Tootfinder

Spectral Thresholds for Identifiability and Stability:Finite-Sample Phase Transitions in High-Dimensional Learning
William Hao-Cheng Huang
https://arxiv.org/abs/2510.03809 https…

Spectral Thresholds for Identifiability and Stability:Finite-Sample Phase Transitions in High-Dimensional Learning
In high-dimensional learning, models remain stable until they collapse abruptly once the sample size falls below a critical level. This instability is not algorithm-specific but a geometric mechanism: when the weakest Fisher eigendirection falls beneath sample-level fluctuations, identifiability fails. Our Fisher Threshold Theorem formalizes this by proving that stability requires the minimal Fisher eigenvalue to exceed an explicit $O(\sqrt{d/n})$ bound. Unlike prior asymptotic or model-specifi…

Correcting sample selection bias with categorical outcomes
Onil Boussim
https://arxiv.org/abs/2510.05551 https://arxiv.org/pdf/2510.05551

Correcting sample selection bias with categorical outcomes
In this paper, we propose a method for correcting sample selection bias when the outcome of interest is categorical, such as occupational choice, health status, or field of study. Classical approaches to sample selection rely on strong parametric distributional assumptions, which may be restrictive in practice. While the recent framework of Chernozhukov et al. (2023) offers a nonparametric identification using a local Gaussian representation (LGR) that holds for any bivariate joint distribution…

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs
Xueyan Li, Guinan Su, Mrinmaya Sachan, Jonas Geiping
https://arxiv.org/abs/2510.05987 https://

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs
Large Language Models (LLMs) are increasingly applied to complex tasks that require extended reasoning. In such settings, models often benefit from diverse chains-of-thought to arrive at multiple candidate solutions. This requires two competing objectives: to inject enough stochasticity to explore multiple reasoning chains, and to ensure sufficient accuracy and quality in each path. Existing works pursue the first objective by increasing exploration at highly uncertain steps with higher tempera…

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
Abid Hussain, Touqeer Ahmad
https://arxiv.org/abs/2510.05353 https://

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
A fundamental challenge in comparing two survival distributions with right censored data is the selection of an appropriate nonparametric test, as the power of standard tests like the Log rank and Wilcoxon is highly dependent on the often unknown nature of the alternative hypothesis. This paper introduces a new, distribution free two sample test designed to overcome this limitation. The proposed method is based on a strategic decomposition of the data into uncensored and censored subsets, from …

Gaseous disks in white dwarfs: properties of the current sample
L. Saker, M. Gomez, L. Garcia
https://arxiv.org/abs/2509.05180 https://arxiv.org/pdf/2509.0…

Gaseous disks in white dwarfs: properties of the current sample
In recent years, the number of white dwarfs (WDs) showing infrared (IR) excesses, attributed to circumstellar dust disks, has grown significantly. Gaseous disks have also been detected in some WDs with dust. We obtained optical spectra with Gemini/GMOS for thirteen WDs exhibiting IR excesses to search for gaseous components. No Ca II emission was detected, suggesting the gas phase may be short-lived compared to the dusty stage. Combining our data with literature, we compiled the largest sample …

Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models
Raha Askari, Sina Zarrie{\ss}, \"Ozge Alacam, Judith Sieker
https://arxiv.org/abs/2510.04764

Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models
Implicit meanings are integral to human communication, making it essential for language models to be capable of identifying and interpreting them. Grice (1975) proposed a set of conversational maxims that guide cooperative dialogue, noting that speakers may deliberately violate these principles to express meanings beyond literal words, and that listeners, in turn, recognize such violations to draw pragmatic inferences. Building on Surian et al. (1996)'s study of children's sensitivity to viol…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

Sample complexity for entropic optimal transport with radial cost
Ruiyu Han. Johannes Wiesel
https://arxiv.org/abs/2510.05685 https://arxiv.org/pdf/2510.05…

Sample complexity for entropic optimal transport with radial cost
We prove a new sample complexity result for entropy regularized optimal transport. Our bound holds for probability measures on $\mathbb R^d$ with exponential tail decay and for radial cost functions that satisfy a local Lipschitz condition. It is sharp up to logarithmic factors, and captures the intrinsic dimension of the marginal distributions through a generalized covering number of their supports. Examples that fit into our framework include subexponential and subgaussian distributions and r…

DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation
Tien Pham, Xinyun Chi, Khang Nguyen, Manfred Huber, Angelo Cangelosi
https://arxiv.org/abs/2509.04970

DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation
Reinforcement learning (RL) agents can learn to solve complex tasks from visual inputs, but generalizing these learned skills to new environments remains a major challenge in RL application, especially robotics. While data augmentation can improve generalization, it often compromises sample efficiency and training stability. This paper introduces DeGuV, an RL framework that enhances both generalization and sample efficiency. In specific, we leverage a learnable masker network that produces a ma…

Sample-Efficient and Smooth Cross-Entropy Method Model Predictive Control Using Deterministic Samples
Markus Walker, Daniel Frisch, Uwe D. Hanebeck
https://arxiv.org/abs/2510.05706

Sample-Efficient and Smooth Cross-Entropy Method Model Predictive Control Using Deterministic Samples
Cross-entropy method model predictive control (CEM--MPC) is a powerful gradient-free technique for nonlinear optimal control, but its performance is often limited by the reliance on random sampling. This conventional approach can lead to inefficient exploration of the solution space and non-smooth control inputs, requiring a large number of samples to achieve satisfactory results. To address these limitations, we propose deterministic sampling CEM (dsCEM), a novel framework that replaces the ra…

Optimal Zeroth-Order Bilevel Optimization
Alireza Aghasi, Jeongyeol Kwon, Saeed Ghadimi
https://arxiv.org/abs/2510.03646 https://arxiv.org/pdf/2510.03646…

Optimal Zeroth-Order Bilevel Optimization
In this paper, we develop zeroth-order algorithms with provably (nearly) optimal sample complexity for stochastic bilevel optimization, where only noisy function evaluations are available. We propose two distinct algorithms: the first is inspired by Jacobian/Hessian-based approaches, and the second builds on using a penalty function reformulation. The Jacobian/Hessian-based method achieves a sample complexity of $\mathcal{O}(d^3/ε^2)$, which is optimal in terms of accuracy $ε$, albeit with po…

The Gamma-ray Luminosity Function of Flat-Spectrum Radio Quasars
Garima Rajguru, Lea Marcotulli, Marco Ajello, Mattia Di Mauro, Meg Urry
https://arxiv.org/abs/2510.05515 https:/…

The Gamma-ray Luminosity Function of Flat-Spectrum Radio Quasars
We have utilized the largest sample of $γ$-ray selected Fermi flat-spectrum radio quasars (FSRQs) ever used (519 sources) to construct the luminosity function and its evolution through the cosmic history. In addition to spanning large redshift ($0

The award for the pull request of the day goes to OpenSSH:
https://github.com/openssh/openssh-portable/pull/554

Make 3rd party unit tests log "PERKELE" instead of "FUCKOFF" by martinpaljak · Pull Request #554 · openssh/openssh-portable
I'm using this sample file as input to known_hosts parsing unit tests. I don't mind a bit of swearing but this Finnish word is a bit less direct than "FUCKOFF". Reference: https:/...

A Comparison of Star Formation Rates by Different Tracers in Nearby Galaxies
Huynh Anh N. Le, Jong-Hak Woo, Yongquan Xue, Ashraf Ayubinia, Changseok Kim, Xiaozhi Lin
https://arxiv.org/abs/2510.05687

A Comparison of Star Formation Rates by Different Tracers in Nearby Galaxies
We utilize a large sample of $\sim$113,000 galaxies ($z < 0.3$) from the Sloan Digital Sky Survey with high-quality data to compare star formation rates (SFRs) across multiple diagnostic methods and examine their connection to Active Galactic Nuclei (AGNs) strength, indicated by Eddington ratio. Our sample encompassed star-forming (SF), composite, Seyfert, and LINER galaxies. Our analysis utilizes various SFRs indicators, including observed infrared flux ($\rm SFR_{FIR}$) from AKARI/Herschel ($…

Opening Line for NFL Week 2: Rams, Eagles to cover; Panthers, Cardinals to flounder; Dolphins to what!? https://www.nytimes.com/athletic/6610803/2025/09/08/nfl-week-2-betting-picks-opening-line/

Crosslisted article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[1/1]:
- Sample-efficient Integration of New Modalities into Large Language Models
Osman Batur \.Ince, Andr\'e F. T. Martins, Oisin Mac Aodha, Edoardo M. Ponti

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[8/13]:
- Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access
Mudit Gaur, Prashant Trivedi, Sasidhar Kunapuli, Amrit Singh Bedi, Vaneet Aggarwal

Quantum Subgradient Estimation for Conditional Value-at-Risk Optimization
Vasilis Skarlatos, Nikos Konofaos
https://arxiv.org/abs/2510.04736 https://arxiv.…

Quantum Subgradient Estimation for Conditional Value-at-Risk Optimization
Conditional Value-at-Risk (CVaR) is a leading tail-risk measure in finance, central to both regulatory and portfolio optimization frameworks. Classical estimation of CVaR and its gradients relies on Monte Carlo simulation, incurring $O(1/ε^2)$ sample complexity to achieve $ε$-accuracy. In this work, we design and analyze a quantum subgradient oracle for CVaR minimization based on amplitude estimation. Via a tripartite proposition, we show that CVaR subgradients can be estimated with $O(1/ε)$…

Thank you #rhel

After sssd upgrade, useradd and usermod fail to flush the sssd cache with "DB version too old for domain implicit_files!". - Red Hat Customer Portal
After sssd upgrade, useradd and usermod fail to flush the sssd cache with "DB version too old for domain implicit_files!". Sample reproducer: # useradd testuser0 # systemctl is-enabled sssd.service # systemctl disable sssd.service # systemctl stop sssd.service # yum update sssd Sample outputs of a sssd upgrade system from sssd-2.3.0-9.el8(RHEL8.3) to sssd-2.5.2-2.el8(RHEL8.5): # useradd testuser1 [sss_cache] [sysdb_domain_cache_connect] (0x0010): DB version too old [0.22], expected [0.23] for d…

Characterizing the variability of a sample of massive stars in eclipsing binaries
C. I. Eze (Nicolaus Copernicus Astronomical Center, Warsaw, Poland, Department of Physics and Astronomy, University of Nigeria, Nsukka, Nigeria), G. Handler (Nicolaus Copernicus Astronomical Center, Warsaw, Poland), F. Kahraman Ali\c{c}avu\c{s} (\c{C}anakkale Onsekiz Mart University, Faculty of Sciences, Physics Department, \c{C}anakkale, T\"urkiye), T. Pawar (Nicolaus Copernicus Astronomical Center,…

Characterizing the variability of a sample of massive stars in eclipsing binaries
Massive stars exhibit a perplexing mismatch between their inferred masses from different observational techniques, posing a significant challenge to our understanding of stellar evolution and structure. This discrepancy is believed to be caused by the underestimation of the convective core masses. The efficiency of such measurement is usually impaired by a lot of processes at work in the interior of the stars such as convective core overshooting and interior rotation. By integrating the precisi…

Optimality and computational barriers in variable selection under dependence
Ming Gao, Bryon Aragam
https://arxiv.org/abs/2510.03990 https://arxiv.org/pdf/…

Optimality and computational barriers in variable selection under dependence
We study the optimal sample complexity of variable selection in linear regression under general design covariance, and show that subset selection is optimal while under standard complexity assumptions, efficient algorithms for this problem do not exist. Specifically, we analyze the variable selection problem and provide the optimal sample complexity with exact dependence on the problem parameters for both known and unknown sparsity settings. Moreover, we establish a sample complexity lower boun…

Strong progenitor age bias in supernova #cosmology – I. Robust and ubiquitous evidence from a larger sample of host galaxies in a broader redshift range / II. Alignment with DESI BAO and signs of a non-accelerating universe: https://academic.oup.com/mnras/article/538/4/3340/8098234 / https://academic.oup.com/mnras/article/544/1/975/8281988 -> Universe's expansion 'is now slowing, not speeding up': https://ras.ac.uk/news-and-press/research-highlights/universes-expansion-now-slowing-not-speeding (this has been claimed by the group since at least 2023 - http://vietnam.in2p3.fr/2023/windows/transparencies/02_tuesday/Astro_5/01_Son.pdf - and is rejected by the SN cosmology community as https://bsky.app/profile/astromarc.bsky.social/post/3m4xmikwfds26 explains).

Adapting HFMCA to Graph Data: Self-Supervised Learning for Generalizable fMRI Representations
Jakub Frac, Alexander Schmatz, Qiang Li, Guido Van Wingen, Shujian Yu
https://arxiv.org/abs/2510.05177

Adapting HFMCA to Graph Data: Self-Supervised Learning for Generalizable fMRI Representations
Functional magnetic resonance imaging (fMRI) analysis faces significant challenges due to limited dataset sizes and domain variability between studies. Traditional self-supervised learning methods inspired by computer vision often rely on positive and negative sample pairs, which can be problematic for neuroimaging data where defining appropriate contrasts is non-trivial. We propose adapting a recently developed Hierarchical Functional Maximal Correlation Algorithm (HFMCA) to graph-structured f…

Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
Roy Siegelmann, Enrique Mallada
https://arxiv.org/abs/2510.03982

Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
We propose a method for data-driven practical stabilization of nonlinear systems with provable guarantees, based on the concept of Nonparametric Chain Policies (NCPs). The approach employs a normalized nearest-neighbor rule to assign, at each state, a finite-duration control signal derived from stored data, after which the process repeats. Unlike recent works that model the system as linear, polynomial, or polynomial fraction, we only assume the system to be locally Lipschitz. Our analysis buil…

Updated Radio Sigma-D Relation and Distances to the Shell-Like Galactic Supernova Remnants -- IV
D. Uro\v{s}evi\'c, B. Vukoti\'c, M. An{\dj}eli\'c, N. Mladenovi\'c
https://arxiv.org/abs/2510.03410

Updated Radio Sigma-D Relation and Distances to the Shell-Like Galactic Supernova Remnants -- IV
We present a new selected sample of 69 Galactic supernova remnants (SNRs) for calibration of radio $Σ-D$ relation at 1 GHz. Calibrators with the most reliable distances were selected through an extensive literature search. The calibration is performed using kernel smoothing of the selected sample of calibrators in $Σ-D$ plane and an orthogonal offsets fitting procedure. We use the obtained calibration to derive the distances to 164 Galactic SNRs and 27 new detected SNRs/SNR candidates with no…

Dynamics of Liquidity Surfaces in Uniswap v3
Jimmy Risk, Shen-Ning Tung, Tai-Ho Wang
https://arxiv.org/abs/2509.05013 https://arxiv.org/pdf/2509.05013

Dynamics of Liquidity Surfaces in Uniswap v3
This paper presents a comprehensive study on the empirical dynamics of Uniswap v3 liquidity, which we model as a time-tick surface, $L_t(x)$. Using a combination of functional principal component analysis (FPCA) and dynamic factor methods, we analyze three distinct pools over multiple sample periods. Our findings offer three main contributions: a statistical characterization of automated market maker liquidity, an interpretable and portable basis for dimension reduction, and a robust analysis o…

First Measurement of the $D_s^ \rightarrow K^0\mu^ \nu_{\mu}$ Decay
BESIII Collaboration, et al.
https://arxiv.org/abs/2510.05904 https://arxiv.org/pdf/251…

First Measurement of the $D_s^+\rightarrow K^0μ^+ν_μ$ Decay
We report the first measurement of the semileptonic decay $D^+_s \rightarrow K^0μ^+ν_μ$, using a sample of $e^+e^-$ annihilation data corresponding to an integrated luminosity of $7.33~\mathrm{fb}^{-1}$ collected at center-of-mass energies between 4.128 to 4.226~GeV with the BESIII detector at the BEPCII collider. The branching fraction of the decay is measured to be $\mathcal{B}(D^+_s\rightarrow K^0μ^+ν_μ) = (2.89 \pm 0.27_{\rm stat} \pm 0.12_{\rm syst})\times 10^{-3}$, where the first u…

The First Dedicated Survey of Atmospheric Escape from Planets Orbiting F Stars
Morgan Saidel, Shreyas Vissapragada, Heather Knutson, Ethan Schreyer, Mike Greklek-McKeon, Jonathan Gomez Barrientos, W. Garrett Levine, Carlos Gasc\'on, Morgan MacLeod, Haedam Im, Nick Tusay
https://arxiv.org/abs/2510.05240

The First Dedicated Survey of Atmospheric Escape from Planets Orbiting F Stars
Hydrodynamic escape can strip the envelopes of close-in exoplanets, but most observations of atmospheric mass loss to date have been confined to planets orbiting K and M dwarfs. A growing body of detections of atmospheric escape from planets orbiting early-type stars indicates that they may have significantly stronger and more extended outflows than planets orbiting cooler stars. However, it is unclear whether this limited sample of planets is representative of all gas giants orbiting early-typ…

Quantum Lattice Boltzmann Method for Multiple Time Steps Without Reinitialization for Linear Advection-Diffusion Problems
Aaron Nagel, Johannes L\"owe
https://arxiv.org/abs/2510.05965

Quantum Lattice Boltzmann Method for Multiple Time Steps Without Reinitialization for Linear Advection-Diffusion Problems
To simulate highly-resolved flow fields, we extend the Quantum Lattice Boltzmann Method (QLBM) to be able to simulate multiple time steps without state extraction or reinitialization. We adjust and extend given QLBM approaches from the literature to completely remove the need to measure or reinitialize the flow field in between the simulation time steps. Therefore, our algorithm does not require to sample the entire flow field at any time. We solve the linear advection-diffusion problem and der…

H I Properties of Field Galaxies at $\boldsymbol{z\approx 0.2}$-0.6: Insights into Declining Cosmic Star Formation
David DePalma, Neeraj Gupta, Hsiao-Wen Chen, Robert A. Simcoe, Sergei Balashev, Erin Boettcher, Sebastiano Cantalupo, Mandy C. Chen, Fran\c{c}oise Combes, Claude-Andr\'e Faucher-Gigu\`ere, Sean D. Johnson, Hans-Rainer Kl\"ockner, Jens-Kristian Krogager, Jennifer I-Hsiu Li, Sebasti\'an L\'opez, Pasquier Noterdaeme, Patrick Petitjean, Zhijie Qu, Gwen C. Rudi…

H I Properties of Field Galaxies at $\boldsymbol{z\approx 0.2}$-0.6: Insights into Declining Cosmic Star Formation
We report statistically significant detection of H I 21-cm emission from intermediate-redshift ($z\approx0.2$-0.6) galaxies. By leveraging multi-sightline galaxy survey data from the Cosmic Ultraviolet Baryon Survey (CUBS) and deep radio observations from the MeerKAT Absorption Line Survey (MALS), we have established a sample of $\approx6000$ spectroscopically identified galaxies in 11 distinct fields to constrain the neutral gas content at intermediate redshifts. The galaxies sample a broad ra…

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
Weixin Wang, Haoyang Zheng, Guang Lin, Wei Deng, Pan Xu
https://arxiv.org/abs/2510.05023 https:…

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
Most existing approximate Thompson Sampling (TS) algorithms for multi-armed bandits use Stochastic Gradient Langevin Dynamics (SGLD) or its variants in each round to sample from the posterior, relaxing the need for conjugacy assumptions between priors and reward distributions in vanilla TS. However, they often require approximating a different posterior distribution in different round of the bandit problem. This requires tricky, round-specific tuning of hyperparameters such as dynamic learning …

how to get a bunch of hosts on the internet to generate some sample TCP SYNs for you:
http://rage4.infra.grebedoc.dev/
mastodons gooo

🇺🇦 #NowPlaying on #BBC6Music's #TheCraigCharlesFunkAndSoulShow
Bobby Womack:
🎵 If You Think You're Lonely Now
#BobbyWomack
https://catfood88.bandcamp.com/track/bobby-womack-if-you-think-youre-lonely-now-high-pitch-sample-chop-remix
https://open.spotify.com/track/6BSHpKBd2pc3A9WQfRWzyM

Neon: Negative Extrapolation From Self-Training Improves Image Generation
Sina Alemohammad, Zhangyang Wang, Richard G. Baraniuk
https://arxiv.org/abs/2510.03597 https://

Neon: Negative Extrapolation From Self-Training Improves Image Generation
Scaling generative AI models is bottlenecked by the scarcity of high-quality training data. The ease of synthesizing from a generative model suggests using (unverified) synthetic data to augment a limited corpus of real data for the purpose of fine-tuning in the hope of improving performance. Unfortunately, however, the resulting positive feedback loop leads to model autophagy disorder (MAD, aka model collapse) that results in a rapid degradation in sample quality and/or diversity. In this pape…

Hyperon-Production Studies in $ p p \rightarrow \Lambda K^0_S p \pi^ $ with HADES
Snehankit Pattnaik, Johan Messchendorp, James Ritman
https://arxiv.org/abs/2509.04937 ht…

Hyperon-Production Studies in $ p+p \rightarrow Λ+ K^0_S + p + π^+ $ with HADES
The production mechanism of hyperons in the proton-proton collisions is explored using exclusive process with the data sample collected by HADES. The clear sign for three intermediate resonances is observed using simulated samples. It opens possibility for further detailed research.

Relative Information Gain and Gaussian Process Regression
Hamish Flynn
https://arxiv.org/abs/2510.04277 https://arxiv.org/pdf/2510.04277

Relative Information Gain and Gaussian Process Regression
The sample complexity of estimating or maximising an unknown function in a reproducing kernel Hilbert space is known to be linked to both the effective dimension and the information gain associated with the kernel. While the information gain has an attractive information-theoretic interpretation, the effective dimension typically results in better rates. We introduce a new quantity called the relative information gain, which measures the sensitivity of the information gain with respect to the o…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

Low-energy single-electron detector with sub-micron resolution
Luis Alfredo Ixquiac M\'endez, Martino Zanetti, Tilman Kraeft, Thomas Juffmann
https://arxiv.org/abs/2510.04743

Low-energy single-electron detector with sub-micron resolution
Single-electron detectors are a key component of electron microscopes and advanced electron optics experiments. We present a YAG:Ce scintillator-based single-electron detector with a spatial resolution of 1 micrometer at an electron energy of 17 keV. Single-electron detection events are identified with an efficiency and purity larger than 0.8 at an electron energy of 17 keV, reaching 0.96 at 30 keV. We show that the detector enables electron diffraction studies with a sample-detector distance c…

Who benefits the most? Direct and indirect effects of a free cesarean section policy in Benin
Selidji Caroline Tossou
https://arxiv.org/abs/2510.03658 https://

Who benefits the most? Direct and indirect effects of a free cesarean section policy in Benin
This paper evaluates the causal effect of the access to Benin's free cesarean section policy on females and their children. I use a large sample of Demographic and Health Surveys (DHS) for West African countries and analyze how the exemption of the cesarean section user fees for females in Benin directly impacts maternal and infant mortality, family size decisions, and labor market participation. I use a Difference in Differences approach and find that having access to the free cesarean section…

Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving
Zhihao Zhang, Chengyang Peng, Ekim Yurtsever, Keith A. Redmill
https://arxiv.org/abs/2509.04712

Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving
Automated vehicle control using reinforcement learning (RL) has attracted significant attention due to its potential to learn driving policies through environment interaction. However, RL agents often face training challenges in sample efficiency and effective exploration, making it difficult to discover an optimal driving strategy. To address these issues, we propose guiding the RL driving agent with a demonstration policy that need not be a highly optimized or expert-level controller. Specifi…

On Cryptography and Distribution Verification, with Applications to Quantum Advantage
Bruno Cavalar, Eli Goldin, Matthew Gray, Taiga Hiroka, Tomoyuki Morimae
https://arxiv.org/abs/2510.05028

On Cryptography and Distribution Verification, with Applications to Quantum Advantage
One of the most fundamental problems in the field of hypothesis testing is the identity testing problem: whether samples from some unknown distribution $\mathcal{G}$ are actually from some explicit distribution $\mathcal{D}$. It is known that when the distribution $\mathcal{D}$ has support $[N]$, the optimal sample complexity for the identity testing problem is roughly $O(\sqrt{N})$. However, many distributions of interest, including those which can be sampled efficiently, have exponential supp…

Gearing up for tonight's decap run.
In the queue: 5x PIC12F683 for delayering, XC6SLX25, XC7S25, ATSAMA5D27, 25AA1024
I'm not bothering to label the sample beakers because I know what most of these chips will look like from having seen other parts in the family. The ATSAM is the main unknown.
Anybody know what foundry it was made at? What node? We'll find out soon I guess.

Angular BAO Measurements with the DESI DR1 BGS Sample
Paula S. Ferreira, Ulisses Ribeiro, Pedro da Silveira Ferreira, Cl\'ecio R. Bom, Armando Bernui
https://arxiv.org/abs/2510.02144

Angular BAO Measurements with the DESI DR1 BGS Sample
We employ a model-independent approach in both the correlation function estimation and the angular BAO feature estimation by computing the angular two-point correlation function. First, we conducted a series of tests to the available DESI tracers to check their representativeness to angular clustering; the result was that, considering the completeness of the first data release across the footprint, we could only make use of the BGS sample for the effective redshifts 0.21 (BGS1) and 0.25 (BGS2).…

Updated https://adrianroselli.com/2025/10/openai-aria-and-seo-making-the-web-worse.html to link to a post from Stephanie Stimac that I missed, Simon Willison on prompt injection attacks, a sample attack from Brave, and Chris Coyier’s surprisingly long lis…

OpenAI, ARIA, and SEO: Making the Web Worse
OpenAI has announced it’s launched a new browser, Atlas, with ChatGPT built in. For those familiar with ARIA, OpenAI outlines what to expect (I left the code as I found it, other than removing the target): We’ll continue to make Atlas better, and our roadmap includes multi-profile support, improved developer…

On Improvement of Control Chart using Repetitive Sampling for Monitoring Process Mean
Fahad Rafique, Saadia Masood, Shabbir Ahmad, Sadaf Amin
https://arxiv.org/abs/2510.05086 ht…

On Improvement of Control Chart using Repetitive Sampling for Monitoring Process Mean
In the practical industry, the most commonly used application of statistical analysis for monitoring the process mean is the control chart. Control charts are generated based on the presumption that we have a sample from a stable process. The control chart then provides a graphical display to test this presumption. In the existing estimator \textcolor{red}{$Mr$}, researchers use a technique involving repetitive sampling along with an auxiliary variable for detecting and monitoring the statistic…

Oracle-based Uniform Sampling from Convex Bodies
Thanh Dang, Jiaming Liang
https://arxiv.org/abs/2510.02983 https://arxiv.org/pdf/2510.02983

Oracle-based Uniform Sampling from Convex Bodies
We propose new Markov chain Monte Carlo algorithms to sample a uniform distribution on a convex body $K$. Our algorithms are based on the Alternating Sampling Framework/proximal sampler, which uses Gibbs sampling on an augmented distribution and assumes access to the so-called restricted Gaussian oracle (RGO). The key contribution of this work is the efficient implementation of RGO for uniform sampling on $K$ via rejection sampling and access to either a projection oracle or a separation oracle…

Researching DIY solutions for preparing digital negatives for my salt/kallitype printing experiments. Working on a little curve fitting tool/library (of course using https://thi.ng/umbrella) for computing tone mapping curves derived from sample swatches (here 5% steps of gray/density). The screenshot shows 2nd - 5th d…

Can language models boost the power of randomized experiments without statistical bias?
Xinrui Ruan, Xinwei Ma, Yingfei Wang, Waverly Wei, Jingshen Wang
https://arxiv.org/abs/2510.05545

Can language models boost the power of randomized experiments without statistical bias?
Randomized experiments or randomized controlled trials (RCTs) are gold standards for causal inference, yet cost and sample-size constraints limit power. Meanwhile, modern RCTs routinely collect rich, unstructured data that are highly prognostic of outcomes but rarely used in causal analyses. We introduce CALM (Causal Analysis leveraging Language Models), a statistical framework that integrates large language models (LLMs) predictions with established causal estimators to increase precision whil…

ResCP: Reservoir Conformal Prediction for Time Series Forecasting
Roberto Neglia, Andrea Cini, Michael M. Bronstein, Filippo Maria Bianchi
https://arxiv.org/abs/2510.05060 https…

ResCP: Reservoir Conformal Prediction for Time Series Forecasting
Conformal prediction offers a powerful framework for building distribution-free prediction intervals for exchangeable data. Existing methods that extend conformal prediction to sequential data rely on fitting a relatively complex model to capture temporal dependencies. However, these methods can fail if the sample size is small and often require expensive retraining when the underlying data distribution changes. To overcome these limitations, we propose Reservoir Conformal Prediction (ResCP), a…

Series C, Episode 07 - Children of Auron
DERAL: Is that all it takes, then? A sample of blood?
FRANTON: It's the genetic print we need. All body cells with a nucleus carry that. The white cells are here. As long as they're capable of differentiation, they're capable of growth, into another you.
https://blake.torpid…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

🇺🇦 Auf radioeins läuft...
Foxwarren:
🎵 Listen2me
#NowPlaying #Foxwarren
https://foxwarren.bandcamp.com/track/listen2me-stem20-sample-listen2me
https://open.spotify.com/track/29WWHCuzU0OCWTfiBKbOm1

Modular and Adaptive Conformal Prediction for Sequential Models via Residual Decomposition
William Zhang, Saurabh Amin, Georgia Perakis
https://arxiv.org/abs/2510.04406 https://…

Modular and Adaptive Conformal Prediction for Sequential Models via Residual Decomposition
Conformal prediction offers finite-sample coverage guarantees under minimal assumptions. However, existing methods treat the entire modeling process as a black box, overlooking opportunities to exploit modular structure. We introduce a conformal prediction framework for two-stage sequential models, where an upstream predictor generates intermediate representations for a downstream model. By decomposing the overall prediction residual into stage-specific components, our method enables practition…

Percolation and criticality of systems with competing interactions on Bethe lattices: limitations and potential strengths of cluster schemes
Greivin Alfaro Miranda, Mingyuan Zheng, Patrick Charbonneau, Antonio Coniglio, Leticia F. Cugliandolo, Marco Tarzia
https://arxiv.org/abs/2510.02961

Percolation and criticality of systems with competing interactions on Bethe lattices: limitations and potential strengths of cluster schemes
The random clusters introduced by Fortuin and Kasteleyn (FK) and analyzed by Coniglio and Klein (CK) for Ising and related models have led first Swendsen and Wang and then Wolff to formulate remarkably efficient Markov chain Monte Carlo sampling schemes that weaken the critical slowing down. In frustrated models, however, no standard way to produce a comparable gain at small frustration -- let alone efficiently sample the large frustration regime -- has yet been identified. In order to understa…

Minimum Sample Size Calculation for Multivariable Regression of Continuous Outcomes in Chemometrics for Astrobiology and Planetary Science
M. Konstantinidis, E. A. Lalla, S. J. Gonzalez, J. Manrique, G. Lopez-Reyes, A. Barlow, E. Sawyers, B. Barrios, M. G. Daly
https://arxiv.org/abs/2510.01210

Minimum Sample Size Calculation for Multivariable Regression of Continuous Outcomes in Chemometrics for Astrobiology and Planetary Science
Over the last few decades, prediction models have become a fundamental tool in statistics, chemometrics, and related fields. However, to ensure that such models have high value, the inferences that they generate must be reliable. In this regard, the internal validity of a prediction model might be threatened if it is not calibrated with a sufficiently large sample size, as problems such as overfitting may occur. Such situations would be highly problematic in many fields, including space science…

Using #PHP arrays as pseudo-objects is almost never the right answer. They're less self-documenting, slower, worse on memory, and more bug prone.
https://peakd.com/php/@crell/php-use-a

Oracle-Guided Masked Contrastive Reinforcement Learning for Visuomotor Policies
Yuhang Zhang, Jiaping Xiao, Chao Yan, Mir Feroskhan
https://arxiv.org/abs/2510.05692 https://

Oracle-Guided Masked Contrastive Reinforcement Learning for Visuomotor Policies
A prevailing approach for learning visuomotor policies is to employ reinforcement learning to map high-dimensional visual observations directly to action commands. However, the combination of high-dimensional visual inputs and agile maneuver outputs leads to long-standing challenges, including low sample efficiency and significant sim-to-real gaps. To address these issues, we propose Oracle-Guided Masked Contrastive Reinforcement Learning (OMC-RL), a novel framework designed to improve the samp…

Exploring Stellar Activity in a Sample of Active M Dwarfs
A. S. Rajpurohit, V. Kumar, K. Srivastava Mudit, L. Labadie, K. Rajpurohit, J. G. Fernandez-Trincado
https://arxiv.org/abs/2510.02693

Exploring Stellar Activity in a Sample of Active M Dwarfs
Most M dwarfs show higher chromospheric activity, often exceeding solar levels. Characterizing stellar activity is essential, particularly since these stars are prime targets in the search for habitable exoplanets. We investigate the stellar activity of active M dwarfs using TESS photometry combined with spectroscopic observations. We explore relations between flare occurrence rate (FOR), flare energies, rotation period, starspot filling factor, and chromospheric indicators. We also examine cor…

From Learning to Mastery: Achieving Safe and Efficient Real-World Autonomous Driving with Human-In-The-Loop Reinforcement Learning
Li Zeqiao, Wang Yijing, Wang Haoyu, Li Zheng, Li Peng, Liu Wenfei, Zuo Zhiqiang
https://arxiv.org/abs/2510.06038

From Learning to Mastery: Achieving Safe and Efficient Real-World Autonomous Driving with Human-In-The-Loop Reinforcement Learning
Autonomous driving with reinforcement learning (RL) has significant potential. However, applying RL in real-world settings remains challenging due to the need for safe, efficient, and robust learning. Incorporating human expertise into the learning process can help overcome these challenges by reducing risky exploration and improving sample efficiency. In this work, we propose a reward-free, active human-in-the-loop learning method called Human-Guided Distributional Soft Actor-Critic (H-DSAC). …

Topic Modeling as Long-Form Generation: Can Long-Context LLMs revolutionize NTM via Zero-Shot Prompting?
Xuan Xu, Haolun Li, Zhongliang Yang, Beilin Chu, Jia Song, Moxuan Xu, Linna Zhou
https://arxiv.org/abs/2510.03174

Topic Modeling as Long-Form Generation: Can Long-Context LLMs revolutionize NTM via Zero-Shot Prompting?
Traditional topic models such as neural topic models rely on inference and generation networks to learn latent topic distributions. This paper explores a new paradigm for topic modeling in the era of large language models, framing TM as a long-form generation task whose definition is updated in this paradigm. We propose a simple but practical approach to implement LLM-based topic model tasks out of the box (sample a data subset, generate topics and representative text with our prompt, text assi…

Spectral Measurement of the $^{214}$Bi beta-decay to the $^{214}$Po Ground State with XENONnT
E. Aprile, J. Aalbers, K. Abe, M. Adrover, S. Ahmed Maouloud, L. Althueser, B. Andrieu, E. Angelino, D. Ant\'on Martin, S. R. Armbruster, F. Arneodo, L. Baudis, M. Bazyk, L. Bellagamba, R. Biondi, A. Bismark, K. Boese, R. M. Braun, A. Brown, G. Bruno, R. Budnik, C. Cai, C. Capelli, J. M. R. Cardoso, A. P. Cimental Ch\'avez, A. P. Colijn, J. Conrad, J. J. Cuenca-Garc\'ia, V. D'A…

Spectral Measurement of the $^{214}$Bi beta-decay to the $^{214}$Po Ground State with XENONnT
We report the measurement of the $^{214}$Bi beta-decay spectrum to the ground state of $^{214}$Po using the XENONnT detector. This decay is classified as first-forbidden non-unique, for which theoretical predictions require detailed nuclear structure modeling. A dedicated identification algorithm isolates a high-purity sample of ground-state beta-decays, explicitly excluding events with associated gamma-rays emission. By comparing the measured spectrum, which covers energies up to 3.27 MeV, wit…

Beyond Regularization: Inherently Sparse Principal Component Analysis
Jan O. Bauer
https://arxiv.org/abs/2510.03729 https://arxiv.org/pdf/2510.03729…

Beyond Regularization: Inherently Sparse Principal Component Analysis
Sparse principal component analysis (sparse PCA) is a widely used technique for dimensionality reduction in multivariate analysis, addressing two key limitations of standard PCA. First, sparse PCA can be implemented in high-dimensional low sample size settings, such as genetic microarrays. Second, it improves interpretability as components are regularized to zero. However, over-regularization of sparse singular vectors can cause them to deviate greatly from the population singular vectors, pote…

Domain-Shift-Aware Conformal Prediction for Large Language Models
Zhexiao Lin, Yuanyuan Li, Neeraj Sarna, Yuanyuan Gao, Michael von Gablenz
https://arxiv.org/abs/2510.05566 http…

Domain-Shift-Aware Conformal Prediction for Large Language Models
Large language models have achieved impressive performance across diverse tasks. However, their tendency to produce overconfident and factually incorrect outputs, known as hallucinations, poses risks in real world applications. Conformal prediction provides finite-sample, distribution-free coverage guarantees, but standard conformal prediction breaks down under domain shift, often leading to under-coverage and unreliable prediction sets. We propose a new framework called Domain-Shift-Aware Conf…

Estimation of intrinsic fast radio burst width and scattering distributions from CRAFT data
C. W. James, J. Hoffmann, J. X. Prochaska, M. Glowacki
https://arxiv.org/abs/2510.05654

Estimation of intrinsic fast radio burst width and scattering distributions from CRAFT data
The intrinsic width and scattering distributions of fast radio bursts (FRBs) inform on their emission mechanism and local environment, and act as a source of detection bias and, hence, an obfuscating factor when performing FRB population and cosmological studies. Here, we utilise a sample of 29 FRBs with measured high-time-resolution properties and known redshift, which were detected using the Australian Square Kilometre Array Pathfinder (ASKAP) by the Commensal Real-time ASKAP Fast Transients …

Active Semantic Perception
Huayi Tang, Pratik Chaudhari
https://arxiv.org/abs/2510.05430 https://arxiv.org/pdf/2510.05430

Active Semantic Perception
We develop an approach for active semantic perception which refers to using the semantics of the scene for tasks such as exploration. We build a compact, hierarchical multi-layer scene graph that can represent large, complex indoor environments at various levels of abstraction, e.g., nodes corresponding to rooms, objects, walls, windows etc. as well as fine-grained details of their geometry. We develop a procedure based on large language models (LLMs) to sample plausible scene graphs of unobser…

General Divergence Regularized Optimal Transport: Sample Complexity and Central Limit Theorems
Jiaping Yang, Yunxin Zhang
https://arxiv.org/abs/2510.02489 https://

General Divergence Regularized Optimal Transport: Sample Complexity and Central Limit Theorems
Optimal transport has emerged as a fundamental methodology with applications spanning multiple research areas in recent years. However, the convergence rate of the empirical estimator to its population counterpart suffers from the curse of dimensionality, which prevents its application in high-dimensional spaces. While entropic regularization has been proven to effectively mitigate the curse of dimensionality and achieve a parametric convergence rate under mild conditions, these statistical gua…

Suzaku observations of outskirts of nearby clusters and groups: I. electron density and gas fraction to the virial radius
Kyoko Matsushita, Marie Kondo, Kosuke Sato, Toru Sasaki, Nobuhiro Okabe, Kotaro Fukushima
https://arxiv.org/abs/2510.04523

Suzaku observations of outskirts of nearby clusters and groups: I. electron density and gas fraction to the virial radius
We present an analysis of Suzaku observations of 14 nearby galaxy clusters and groups (z < 0.06), extending radial coverage out to the virial radius (approximately r200). The sample spans a wide mass range, from M500 about 2x10^13 to 7x10^14 solar masses, and includes well-studied systems such as Coma, Perseus, and Virgo. We carefully modeled all background components, including the soft X-ray foregrounds (the Local Hot Bubble, Milky Way Halo, and super-virial temperature components), the cosmi…

Abundance of strontium in the Galactic globular cluster 47 Tuc
E. Kolomiecas, A. Ku\v{c}inskas, J. Klevas, V. Dobrovolskas
https://arxiv.org/abs/2510.04722 https://

Abundance of strontium in the Galactic globular cluster 47 Tuc
Aims. We have determined Sr abundance in a sample of 31 red giant branch stars located in the Galactic globular cluster 47 Tuc with the aim to identify potential differences in the Sr abundance between first population (1P, Na-poor) and second population (2P, Na-rich) stars. Methods. We derived the Na and Sr abundances from the archival spectra obtained with the UVES spectrograph. To do this, we used 1D ATLAS9 model atmospheres and a 1D local thermodynamic equilibrium spectral synthesis method.…

Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models
Ethan Baron, Boris Oreshkin, Ruijun Ma, Hanyu Zhang, Kari Torkkola, Michael W. Mahoney, Andrew Gordon Wilson, Tatiana Konstantinova
https://arxiv.org/abs/2510.02224

Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models
Many time series applications require access to multi-step forecast trajectories in the form of sample paths. Recently, time series foundation models have leveraged multi-step lookahead predictions to improve the quality and efficiency of multi-step forecasts. However, these models only predict independent marginal distributions for each time step, rather than a full joint predictive distribution. To generate forecast sample paths with realistic correlation structures, one typically resorts to …

Self-Speculative Masked Diffusions
Andrew Campbell, Valentin De Bortoli, Jiaxin Shi, Arnaud Doucet
https://arxiv.org/abs/2510.03929 https://arxiv.org/pdf/2…

Self-Speculative Masked Diffusions
We present self-speculative masked diffusions, a new class of masked diffusion generative models for discrete data that require significantly fewer function evaluations to generate samples. Standard masked diffusion models predict factorized logits over currently masked positions. A number of masked positions are then sampled, however, the factorization approximation means that sampling too many positions in one go leads to poor sample quality. As a result, many simulation steps and therefore n…

When correcting for regression to the mean is worse than no correction at all
Jos\'e F. Fontanari, Mauro Santos
https://arxiv.org/abs/2509.04718 https://

When correcting for regression to the mean is worse than no correction at all
The ubiquitous regression to the mean (RTM) effect complicates statistical inference in biological studies of change. We demonstrate that common RTM correction methods are flawed: the Berry et al. method popularized by Kelly & Price in The American Naturalist is unreliable for hypothesis testing, leading to both false positives and negatives, while the theoretically unbiased Blomqvist method has poor efficiency in limited sample sizes. Our findings show that the most robust approach to handling…

Gravitational lensing by a spiral galaxy I: the influence from bar's structure to the flux ratio anomaly
Xikai Shan, Yunpeng Jin, Shude Mao
https://arxiv.org/abs/2510.02805 …

Gravitational lensing by a spiral galaxy I: the influence from bar's structure to the flux ratio anomaly
Gravitational lens flux ratio anomalies are a powerful probe of small-scale mass structures within lens galaxies. These anomalies are often attributed to dark matter subhalos, but the baryonic components of the lens can also play a significant role. This study investigates the impact of galactic bars, a common feature in spiral galaxies, on flux ratio anomalies. We conduct a systematic analysis using a sample of 21 barred galaxies from the high-resolution Auriga cosmological simulations. First,…

WALLABY Pilot Survey: Characterizing Low Rotation Kinematically Modelled Galaxies
N. Deg, K. Spekkens, N. Arora, R. Dudley, H. White, A. Helias, J. English, T. O'Beirne, V. Kilborn, G. Ferrand, M. L. A. Richardson, B. Catinella, L. Cortese, H. D\'enes, A. Elagali, B. -Q. For, K. Lee-Waddell, J. Rhee, L. Shao, A. X. Shen, L. Staveley-Smith, T. Westmeier, O. I. Wong

WALLABY Pilot Survey: Characterizing Low Rotation Kinematically Modelled Galaxies
Many of the tensions in cosmological models of the Universe lie in the low mass, low velocity regime. Probing this regime requires a statistically significant sample of galaxies with well measured kinematics and robustly measured uncertainties. WALLABY, as a wide area, untargetted HI survey is well positioned to construct this sample. As a first step towards this goal we develop a framework for testing kinematic modelling codes in the low resolution, low $S/N$, low rotation velocity regime. We …

Dormant BH candidates from Gaia DR3 summary diagnostics
Johanna M\"uller-Horn, Hans-Walter Rix, Kareem El-Badry, Ben Pennell, Matthew Green, Jiadong Li, Rhys Seeburger
https://arxiv.org/abs/2510.05982

Dormant BH candidates from Gaia DR3 summary diagnostics
We present a rigorous identification of candidates for dormant black holes (BHs) and neutron stars (NSs) in binaries using summary statistics from Gaia DR3, rather than full orbital solutions. Although Gaia astrometric orbits have already revealed a small sample of compact object binaries, many systems remain undetected due to stringent quality cuts imposed on the published orbits. Using a forward-modelling framework that simulates Gaia observables, in particular the renormalised unit weight er…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
Zhijun Liu, Jiang Hu, Zhidong Bai, Zhihui Lv
https://arxiv.org/abs/2510.04185 h…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
In this paper, we establish the Central Limit Theorem (CLT) for linear spectral statistics (LSSs) of large-dimensional generalized spiked sample covariance matrices, where the spiked eigenvalues may be either bounded or diverge to infinity. Building upon this theorem, we derive the asymptotic distributions of linear hypothesis test statistics under the generalized spiked model, including Wilks' likelihood ratio test statistic U, the Lawley-Hotelling trace test statistic W, and the Bartlett-Nand…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
Jan Ole von Hartz, Lukas Schweizer, Joschka Boedecker, Abhinav Valada
https://arxiv.org/abs/2509.24956

MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
Generative robot policies such as Flow Matching offer flexible, multi-modal policy learning but are sample-inefficient. Although object-centric policies improve sample efficiency, it does not resolve this limitation. In this work, we propose Multi-Stream Generative Policy (MSG), an inference-time composition framework that trains multiple object-centric policies and combines them at inference to improve generalization and sample efficiency. MSG is model-agnostic and inference-only, hence widely…

Wide binaries in an ultra-faint dwarf galaxy: discovery, population modeling, and a nail in the coffin of primordial black hole dark matter
Cheyanne Shariat, Kareem El-Badry, Mario Gennaro, Keyi Ding, Joshua D. Simon, Roberto J. Avila, Annalisa Calamida, Santi Cassisi, Matteo Correnti, Daniel R. Weisz, Marla Geha, Evan N. Kirby, Thomas M. Brown, Massimo Ricotti, Kristen B. W. McQuinn, Nitya Kallivayalil, Karoline Gilbert, Camilla Pacifici, Puragra Guhathakurta, Denija Crnojevi\'c, …

Wide binaries in an ultra-faint dwarf galaxy: discovery, population modeling, and a nail in the coffin of primordial black hole dark matter
We report the discovery and characterization of a wide binary population in the ultrafaint dwarf galaxy Boötes I using deep JWST/NIRCam imaging. Our sample consists of 52 candidate binaries with projected separations of 7,000 - 16,000 au and stellar masses from near the hydrogen-burning limit to the main-sequence turnoff ($\sim0.1$ - $0.8~{\rm M_\odot}$). By forward-modeling selection biases and chance alignments, we find that $1.25\pm0.25\%$ of Boötes I stars are members of wide binaries wit…

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
Ali Dadsetan, Frank Rudzicz
https://arxiv.org/abs/2510.01137 https://arxi…

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
We address the challenge of sample efficiency in differentially private fine-tuning of large language models (LLMs) using DP-SGD. While DP-SGD provides strong privacy guarantees, the added noise significantly increases the entropy of gradient matrices, disrupting their low-rank structure and slowing optimization. We propose a post-processing algorithm that leverages random matrix theory to denoise gradients, restore low-rank structure, and improve alignment with the original signal. Applied to …

A GLIMPSE into the very faint-end of the H$\beta$ [OIII]$\lambda\lambda$4960,5008 luminosity function at z=7-9 behind Abell S1063
Damien Korber, Iryna Chemerynska, Lukas J. Furtak, Hakim Atek, Ryan Endsley, Daniel Schaerer, John Chisholm, Alberto Saldana-Lopez, Angela Adamo, Julian B. Mu\~noz, Pascal A. Oesch, Romain Meyer, Rui Marques-Chaves, Seiji Fujimoto
ht…

A GLIMPSE into the very faint-end of the H$β$+[OIII]$λλ$4960,5008 luminosity function at z=7-9 behind Abell S1063
We use the ultra-deep GLIMPSE JWST/NIRCam survey to constrain the faint-end of the H$β$+[OIII]$λλ$4960,5008 luminosity function (LF) down to $10^{39}$ erg/s at z=7-9 behind the lensed Hubble Frontier Field Abell S1063. We perform SED fitting on a Lyman-Break Galaxy sample, measuring combined H$β$+[OIII] fluxes to construct the emission-line LF. The resulting LF ($α$=-1.55 to -1.78) is flatter than the UV LF ($α<-2$), indicating a lower number density of low H$β$+[OIII] emitters at fixed …

A supermassive black hole under the radar: repeating X-ray variability in a Seyfert galaxy
Matteo Imbrogno, Andrea Sacchi, Giovanni Miniutti, Francesco Tombesi, Gian Luca Israel, Enrico Piconcelli, Roberta Amato
https://arxiv.org/abs/2510.02832

A supermassive black hole under the radar: repeating X-ray variability in a Seyfert galaxy
In the last few years, a few supermassive black holes (SMBHs) have shown short-term (of the order of hours) X-ray variability. Given the limited size of the sample, every new addition to this class of SMBHs can bring invaluable information. Within the context of an automated search for X-ray sources showing flux variability in the \textit{Chandra} archive, we identified peculiar variability patterns in 2MASX J12571076+2724177 (J1257), a SMBH in the Coma cluster, during observations performed in…

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
Ahmad Fraij, Sam Dauncey
https://arxiv.org/abs/2509.24974 https://

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
Data scarcity drives the need for more sample-efficient large language models. In this work, we use the double descent phenomenon to holistically compare the sample efficiency of discrete diffusion and autoregressive models. We show that discrete diffusion models require larger capacity and more training epochs to escape their underparameterized regime and reach the interpolation threshold. In the strongly overparameterized regime, both models exhibit similar behavior, with neither exhibiting a…

The Prevalence of Bursty Star Formation in Low-Mass Galaxies at z=1-7 from H{\alpha}-to-UV Diagnostics
Marissa N. Perry (The University of Texas at Austin, Department of Astronomy), Anthony J. Taylor (The University of Texas at Austin, Department of Astronomy), Oscar A. Chavez Ortiz (The University of Texas at Austin, Department of Astronomy), Steven L. Finkelstein (The University of Texas at Austin, Department of Astronomy), Gene C. K. Leung (MIT Kavli Institute for Astrophysics and S…

The Prevalence of Bursty Star Formation in Low-Mass Galaxies at z=1-7 from Hα-to-UV Diagnostics
We present an analysis of bursty star-formation histories (SFHs) of 346 star-forming galaxies at $1\lesssim z<7$, selected from JWST/NIRSpec G395M and PRISM spectroscopy provided by the CEERS and RUBIES surveys. We analyze the correlation of star-formation rate vs. stellar mass (the star-forming main sequence, SFMS) for our sample and find no significant difference between the intrinsic scatter in the H$α$-based SFMS and the UV-continuum-based SFMS. However, the diagnostic power of the SFMS is…

Empirical partially Bayes two sample testing
Wanyi Ling, Wufang Hong, Nikolaos Ignatiadis
https://arxiv.org/abs/2510.00432 https://arxiv.org/pdf/2510.00432…

Empirical partially Bayes two sample testing
A common task in high-throughput biology is to test for differences in means between two samples across thousands of features (e.g., genes or proteins), often with only a handful of replicates per sample. Moderated t-tests handle this problem by assuming normality and equal variances, and by applying the empirical partially Bayes principle: a prior is posited and estimated for the nuisance parameters (variances) but not for the primary parameters (means). This approach has been highly successfu…

The atomic gas properties of Green Pea galaxies: Connections to Lyman continuum leakage
Archishman Khasnovis (National Centre for Radio Astrophysics, India), Nissim Kanekar (National Centre for Radio Astrophysics, India), Sangeeta Malhotra (NASA Goddard Space Flight Center, USA), James Rhoads (NASA Goddard Space Flight Center, USA)
https://

The atomic gas properties of Green Pea galaxies: Connections to Lyman continuum leakage
We have used the Green Bank Telescope to search for H{\sc{i}} 21\,cm emission from 30 Green Pea galaxies (GPs) at $z\approx0.012-0.045$, obtaining 7 detections of H{\sc{i}} 21\,cm emission and 17 upper limits on the H{\sc{i}} mass. Including GPs from the literature, we obtain a sample of 60 GPs at $z<0.05$, with 19 detections and 41 non-detections of H{\sc{i}} 21\,cm emission, and with stellar masses in the range $10^6-10^9\,\rm{M_{\odot}}$. We use the line luminosity ratio O32~$\equiv$~[O{\sc …

Neural Jump ODEs as Generative Models
Robert A. Crowell, Florian Krach, Josef Teichmann
https://arxiv.org/abs/2510.02757 https://arxiv.org/pdf/2510.02757…

Neural Jump ODEs as Generative Models
In this work, we explore how Neural Jump ODEs (NJODEs) can be used as generative models for Itô processes. Given (discrete observations of) samples of a fixed underlying Itô process, the NJODE framework can be used to approximate the drift and diffusion coefficients of the process. Under standard regularity assumptions on the Itô processes, we prove that, in the limit, we recover the true parameters with our approximation. Hence, using these learned coefficients to sample from the correspond…

ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization
Jamison Meindl, Yunsheng Tian, Tony Cui, Veronika Thost, Zhang-Wei Hong, Johannes D\"urholt, Jie Chen, Wojciech Matusik, Mina Konakovi\'c Lukovi\'c
https://arxiv.org/abs/2510.03051

ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization
Global optimization of expensive, derivative-free black-box functions requires extreme sample efficiency. While Bayesian optimization (BO) is the current state-of-the-art, its performance hinges on surrogate and acquisition function hyper-parameters that are often hand-tuned and fail to generalize across problem landscapes. We present ZeroShotOpt, a general-purpose, pretrained model for continuous black-box optimization tasks ranging from 2D to 20D. Our approach leverages offline reinforcement …

Rapid Scaling of Compositional Uncertainty from Sample to Population Levels
Yiran Wang, Martin Lysy, Audrey B\'eliveau
https://arxiv.org/abs/2510.00980 https://

Rapid Scaling of Compositional Uncertainty from Sample to Population Levels
Understanding population composition is essential across ecological, evolutionary, conservation, and resource management contexts. Modern methods such as genetic stock identification (GSI) estimate the proportion of individuals from each subpopulation using genetic data. Ideally, these estimates are obtained through mixture analysis, which captures both sampling and genetic uncertainty. However, historical datasets often rely on individual assignment methods that only account for sample-level u…

Learning to Sample: Reinforcement Learning-Guided Sampling for Autonomous Vehicle Motion Planning
Korbinian Moller, Roland Stroop, Mattia Piccinini, Alexander Langmann, Johannes Betz
https://arxiv.org/abs/2509.24313

Learning to Sample: Reinforcement Learning-Guided Sampling for Autonomous Vehicle Motion Planning
Sampling-based motion planning is a well-established approach in autonomous driving, valued for its modularity and analytical tractability. In complex urban scenarios, however, uniform or heuristic sampling often produces many infeasible or irrelevant trajectories. We address this limitation with a hybrid framework that learns where to sample while keeping trajectory generation and evaluation fully analytical and verifiable. A reinforcement learning (RL) agent guides the sampling process toward…

Optimising the MeerKAT Pulsar Timing Array and towards precision pulsar timing with SKA-mid
Pratyasha Gitika, Ryan M. Shannon, Matthew Bailes, Daniel J. Reardon, Matthew T. Miles, David J. Champion, Kathrin Grunthal
https://arxiv.org/abs/2510.03139

Optimising the MeerKAT Pulsar Timing Array and towards precision pulsar timing with SKA-mid
Pulsar timing arrays (PTAs) are Galactic-scale nanohertz-frequency gravitational wave (GW) detectors. Recently, several PTAs have found evidence for the presence of GWs in their datasets, but none of them have achieved a community-defined definitive (> 5$σ$) detection. Here, we identify limiting noise sources for PTAs and quantify their impact on sensitivity to GWs under different observing and noise modelling strategies. First, we search for intrinsic pulse jitter in a sample of 89 MSPs obser…

The orbital anisotropy profile of the Gaia-Sausage/Enceladus accretion remnant
James M. M. Lane, Jo Bovy
https://arxiv.org/abs/2509.04557 https://arxiv.org…

The orbital anisotropy profile of the Gaia-Sausage/Enceladus accretion remnant
The Gaia-Sausage/Enceladus (GS/E) accretion remnant is one of the most important stellar populations in the Milky Way halo. Recent simulation-based work has suggested that the anisotropy profiles of remnants like GS/E decline towards the center and may be well-fit by an Osipkov-Merritt-type distribution function (DF). We study the anisotropy profile of GS/E using a chemically-selected sample of stars from APOGEE DR17 and Gaia. We find that the anisotropy profile of GS/E is high and constant wit…

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
Ivan Lau, Jonathan Scarlett
https://arxiv.org/abs/2509.21940 https://arxiv.org/pdf/250…

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
In this paper, we study the problem of distributed mean estimation with 1-bit communication constraints. We propose a mean estimator that is based on (randomized and sequentially-chosen) interval queries, whose 1-bit outcome indicates whether the given sample lies in the specified interval. Our estimator is $(ε, δ)$-PAC for all distributions with bounded mean ($-λ\le \mathbb{E}(X) \le λ$) and variance ($\mathrm{Var}(X) \le σ^2$) for some known parameters $λ$ and $σ$. We derive a sample c…

A Large Sample of JWST/NIRSpec Brown Dwarfs: New Distant Discoveries
Zhijun Tu, Shu Wang, Xiaodian Chen, Jifeng Liu
https://arxiv.org/abs/2510.02026 https://

A Large Sample of JWST/NIRSpec Brown Dwarfs: New Distant Discoveries
Brown dwarfs are essential probes of stellar and planetary formation, yet their low luminosities pose challenges for detection at large Galactic distances. The James Webb Space Telescope (JWST), with its unprecedented near-infrared sensitivity, enables the discovery and characterization of distant substellar objects, including those in the Milky Way's thick disk and halo. We conducted a systematic search using over 40,000 publicly available JWST/NIRSpec PRISM/CLEAR spectra and identified 68 bro…

Private Realizable-to-Agnostic Transformation with Near-Optimal Sample Complexity
Bo Li, Wei Wang, Peng Ye
https://arxiv.org/abs/2510.01291 https://arxiv.o…

Private Realizable-to-Agnostic Transformation with Near-Optimal Sample Complexity
The realizable-to-agnostic transformation (Beimel et al., 2015; Alon et al., 2020) provides a general mechanism to convert a private learner in the realizable setting (where the examples are labeled by some function in the concept class) to a private learner in the agnostic setting (where no assumptions are imposed on the data). Specifically, for any concept class $\mathcal{C}$ and error parameter $α$, a private realizable learner for $\mathcal{C}$ can be transformed into a private agnostic le…

The Accretion Disk Size Problem in AGN Disk Reverberation Mapping is an Obscuration Effect: A Uniform AGN Sample Study with Swift
Collin Lewin, Erin Kara, Christos Panagiotou, Edward M. Cackett, Jonathan Gelbord, Juan V. Hern\'andez Santisteban, Keith Horne, Gerard A. Kriss
https://arxiv.org/abs/2509.25315

The Accretion Disk Size Problem in AGN Disk Reverberation Mapping is an Obscuration Effect: A Uniform AGN Sample Study with Swift
In the past decade, Swift has performed several AGN high-cadence reverberation mapping campaigns, and generally found that the UV/optical interband lags are $\sim$3 times longer than predicted for a standard thin disk, thus coined "the accretion disk size problem". Here we present a systematic sample of Swift-monitored AGN. In this analysis, we confirm the accretion disk size problem, but find that the lag excess occurs only in the subset of obscured AGN, which show a significantly elevated mea…

Bias-Reduced Estimation of Structural Equation Models
Haziq Jamil, Yves Rosseel, Oliver Kemp, Ioannis Kosmidis
https://arxiv.org/abs/2509.25419 https://arx…

Bias-Reduced Estimation of Structural Equation Models
Finite-sample bias is a pervasive challenge in the estimation of structural equation models (SEMs), especially when sample sizes are small or measurement reliability is low. A range of methods have been proposed to improve finite-sample bias in the SEM literature, ranging from analytic bias corrections to resampling-based techniques, with each carrying trade-offs in scope, computational burden, and statistical performance. We apply the reduced-bias M-estimation framework (RBM, Kosmidis & Lunard…

JADES Data Release 4 Paper I: Sample Selection, Observing Strategy and Redshifts of the complete spectroscopic sample
Emma Curtis-Lake, Alex J. Cameron, Andrew J. Bunker, Jan Scholtz, Stefano Carniani, Eleonora Parlanti, Francesco D'Eugenio, Peter Jakobsen, Christopher N. A. Willmer, Santiago Arribas, William M. Baker, St\'ephane Charlot, Jacopo Chevallard, Chiara Circosta, Mirko Curti, Daniel J. Eisenstein, Kevin Hainline, Zhiyuan Ji, Benjamin D. Johnson, Gareth C. Jones, Robe…

JADES Data Release 4 Paper I: Sample Selection, Observing Strategy and Redshifts of the complete spectroscopic sample
This paper accompanies Data Release 4 of the JWST Deep Extragalactic Survey (JADES), which presents the full NIRSpec spectroscopy of the survey. We provide spectra of 5190 targets across GOODS-North and GOODS-South (including the Hubble Ultra Deep Field), observed with the low-dispersion (R $\sim$ 30-300) prism and three medium-resolution (R $\sim$ 1000) gratings spanning 0.8 $< λ<$ 5.5 microns; 2654 were also observed with the higher-resolution (R $\sim$ 2700) G395H grating. The tiered survey…

Probing the Low Radio Frequency Emission in PG Quasars with the uGMRT - II
Sanna Gulati (NCRA-TIFR), Silpa Sasikumar (Universidad de Concepci\'on), Preeti Kharb (NCRA-TIFR), Luis C. Ho (Peking University), Salmoli Ghosh (NCRA-TIFR), Janhavi Baghel (NCRA-TIFR)
https://arxiv.org/abs/2510.02736

Probing the Low Radio Frequency Emission in PG Quasars with the uGMRT - II
We present results from uGMRT 685 MHz observations of 87 QSOs belonging to the Palomar Green (PG) quasar sample with $z<0.5$. Radio emission is detected in all sources except for 3 radio-quiet (RQ) sources, viz., PG 0043+039, PG 1121+422, and PG 1552+085. The radio-loud (RL) $-$ RQ dichotomy persists at 685 MHz with only 1 source, PG 1216+069, changing its classification from RQ to RL. Approximately 1/3 of the detected RQ quasars display AGN-dominated radio emission while the rest may show addi…

Analysis of the plane of satellites around Milky Way-like galaxies in $\Lambda$CDM cosmology
Xinghai Zhao, Guobao Tang, Paola Gonzalez, Grant J. Mathews, Lara Arielle Phillips
https://arxiv.org/abs/2510.02518

Analysis of the plane of satellites around Milky Way-like galaxies in $Λ$CDM cosmology
It has been suggested that the Plane of Satellites (PoS) phenomenon may imply a tension with current $Λ$CDM cosmology since a Milky-Way (MW)-like PoS is very rare in simulations. In this study, we analyze a large sample of satellite systems of MW-like galaxies in the IllustrisTNG simulations. We analyze their spatial aspect ratio, orbital pole dispersion, Gini coefficient, radial distribution, and bulk satellite velocity relative to the host galaxy. These are compared to the observed Milky~Way…