Tootfinder

A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
Bolin Li, Gewei Zuo, Zhixiang Wang, Xiaotian Ke, Lijun Zhu, Han Ding
https://arxiv.org/abs/2508.13531

A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
This paper presents a control framework designed to enhance the stability and robustness of legged robots in the presence of uncertainties, including model uncertainties, external disturbances, and faults. The framework enables the full-state feedback estimator to estimate and compensate for uncertainties in whole-body dynamics of the legged robots. First, we propose a novel moving horizon extended state observer (MH-ESO) to estimate uncertainties and mitigate noise in legged systems, which can…

Iterative Youla-Kucera Loop Shaping For Precision Motion Control
Xiaohai Hu, Jason Laks, Guoxiao Guo, Xu Chen
https://arxiv.org/abs/2508.14309 https://arxi…

Iterative Youla-Kucera Loop Shaping For Precision Motion Control
This paper presents a numerically robust approach to multi-band disturbance rejection using an iterative Youla-Kucera parameterization technique. The proposed method offers precise control over shaping the frequency response of a feedback loop while maintaining numerical stability through a systematic design process. By implementing an iterative approach, we overcome a critical numerical issue in rejecting vibrations with multiple frequency bands. Meanwhile, our proposed modification of the all…

Multi-pathology Chest X-ray Classification with Rejection Mechanisms
Yehudit Aperstein, Amit Tzahar, Alon Gottlib, Tal Verber, Ravit Shagan Damti, Alexander Apartsin
https://arxiv.org/abs/2509.10348

Multi-pathology Chest X-ray Classification with Rejection Mechanisms
Overconfidence in deep learning models poses a significant risk in high-stakes medical imaging tasks, particularly in multi-label classification of chest X-rays, where multiple co-occurring pathologies must be detected simultaneously. This study introduces an uncertainty-aware framework for chest X-ray diagnosis based on a DenseNet-121 backbone, enhanced with two selective prediction mechanisms: entropy-based rejection and confidence interval-based rejection. Both methods enable the model to ab…

I’ve been cut seven times in the NFL. Here is what those experiences taught me https://www.nytimes.com/athletic/6617623/2025/09/12/ben-dinucci-nfl-failure-rejection-released-cut/

Using the rejection sampling for finding tests
Markku Kuismin
https://arxiv.org/abs/2509.10325 https://arxiv.org/pdf/2509.10325

Using the rejection sampling for finding tests
A new method based on the rejection sampling for finding statistical tests is proposed. This method is conceptually intuitive, easy to implement, and applicable for arbitrary dimension. To illustrate its potential applicability, three distinct empirical examples are presented: (1) examine the differences between group means of correlated (repeated) or independent samples, (2) examine if a mean vector equals to a specific fixed vector, and (3) investigate if samples come from a specific populati…

Trump Offers All Colleges Preferential Funding Plan Rejected by MIT (Liam Knox/Bloomberg)
https://www.bloomberg.com/news/articles/2025-10-13/trump-invites-all-colleges-to-join-compact-after-mit-s-rejection
http://www.memeorandum.com/251013/p102#a251013p102

Finished "The Collected Regrets of Clover" by Mikki Brammer. Clover is a death doula, who avoids most human social connections for fear of rejection, the residual trauma of her childhood.
You make allowances for characters you can't relate to, but this book was a bowl of sugary cereal w/ extra teaspoons of sugar poured on top. Predictable & ridiculous. The characters all one-dimensional stereotypes.
Most people really liked it. I didn't.
2/5 stars ⭐ ⭐ …

The Collected Regrets of Clover
What’s the point of giving someone a beautiful death if…

An ETH-Tight FPT Algorithm for Rejection-Proof Set Packing with Applications to Kidney Exchange
Bart M. P. Jansen, Jeroen S. K. Lamme, Ruben F. A. Verhaegh
https://arxiv.org/abs/2509.11965

An ETH-Tight FPT Algorithm for Rejection-Proof Set Packing with Applications to Kidney Exchange
We study the parameterized complexity of a recently introduced multi-agent variant of the Kidney Exchange problem. Given a directed graph $G$ and integers $d$ and $k$, the standard problem asks whether $G$ contains a packing of vertex-disjoint cycles, each of length $\leq d$, covering at least $k$ vertices in total. In the multi-agent setting we consider, the vertex set is partitioned over several agents who reject a cycle packing as solution if it can be modified into an alternative packing th…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/5]:
- EMOE: A Framework for Out-of-distribution Uncertainty Based Rejection via Model-Agnostic Expansiv...
Yunni Qu, James Wellnitz, Dzung Dinh, Bhargav Vaduri, Alexander Tropsha, Junier Oliva

Improved Riemannian potato field: an Automatic Artifact Rejection Method for EEG
Davoud Hajhassani (GIPSA-VIBS), Quentin Barth\'elemy (CRNL, CRNL-COPHY), J\'er\'emie Mattout (CRNL, CRNL-COPHY), Marco Congedo (GIPSA-VIBS)
https://arxiv.org/abs/2509.09264

Improved Riemannian potato field: an Automatic Artifact Rejection Method for EEG
Electroencephalography (EEG) signal cleaning has long been a critical challenge in the research community. The presence of artifacts can significantly degrade EEG data quality, complicating analysis and potentially leading to erroneous interpretations. While various artifact rejection methods have been proposed, the gold standard remains manual visual inspection by human experts-a process that is time-consuming, subjective, and impractical for large-scale EEG studies. Existing techniques are of…

Bayesian Anomaly Detection for Ia Cosmology: Automating SALT3 Data Curation
S. A. K. Leeney, W. J. Handley, H. T. J. Bevins, E. de Lera Acedo
https://arxiv.org/abs/2509.13394 ht…

Bayesian Anomaly Detection for Ia Cosmology: Automating SALT3 Data Curation
Precision cosmology with Type Ia supernovae (SNe Ia) requires robust quality control of large, heterogeneous datasets. Current data processing often relies on manual, subjective rejection of photometric data, a practice that is not scalable for forthcoming surveys like the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). We present a Bayesian framework that automates this step by integrating anomaly detection directly into the light curve fitting process. While the framework …

Finished "Lobizona" by Romina Garber. I have extremely mixed feelings about this book. It's a powerful depiction of the fear of living as an undocumented child/teen and it has interesting things to say about rejection, belonging, and the choice between seeking to be recognized for who you are and wanting you blend in enough to be accepted as normal. However, it's also an explicit homage to Harry Potter, and while it doesn't include antisemitic tropes or glorify slavery or even have any anti-trans sentiments I can detect, to me the magical school setup felt forced and I thought it would have been a better book had it not tried to fit that mould. Also, it would have been a super interesting situation to explore trans issues, and while it's definitely fine for it not to do that, the author's praise of Rowling's work has me wondering...
There's a sequel that I think could in theory be amazing, but given the execution of the first book, I think I'll wait a bit before checking it out. By putting her main character in opposition to both ICE in the human world and the magical authorities in the other world, Garber explicitly sets the stage for a revolution standing between her protagonist and any kind of lasting peace. But I'm not confident she's capable of writing that story without relying on some kind of supernatural deus ex machina, which would be disappointing to me, since "a better world if only possible through divine intervention" is an inherently regressive message.
Overall, #OwnVoices fantasy centering an undocumented immigrant is an excellent thing, and I've certainly got a lot of privilege that surely influences my criticism. However, #OwnVoices stuff has a range of levels of craft and political stances, and it can be excellent for some reasons and mediocre for others.
On that point, if anyone reading this has suggestions for fiction books grappling with borders and the carceral state, Is be happy to hear them.
#AmReading

Distributed Coherent Beamforming at 60 GHz Enabled by Optically-Established Coherence
Drake Silbernagel, Yu Rong, Isabella Lenz, Prithvi Hemanth, Carl Morgenstern, Owen Ma, Nolan Matthews, Nader Zaki, Kyle W. Martin, John D. Elgin, Jacob Holtom, Daniel W. Bliss, Kimberly Frey
https://arxiv.org/abs/2509.13984

Distributed Coherent Beamforming at 60 GHz Enabled by Optically-Established Coherence
We implement and experimentally demonstrate a 60 GHz distributed system leveraging an optical time synchronization system that provides precise time and frequency alignment between independent elements of the distributed mesh. Utilizing such accurate coherence, we perform receive beamforming with interference rejection and transmit nulling. In these configurations, the system achieves a coherent gain over an incoherent network of N nodes, significantly improving the relevant signal power ratios…

Model-Agnostic Open-Set Air-to-Air Visual Object Detection for Reliable UAV Perception
Spyridon Loukovitis, Anastasios Arsenos, Vasileios Karampinis, Athanasios Voulodimos
https://arxiv.org/abs/2509.09297

Model-Agnostic Open-Set Air-to-Air Visual Object Detection for Reliable UAV Perception
Open-set detection is crucial for robust UAV autonomy in air-to-air object detection under real-world conditions. Traditional closed-set detectors degrade significantly under domain shifts and flight data corruption, posing risks to safety-critical applications. We propose a novel, model-agnostic open-set detection framework designed specifically for embedding-based detectors. The method explicitly handles unknown object rejection while maintaining robustness against corrupted flight data. It e…

Job Location in Listing: Remote
Rejection Email: We want someone who will come into the office 3 days week.
Me: 😐️

⏰ The new engine of voting: Out-party hostility outpaces in-party loyalty across established democracies
https://phys.org/news/2025-09-voting-party-hostility-outpaces-loyalty.html

The new engine of voting: Out-party hostility outpaces in-party loyalty across established democracies
A new study led by Professor Diego Garzia of the University of Lausanne, published in Public Opinion Quarterly, reveals a major shift in electoral motivation. In many Western democracies, voters are now more driven by opposition to their political adversaries than by support for their own side. This phenomenon marks a move away from ideological disagreement toward an emotionally charged dynamic rooted in rejection and hostility, an evolution that may ultimately weaken the very foundations of de…

“Trump has a child’s understanding of the world and is driven by ego and whatever impulses come into his weak mind. It’s causing the U.S. economy to burn as he pursues trade and economic policies that are completely unworkable and destroys U.S. leadership on the global stage. And he’s doing a lot of it to distract from the Epstein files.”
Trump discovers rejection on the world stage — because of his 'weak mind': analysis - Alternet.org
https://www.alternet.org/trump-international-leaders/

Loading non-Maxwellian Velocity Distributions in Particle Simulations
Seiji Zenitani, Shunsuke Usami, Shuichi Matsukiyo
https://arxiv.org/abs/2510.11890 https://

Loading non-Maxwellian Velocity Distributions in Particle Simulations
Numerical procedures for generating non-Maxwellian velocity distributions in particle simulations are presented. First, Monte Carlo methods for an $(r,q)$ distribution that generalizes flattop and kappa distributions are discussed. Then, two rejection methods for the regularized kappa distribution are presented, followed by a comparison in the $κ$ space. A simple recipe is proposed for the subtracted kappa distribution. Properties and numerical recipes for the ring and shell distributions with…

Control Disturbance Rejection in Neural ODEs
Erkan Bayram, Mohamed-Ali Belabbas, Tamer Ba\c{s}ar
https://arxiv.org/abs/2509.18034 https://arxiv.org/pdf/250…

Control Disturbance Rejection in Neural ODEs
In this paper, we propose an iterative training algorithm for Neural ODEs that provides models resilient to control (parameter) disturbances. The method builds on our earlier work Tuning without Forgetting-and similarly introduces training points sequentially, and updates the parameters on new data within the space of parameters that do not decrease performance on the previously learned training points-with the key difference that, inspired by the concept of flat minima, we solve a minimax prob…

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security
Yanrui Du, Fenglei Fan, Sendong Zhao, Jiawei Cao, Ting Liu, Bing Qin
https://arxiv.org/abs/2509.06807

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security
As Large Language Models (LLMs) increasingly permeate human life, their security has emerged as a critical concern, particularly their ability to maintain harmless responses to malicious instructions. Although extensive methods have improved LLMs' security, they often lead to conservative, rejection-oriented responses that compromise practical usability. This presents a key challenge: how to advance the Pareto frontier between LLMs' usability and security, rather than necessitate a trade-off be…

Dependency-Aware Execution Mechanism in Hyperledger Fabric Architecture
Sanyam Kaul, Manaswini Piduguralla, Gayathri Shreeya Patnala, Sathya Peri
https://arxiv.org/abs/2509.07425

Dependency-Aware Execution Mechanism in Hyperledger Fabric Architecture
Hyperledger Fabric is a leading permissioned blockchain framework for enterprise use, known for its modular design and privacy features. While it strongly supports configurable consensus and access control, Fabric can face challenges in achieving high transaction throughput and low rejection rates under heavy workloads. These performance limitations are often attributed to endorsement, ordering, and validation bottlenecks. Further, optimistic concurrency control and deferred validation in Fabri…

An empirical study on declined proposals: why are these proposals declined?
Masanari Kondo, Mahmoud Alfadel, Shane McIntosh, Yasutaka Kamei, Naoyasu Ubayashi
https://arxiv.org/abs/2510.06984

An empirical study on declined proposals: why are these proposals declined?
Design-level decisions in open-source software (OSS) projects are often made through structured mechanisms such as proposals, which require substantial community discussion and review. Despite their importance, the proposal process is resource-intensive and often leads to contributor frustration, especially when proposals are declined without clear feedback. Yet, the reasons behind proposal rejection remain poorly understood, limiting opportunities to streamline the process or guide contributor…

A class of unified disturbance rejection control barrier functions
Xinyang Wang, Wei Xiao, Hongwei Zhang
https://arxiv.org/abs/2508.01601 https://arxiv.org…

A class of unified disturbance rejection control barrier functions
Most existing robust control barrier functions (CBFs) can only handle matched disturbances, restricting their applications in real-world scenarios. While some recent advances extend robust CBFs to unmatched disturbances, they heavily rely on differentiability property of disturbances, and fail to accommodate non-differentiable case for high-relative-degree safety constraints. To address these limitations, this paper proposes a class of disturbance rejection CBFs (DRCBFs), including DRCBFs and a…

Opposition leader Benny Gantz proclaims long-term multiparty rejection of a Palestinian state by Israeli Jewish political society. https://www.nytimes.com/2025/09/24/opinion/israel-war-security.html?un…

Opinion | What the World Gets Wrong About Israel
There are deep political divisions and disagreements in Israel, but the nation’s core security interests are not partisan property.

I love the @… Security Advisory Database because they actually preserve the data from rejected advisories including the original information and the reason for rejection.
It’s clearly much more insightful than just having a bare ID marked as "rejected."
You can easily spot this in vulnerability-lookup:

Adaptive randomized pivoting and volume sampling
Ethan N. Epperly
https://arxiv.org/abs/2510.02513 https://arxiv.org/pdf/2510.02513

Adaptive randomized pivoting and volume sampling
Adaptive randomized pivoting (ARP) is a recently proposed and highly effective algorithm for column subset selection. This paper reinterprets the ARP algorithm by drawing connections to the volume sampling distribution and active learning algorithms for linear regression. As consequences, this paper presents new analysis for the ARP algorithm and faster implementations using rejection sampling.

Visual artist David Hendren on building community as an introvert – #creativity and #community http…

Visual artist David Hendren on building community as an introvert – The Creative Independent
Visual artist David Hendren discusses dealing with rejection, sustaining an art practice, and working with intention

Optimally revealing bits for rejection sampling
Louis-Roy Langevin, Alex Waese-Perlman
https://arxiv.org/abs/2509.24290 https://arxiv.org/pdf/2509.24290

Optimally revealing bits for rejection sampling
Rejection sampling is a popular method used to generate numbers that follow some given distribution. We study the use of this method to generate random numbers in the unit interval from increasing probability density functions. We focus on the problem of sampling from $n$ correlated random variables from a joint distribution whose marginal distributions are all increasing. We show that, in the worst case, the expected number of random bits required to accept or reject a sample grows at least li…

Rejection or Inclusion in the Emotion-Identity Dynamics of TikTok Refugees on RedNote
Mingchen Li, Wenbo Xu, Wenqing Gu, Yixuan Xie, Yao Zhou, Yunsong Dai, Cheng Tan, Pan Hui
https://arxiv.org/abs/2507.14623

Rejection or Inclusion in the Emotion-Identity Dynamics of TikTok Refugees on RedNote
This study examines cross-cultural interactions between Chinese users and self-identified "TikTok Refugees"(foreign users who migrated to RedNote after TikTok's U.S. ban). Based on a dataset of 1,862 posts and 403,054 comments, we use large language model-based sentiment classification and BERT-based topic modelling to explore how both groups engage with the TikTok refugee phenomenon. We analyse what themes foreign users express, how Chinese users respond, how stances (Pro-China, Neutral, Pro-F…

Lammy slowly emerging from a long sleep?
David Lammy 'appalled and sickened' by civilian suffering in Gaza - BBC News
https://www.bbc.co.uk/news/articles/cgjg993670jo

David Lammy 'appalled and sickened' by civilian suffering in Gaza
The UK foreign secretary also criticises Israel's rejection of an international statement calling for the war to end.

Spatial resolution studies with the BabyIAXO Micromegas prototype
A. Quintana (IRFU, CEA, Universit\'e Paris Saclay, France, Centro de Astropart\'iculas y F\'isica de Altas Energ\'ias, Universidad de Zaragoza, Zaragoza, Spain), J. Castel (Centro de Astropart\'iculas y F\'isica de Altas Energ\'ias, Universidad de Zaragoza, Zaragoza, Spain), S. Cebri\'an (Centro de Astropart\'iculas y F\'isica de Altas Energ\'ias, Universidad de Zaragoza, Zarag…

Spatial resolution studies with the BabyIAXO Micromegas prototype
The spatial resolution of the Micromegas prototype developed for the BabyIAXO experiment was evaluated using a low-energy X-ray beam at the SOLEIL synchrotron facility. BabyIAXO, currently under construction, aims to search for hypothetical solar axions. A key component of the experiment is a low-background X-ray detector with high efficiency in the 1-10 keV energy range and stringent background rejection capabilities. Achieving a spatial resolution on the order of, or better than, 1 mm is crit…

Enhancing Safety in Diabetic Retinopathy Detection: Uncertainty-Aware Deep Learning Models with Rejection Capabilities
Madhushan Ramalingam, Yaish Riaz, Priyanthi Rajamanoharan, Piyumi Dasanayaka
https://arxiv.org/abs/2510.00029

Enhancing Safety in Diabetic Retinopathy Detection: Uncertainty-Aware Deep Learning Models with Rejection Capabilities
Diabetic retinopathy (DR) is a major cause of visual impairment, and effective treatment options depend heavily on timely and accurate diagnosis. Deep learning models have demonstrated great success identifying DR from retinal images. However, relying only on predictions made by models, without any indication of model confidence, creates uncertainty and poses significant risk in clinical settings. This paper investigates an alternative in uncertainty-aware deep learning models, including a reje…

Robust Load Disturbance Rejection in PWM DC-DC Buck Converters
Simone Pirrera, Francesco Gabriele, Davide Lena, Fabio Pareschi, Diego Regruto, Gianluca Setti
https://arxiv.org/abs/2509.02102

Robust Load Disturbance Rejection in PWM DC-DC Buck Converters
This paper presents a novel approach to robust load disturbance rejection in DC-DC Buck converters. We propose a novel control scheme based on the design of two nested feedback loops. First, we design the controller in the outer loop using H infinity optimal control theory, and we show, by means of mu-analysis, that such a controller provides robust stability in the presence of uncertainty affecting the physical parameters of the circuit. Then, we introduce an inner feedback loop to improve the…

Self-Tuned Rejection Sampling within Gibbs and a Case Study in Small Area Estimation
Andrew M. Raim, Kyle M. Irimata, James A. Livsey
https://arxiv.org/abs/2509.17155 https://…

Self-Tuned Rejection Sampling within Gibbs and a Case Study in Small Area Estimation
When preparing a Gibbs sampler, some conditionals may be unfamiliar distributions without well-known variate generation routines. Rejection sampling may be used to draw from such distributions exactly; however, it can be challenging to obtain practical proposal distributions. A practical proposal is one where accepted draws are not extremely rare occurrences and which is not too computationally intensive to use repeatedly within the Gibbs sampler. Consequently, approximate methods such as Metro…

Testing Gamma/Hadron Separation for Ultra-High-Energy Cherenkov Astronomy
Sruthiranjani Ravikularaman (for the PANOSETI Collaboration), Felix Riehn, Dominik Elsaesser
https://arxiv.org/abs/2508.01354

Testing Gamma/Hadron Separation for Ultra-High-Energy Cherenkov Astronomy
Dark100 is a planned array of six telescopes, using the Panoramic Search for Extraterrestrial Intelligence (PANOSETI) telescope system. It will operate as an imaging atmospheric Cherenkov telescope array, with a telescope design and array layout optimized for accessing gamma rays with tens of TeV to PeV energies. The science goals of Dark100 include the search for ultra-heavy dark matter, observations of Galactic Pevatrons, and the search for ultra-fast optical transients. Rejection of backgrou…

Hybrid quantum-classical algorithm for near-optimal planning in POMDPs
Gilberto Cunha, Alexandra Ram\^oa, Andr\'e Sequeira, Michael de Oliveira, Lu\'is Barbosa
https://arxiv.org/abs/2507.18606 …

Hybrid quantum-classical algorithm for near-optimal planning in POMDPs
Reinforcement learning (RL) provides a principled framework for decision-making in partially observable environments, which can be modeled as Markov decision processes and compactly represented through dynamic decision Bayesian networks. Recent advances demonstrate that inference on sparse Bayesian networks can be accelerated using quantum rejection sampling combined with amplitude amplification, leading to a computational speedup in estimating acceptance probabilities.\\ Building on this resul…

Hidden Actions and Hidden Information in Peer Review: A Dynamic Solution
Raphael Mu
https://arxiv.org/abs/2510.04906 https://arxiv.org/pdf/2510.04906

Hidden Actions and Hidden Information in Peer Review: A Dynamic Solution
We develop a simple model of the scientific peer review process, in which authors of varying ability invest to produce papers of varying quality, and journals evaluate papers based on a noisy signal, choosing to accept or reject each paper. We find that the first-best outcome is the limiting case as the evaluation technology is perfected, even though author type and effort are not known to the journal. Then, we consider the case where journals allow authors to challenge an initial rejection, an…

When backgrounds become signals: neutrino interactions in xenon-based dark matter detectors
M. Atzori Corona, M. Cadeddu, N. Cargioli, F. Dordei, M. Sestu
https://arxiv.org/abs/2509.22178

When backgrounds become signals: neutrino interactions in xenon-based dark matter detectors
Direct detection dark matter experiments have proven to be compelling probes for studying low-energy neutrino interactions with both nuclei and atomic electrons, offering complementary information to accelerator and reactor-based neutrino experiments. Recently, the XENONnT and PandaX-4T collaborations reported the first evidence of coherent elastic neutrino-nucleus scattering from $^8\mathrm{B}$ solar neutrinos. Thanks to their excellent background rejection capabilities and distinctive signal …

EMORe: Motion-Robust 5D MRI Reconstruction via Expectation-Maximization-Guided Binning Correction and Outlier Rejection
Syed M. Arshad, Lee C. Potter, Yingmin Liu, Christopher Crabtree, Matthew S. Tong, Rizwan Ahmad
https://arxiv.org/abs/2507.23224

EMORe: Motion-Robust 5D MRI Reconstruction via Expectation-Maximization-Guided Binning Correction and Outlier Rejection
We propose EMORe, an adaptive reconstruction method designed to enhance motion robustness in free-running, free-breathing self-gated 5D cardiac magnetic resonance imaging (MRI). Traditional self-gating-based motion binning for 5D MRI often results in residual motion artifacts due to inaccuracies in cardiac and respiratory signal extraction and sporadic bulk motion, compromising clinical utility. EMORe addresses these issues by integrating adaptive inter-bin correction and explicit outlier rejec…

Cloud Detection using Night Sky Background Light at the Pierre Auger Observatory
Fedor Tairli, for the Pierre Auger Collaboration
https://arxiv.org/abs/2509.06343 https://

Cloud Detection using Night Sky Background Light at the Pierre Auger Observatory
Rejection of cloud-contaminated data is a complex and important process at the Pierre Auger Observatory, one which combines information from several sources, including IR cameras, lidars, and satellite imaging. With the deteriorating quality of the IR cameras and challenges in using other sources, we propose a new method. We use continuous detector monitoring measurements to build a large database of night sky background fluxes for each pixel across 27 telescopes. Using this database, we genera…

Tenure Under Pressure: Simulating the Disruptive Effects of AI on Academic Publishing
Shan Jiang
https://arxiv.org/abs/2509.16925 https://arxiv.org/pdf/250…

Tenure Under Pressure: Simulating the Disruptive Effects of AI on Academic Publishing
Generative artificial intelligence (AI) has begun to reshape academic publishing by enabling the rapid production of submission-ready manuscripts. While such tools promise to enhance productivity, they also raise concerns about overwhelming journal systems that have fixed acceptance capacities. This paper uses simulation modeling to investigate how AI-driven surges in submissions may affect desk rejection rates, review cycles, and faculty publication portfolios, with a focus on business school …

Challenges in Scaling ScAlN Bulk Acoustic Wave Filters toward Ku-Band Frequencies
Sinwoo Cho, Byeongjin Kim, Lezli Matto, Omar Barrera, Pietro Simeoni, Yinan Wang, Michael Liao, Tzu-Hsuan Hsu, Jack Kramer, Matteo Rinaldi, Mark S. Goorsky, Ruochen Lu
https://arxiv.org/abs/2509.03679

Challenges in Scaling ScAlN Bulk Acoustic Wave Filters toward Ku-Band Frequencies
This paper reports an 11.7 GHz compact filter based on Scandium Aluminum Nitride (ScAlN) Film Bulk Acoustic Resonators (FBARs) and provides a detailed analysis of the fundamental challenges that limit performance when scaling to higher frequencies. A 50 Ω ladder filter based on single-layer thin film ScAlN with Platinum (Pt) electrodes was demonstrated at 11.7 GHz with a 3 dB fractional bandwidth (FBW) of 4.0% and an out of band rejection greater than 23.1 dB. However, the filter exhibits a mo…

Variational Reasoning for Language Models
Xiangxin Zhou, Zichen Liu, Haonan Wang, Chao Du, Min Lin, Chongxuan Li, Liang Wang, Tianyu Pang
https://arxiv.org/abs/2509.22637 https:…

Variational Reasoning for Language Models
We introduce a variational reasoning framework for language models that treats thinking traces as latent variables and optimizes them through variational inference. Starting from the evidence lower bound (ELBO), we extend it to a multi-trace objective for tighter bounds and propose a forward-KL formulation that stabilizes the training of the variational posterior. We further show that rejection sampling finetuning and binary-reward RL, including GRPO, can be interpreted as local forward-KL obje…

Predictive Quality Assessment for Mobile Secure Graphics
Cas Steigstra, Sergey Milyaev, Shaodi You
https://arxiv.org/abs/2509.20028 https://arxiv.org/pdf/2…

Predictive Quality Assessment for Mobile Secure Graphics
The reliability of secure graphic verification, a key anti-counterfeiting tool, is undermined by poor image acquisition on smartphones. Uncontrolled user captures of these high-entropy patterns cause high false rejection rates, creating a significant 'reliability gap'. To bridge this gap, we depart from traditional perceptual IQA and introduce a framework that predictively estimates a frame's utility for the downstream verification task. We propose a lightweight model to predict a quality score…

DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
Shae McFadden, Myles Foley, Mario D'Onghia, Chris Hicks, Vasilios Mavroudis, Nicola Paoletti, Fabio Pierazzi
https://arxiv.org/abs/2508.18839

DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
Malware detection in real-world settings must deal with evolving threats, limited labeling budgets, and uncertain predictions. Traditional classifiers, without additional mechanisms, struggle to maintain performance under concept drift in malware domains, as their supervised learning formulation cannot optimize when to defer decisions to manual labeling and adaptation. Modern malware detection pipelines combine classifiers with monthly active learning (AL) and rejection mechanisms to mitigate t…

Modeling Scintillation Photon Transport and Reconstruction Algorithms for the Time-of-Flight Detector in the T2K Neutrino Experiment
C. Alt, A. Blanchet, S. Bordoni, P. Collard, T. H. Bui, M. H. Bui, G. Ha, C. Jes\'us-Valls, V. S. Kasturi, A. Klustov\'a, A. Korzenev, T. A. Le, T. Lux, A. D. Nguyen, D. T. Nguyen, H. Nguyen, S. Samani, F. S\'anchez, M. Ta, T. Tha\'iduc, E. Villa

Modeling Scintillation Photon Transport and Reconstruction Algorithms for the Time-of-Flight Detector in the T2K Neutrino Experiment
The T2K ND280 upgrade aims to reduce the systematic uncertainty of the CP-violating phase, $δ_{CP}$, to reject non-CP violation hypothesis at $3σ$ confidence level. A crucial component of the ND280 upgrade, alongside the Super Fine Grained Detector (SuperFGD) and two High-Angle Time Projection Chambers (TPCs), is the Time-of-Flight (ToF) detector, which significantly enhances background rejection and particle identification capabilities. The ToF detector features six modules in a cube configu…

Leveraging the group structure of hypotheses for more powerful multiple testing with FDR control for the filtered rejection set
Marina Bogomolov, Shinjini Nandi
https://arxiv.org/abs/2509.15444

Leveraging the group structure of hypotheses for more powerful multiple testing with FDR control for the filtered rejection set
Modern biological studies often involve testing many hypotheses organized in a group or a hierarchical structure, such as a directed acyclic graph (DAG). In these studies, researchers often wish to control the false discovery rate (FDR) after filtering the discoveries to obtain interpretable results. For addressing this goal, Katsevich, Sabatti, and Bogomolov (2023, Journal of the American Statistical Association, 118(541), 165-176) developed a general method, Focused BH, that guarantees FDR co…

$H_\infty$ Performance Analysis for Almost Periodic Piecewise Linear Systems with Application to Roll-to-Roll Manufacturing Control
Christopher Martin, Edward Kim, Enrique Velasquez, Wei Li, Dongmei Chen
https://arxiv.org/abs/2508.21199

$H_\infty$ Performance Analysis for Almost Periodic Piecewise Linear Systems with Application to Roll-to-Roll Manufacturing Control
An almost periodic piecewise linear system (APPLS) is a type of piecewise linear system where the system cyclically switches between different modes, each with an uncertain but bounded dwell-time. Process regulation, especially disturbance rejection, is critical to the performance of these advanced systems. However, a method to guarantee disturbance rejection has not been developed. The objective of this study is to develop an $H_\infty$ performance analysis method for APPLSs, building on which…

The Surprising Effectiveness of Linear Models for Whole-Body Model-Predictive Control
Arun L. Bishop, Juan Alvarez-Padilla, Sam Schoedel, Ibrahima Sory Sow, Juee Chandrachud, Sheitej Sharma, Will Kraus, Beomyeong Park, Robert J. Griffin, John M. Dolan, Zachary Manchester
https://arxiv.org/abs/2509.17884

The Surprising Effectiveness of Linear Models for Whole-Body Model-Predictive Control
When do locomotion controllers require reasoning about nonlinearities? In this work, we show that a whole-body model-predictive controller using a simple linear time-invariant approximation of the whole-body dynamics is able to execute basic locomotion tasks on complex legged robots. The formulation requires no online nonlinear dynamics evaluations or matrix inversions. We demonstrate walking, disturbance rejection, and even navigation to a goal position without a separate footstep planner on a…

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…

The Pareto Frontier of Resilient Jet Tagging
Rikab Gambhir, Matt LeBlanc, Yuanchen Zhou
https://arxiv.org/abs/2509.19431 https://arxiv.org/pdf/2509.19431…

The Pareto Frontier of Resilient Jet Tagging
Classifying hadronic jets using their constituents' kinematic information is a critical task in modern high-energy collider physics. Often, classifiers are designed by targeting the best performance using metrics such as accuracy, AUC, or rejection rates. However, the use of a single metric can lead to the use of architectures that are more model-dependent than competitive alternatives, leading to potential uncertainty and bias in analysis. We explore such trade-offs and demonstrate the consequ…

Filtering for Creativity: Adaptive Prompting for Multilingual Riddle Generation in LLMs
Duy Le, Kent Ziti, Evan Girard-Sun, Sean O'Brien, Vasu Sharma, Kevin Zhu
https://arxiv.org/abs/2508.18709

Filtering for Creativity: Adaptive Prompting for Multilingual Riddle Generation in LLMs
Multilingual riddle generation challenges large language models (LLMs) to balance cultural fluency with creative abstraction. Standard prompting strategies -- zero-shot, few-shot, chain-of-thought -- tend to reuse memorized riddles or perform shallow paraphrasing. We introduce Adaptive Originality Filtering (AOF), a prompting framework that filters redundant generations using cosine-based similarity rejection, while enforcing lexical novelty and cross-lingual fidelity. Evaluated across three LL…

A Lightweight Face Quality Assessment Framework to Improve Face Verification Performance in Real-Time Screening Applications
Ahmed Aman Ibrahim, Hamad Mansour Alawar, Abdulnasser Abbas Zehi, Ahmed Mohammad Alkendi, Bilal Shafi Ashfaq Ahmed Mirza, Shan Ullah, Ismail Lujain Jaleel, Hassan Ugail
https://arxiv.org/abs/2507.15961

A Lightweight Face Quality Assessment Framework to Improve Face Verification Performance in Real-Time Screening Applications
Face image quality plays a critical role in determining the accuracy and reliability of face verification systems, particularly in real-time screening applications such as surveillance, identity verification, and access control. Low-quality face images, often caused by factors such as motion blur, poor lighting conditions, occlusions, and extreme pose variations, significantly degrade the performance of face recognition models, leading to higher false rejection and false acceptance rates. In th…

Explainable AI-Enhanced Supervisory Control for Robust Multi-Agent Robotic Systems
Reza Pirayeshshirazinezhad, Nima Fathi
https://arxiv.org/abs/2509.15491 https://

Explainable AI-Enhanced Supervisory Control for Robust Multi-Agent Robotic Systems
We present an explainable AI-enhanced supervisory control framework for multi-agent robotics that combines (i) a timed-automata supervisor for safe, auditable mode switching, (ii) robust continuous control (Lyapunov-based controller for large-angle maneuver; sliding-mode controller (SMC) with boundary layers for precision and disturbance rejection), and (iii) an explainable predictor that maps mission context to gains and expected performance (energy, error). Monte Carlo-driven optimization pro…

A Wide-Input 0.25 um BCD LDO with Dual-Stage Amplifier and Active Ripple Cancellation for High PSRR and Fast Transient Response
Yi Zhang, Zhuolong Chen, Zhenghao Xu, Yujin He
https://arxiv.org/abs/2507.20522

A Wide-Input 0.25 um BCD LDO with Dual-Stage Amplifier and Active Ripple Cancellation for High PSRR and Fast Transient Response
Demand for on-chip low-dropout regulators (LDOs) with both high power-supply rejection ratio (PSRR) and fast transient response is growing as system-on-chip (SoC) integration increases. However, conventional LDO architectures face difficulty achieving these performance metrics simultaneously over wide input voltage ranges. This paper presents a wide-input linear regulator implemented in 0.25 um BCD technology that attains high PSRR and swift load-transient performance while maintaining low quie…

A Bayesian model-free dose-finding approach in Phase II clinical trials with the flexibility of historical borrowing
Linxi Han, Qiqi Deng, Feng Yu, Zhangyi He
https://arxiv.org/abs/2509.23777

A Bayesian model-free dose-finding approach in Phase II clinical trials with the flexibility of historical borrowing
Accurate dose selection in Phase II trials is critical to the success of subsequent Phase III trials, but suboptimal choices remain a leading cause of trial failure and regulatory rejection. Although MCP-Mod is widely adopted and endorsed by regulatory agencies, it requires prespecification of candidate models and is highly sensitive to model misspecification. To address these challenges, we introduce MAP-curvature, a general model-free framework for dose-response modelling that penalises the t…

Robustness Enhancement for Multi-Quadrotor Centralized Transportation System via Online Tuning and Learning
Tianhua Gao, Kohji Tomita, Akiya Kamimura
https://arxiv.org/abs/2509.01952

Robustness Enhancement for Multi-Quadrotor Centralized Transportation System via Online Tuning and Learning
This paper introduces an adaptive-neuro geometric control for a centralized multi-quadrotor cooperative transportation system, which enhances both adaptivity and disturbance rejection. Our strategy is to coactively tune the model parameters and learn the external disturbances in real-time. To realize this, we augmented the existing geometric control with multiple neural networks and adaptive laws, where the estimated model parameters and the weights of the neural networks are simultaneously tun…

Finite-Time Stabilization of a Class of Nonlinear Systems in Hilbert Space
Kamal Fenza, Moussa Labbadi, Mohamed Ouzahra
https://arxiv.org/abs/2509.02212 https://

Finite-Time Stabilization of a Class of Nonlinear Systems in Hilbert Space
This paper deals with the finite-time stabilization of a class of nonlinear infinite-dimensional systems. First, we consider a bounded matched perturbation in its linear form. It is shown that by using a set-valued function, both the convergence objective (finite-time) and the rejection of perturbations are achieved. Second, we consider a class of nonlinear systems and design a feedback control that ensures the closed-loop system is finite-time stable. All proofs presented in this paper regardi…