lepton sector, and the octant of $θ_{23}$ are expected to be resolved in the coming years. The current precise knowledge of neutrino mass and mixing parameters, together with the promising prospects of next-generation neutrino …

Enhancing compact convolutional transformers with super attention
Simpenzwe Honore Leandre, Natenaile Asmamaw Shiferaw, Dillip Rout
https://arxiv.org/abs/2508.18960 https://

Enhancing compact convolutional transformers with super attention
In this paper, we propose a vision model that adopts token mixing, sequence-pooling, and convolutional tokenizers to achieve state-of-the-art performance and efficient inference in fixed context-length tasks. In the CIFAR100 benchmark, our model significantly improves the baseline of the top 1% and top 5% validation accuracy from 36.50% to 46.29% and 66.33% to 76.31%, while being more efficient than the Scaled Dot Product Attention (SDPA) transformers when the context length is less than the em…

ArgoLOOM: agentic AI for fundamental physics from quarks to cosmos
S. D. Bakshi, P. Barry, C. Bissolotti, I. Cloet, S. Corrodi, Z. Djurcic, S. Habib, K. Heitmann, T. J. Hobbs, W. Hopkins, S. Joosten, B. Kriesten, N. Ramachandra, A. Wells, M. Zurek
https://arxiv.org/abs/2510.02426

ArgoLOOM: agentic AI for fundamental physics from quarks to cosmos
Progress in modern physics has been supported by a steadily expanding corpus of numerical analyses and computational frameworks, which in turn form the basis for precision calculations and baseline predictions in experimental programs. These tools play a central role in navigating a complex landscape of theoretical models and current and potential observables to identify and understand fundamental interactions in physics. In addition, efforts to search for new fundamental interactions increasin…

Style4D-Bench: A Benchmark Suite for 4D Stylization
Beiqi Chen, Shuai Shao, Haitang Feng, Jianhuang Lai, Jianlou Si, Guangcong Wang
https://arxiv.org/abs/2508.19243 https://

Style4D-Bench: A Benchmark Suite for 4D Stylization
We introduce Style4D-Bench, the first benchmark suite specifically designed for 4D stylization, with the goal of standardizing evaluation and facilitating progress in this emerging area. Style4D-Bench comprises: 1) a comprehensive evaluation protocol measuring spatial fidelity, temporal coherence, and multi-view consistency through both perceptual and quantitative metrics, 2) a strong baseline that make an initial attempt for 4D stylization, and 3) a curated collection of high-resolution dynami…

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization
Zhibo Xu, Jianhao Zhu, Jingwen Xu, Changze Lv, Zisu Huang, Xiaohua Wang, Muling Wu, Qi Qian, Xiaoqing Zheng, Xuanjing Huang
https://arxiv.org/abs/2508.18911

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization
Experimental results across various models and tasks demonstrate that our approach not only maintains strong model performance in federated learning settings but also achieves enhanced protection of model parameters compared to baseline methods.

A Compact Symmetric Object Discovered by the VLA Low-band Ionosphere and Transient Experiment
Kristina Nyland, Mary Rachelle Barrett, Genna Crom, Pallavi Patil, Emil Polisensky, Wendy Peters, Simona Giacintucci, Tracy Clarke, Mark Lacy, Shyaam Mukundan, Dillon Z. Dong, Andy Goulding, Amy E Kimball, Magdalena Kunert-Bajraszewska
https://arx…

A Compact Symmetric Object Discovered by the VLA Low-band Ionosphere and Transient Experiment
We present new Very Long Baseline Array (VLBA) imaging of a MHz-peaked spectrum (MPS) source that was found using commensal low-frequency data taken with the Karl G. Jansky Very Large Array (VLA). The source, J0330-2730, was identified in multi-epoch data from the VLA Low-band Ionosphere and Transient Experiment (VLITE). VLITE continuously collects low-frequency data at 340 MHz during regular VLA observations. Our analysis of the VLITE light curve demonstrates that J0330-2730 has significant 34…

VLA FRAMEx. III. Circumnuclear Radio Emission Mechanisms in Hard X-ray Selected Active Galactic Nuclei
Andrew J. Sargent, Alexander J. van der Horst, Megan C. Johnson, Travis C. Fischer, Nathan J. Secrest, Onic I. Shuvo, Macon A. Magno, Luis C. Fernandez
https://arxiv.org/abs/2509.03466

VLA FRAMEx. III. Circumnuclear Radio Emission Mechanisms in Hard X-ray Selected Active Galactic Nuclei
We present Stokes I continuum analysis for a volume-limited sample ($<40~\rm{Mpc}$) of hard X-ray selected active galactic nuclei (AGNs) using $4-12$ GHz observations with the Karl G. Jansky Very Large Array (VLA). All of the 25 sources analyzed here have previously been observed with the Very Long Baseline Array (VLBA) to probe their subparsec projected physical scales, but detected emission has only been measured for 12 of the sources at $C$ band (4.4 GHz), despite expectations. We determined…