Tootfinder

Efficient Importance Sampling for Wrong Exit Probabilities over Combinatorially Many Rare Regions
Yanglei Song, Georgios Fellouris
https://arxiv.org/abs/2509.14596 https://

Efficient Importance Sampling for Wrong Exit Probabilities over Combinatorially Many Rare Regions
We consider importance sampling for estimating the probability that a light-tailed $d$-dimensional random walk exits through one of many disjoint rare-event regions before reaching an anticipated target. This problem arises in sequential multiple hypothesis testing, where the number of such regions may grow combinatorially and in some cases exponentially with the dimension. While mixtures over all associated exponential tilts are asymptotically efficient, they become computationally infeasible …

All political violence is bad; violence is never a good answer.
From report AG and potus want to hide: "…the number of far-right attacks continues to outpace all other types of terrorism and domestic violent extremism."
https://www.scribd.com/document/9186184…

What NIJ Research Tells Us About Domestic Terrorism | PDF | Extremism | Crimes
NIJ-funded research has enhanced understanding of domestic terrorism, particularly the rise of far-right extremist violence in the U.S., which has outpaced other forms of terrorism. The studies reveal that radicalization processes vary by group and crime type, and highlight the importance of community-based prevention strategies. Key findings include the diversity of extremist beliefs and behaviors, the role of military experience in radicalization, and the need for targeted interventions to pr…

Importance of Shot Noise in the Search for an Isotropic Stochastic Gravitational-Wave Background with Next Generation Detectors
Haowen Zhong, Vuk Mandic
https://arxiv.org/abs/2509.15014

Importance of Shot Noise in the Search for an Isotropic Stochastic Gravitational-Wave Background with Next Generation Detectors
We investigate the impact of shot noise on the stochastic gravitational wave background generated by binary neutron star mergers, and confirm that the overall background can be significantly influenced by relatively few neighboring, loud events. To mitigate the shot noise, we propose a procedure to remove nearby events by notching them out in the time-frequency domain. Additionally, we quantify the cosmic/sample variance of the resulting background after notching, and we study the deviation bet…

Jessie Price and David Pocock in conversation about the critical importance of community Independents on the crossbench in the context of a Coalition shambles and Labor majority - sharpening the role of the crossbench in holding the government to account and pushing for stronger action.
#JessiePrice #DavidPocock

Critical Importance of Grain Boundaries to the Conductivity of Polycrystalline Molecular Crystals
Shujit Chandra Paul, William A. Goddard III, Michael J. Zdilla, Prabhat Prakash, Stephanie L. Wunder
https://arxiv.org/abs/2508.12172

Critical Importance of Grain Boundaries to the Conductivity of Polycrystalline Molecular Crystals
Soft-solid molecular crystals consist of crystalline grains and fluid grain boundaries (GB) that enhance the grain binding and transport of Li+ ions between the grains. The total ionic conductivity consists of ion migration in both the grains and GBs. To unravel these contributions in adiponitrile (Adpn)-LiPF6 molecular crystals, the GB volume fraction was varied by changing the size of the crystals and the adiponitrile/LiPF6 molar ratio. Molecular dynamic (MD) simulations indicate that ion mot…

Our Congress is too cowardly to cancel Trumps contract.
But El Cheeto's show is loosing money, at lot more than a measly $40million/year. And viewers and voters are tuning away in droves.
The 2026 mid term elections are only a bit more than a year away. I am surprised that the obvious sole issues of importance are not being raised by aspiring candidates:
- No funding, i.e. zero dollars, zero - appropriated. Better a non functioning government than one that is activel…

exposure, highlighting importance of #ConsumerRights and #RightToRepair advocacy
https…

FRIT: Using Causal Importance to Improve Chain-of-Thought Faithfulness
Anand Swaroop, Akshat Nallani, Saksham Uboweja, Adiliia Uzdenova, Michael Nguyen, Kevin Zhu, Sunishchal Dev, Ashwinee Panda, Vasu Sharma, Maheep Chaudhary
https://arxiv.org/abs/2509.13334

FRIT: Using Causal Importance to Improve Chain-of-Thought Faithfulness
Chain-of-thought (CoT) reasoning has emerged as a powerful tool for improving large language model performance on complex tasks, but recent work shows that reasoning steps often fail to causally influence the final answer, creating brittle and untrustworthy outputs. Prior approaches focus primarily on measuring faithfulness, while methods for systematically improving it remain limited. We introduce Faithful Reasoning via Intervention Training (FRIT), a scalable alignment method that trains mode…

Importance-Aware Robust Semantic Transmission for LEO Satellite-Ground Communication
Hui Cao, Rui Meng, Xiaodong Xu, Shujun Han, Ping Zhang
https://arxiv.org/abs/2508.11457 http…

Importance-Aware Robust Semantic Transmission for LEO Satellite-Ground Communication
Satellite-ground semantic communication is anticipated to serve a critical role in the forthcoming 6G era. Nonetheless, task-oriented data transmission in such systems remains a formidable challenge, primarily due to the dynamic nature of signal-to-noise ratio (SNR) fluctuations and the stringent bandwidth limitations inherent to low Earth orbit (LEO) satellite channels. In response to these constraints, we propose an importance-aware robust semantic transmission (IRST) framework, specifically …

Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation
Xiaoyu Yue, Zidong Wang, Yuqing Wang, Wenlong Zhang, Xihui Liu, Wanli Ouyang, Lei Bai, Luping Zhou
https://arxiv.org/abs/2509.15185

Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation
Recent studies have demonstrated the importance of high-quality visual representations in image generation and have highlighted the limitations of generative models in image understanding. As a generative paradigm originally designed for natural language, autoregressive models face similar challenges. In this work, we present the first systematic investigation into the mechanisms of applying the next-token prediction paradigm to the visual domain. We identify three key properties that hinder th…

Finite Axiomatizability by Disjunctive Existential Rules
Marco Calautti, Marco Console, Andreas Pieris
https://arxiv.org/abs/2508.11946 https://arxiv.org/p…

Finite Axiomatizability by Disjunctive Existential Rules
Rule-based languages lie at the core of several areas of central importance to databases and artificial intelligence such as deductive databases and knowledge representation and reasoning. Disjunctive existential rules (a.k.a. disjunctive tuple-generating dependencies in the database literature) form such a prominent rule-based language. The goal of this work is to pinpoint the expressive power of disjunctive existential rules in terms of insightful model-theoretic properties. More precisely, g…

Next Woman Up: Emma Kaptein, Director of Social Strategy for the New York Giants https://www.nfl.com/news/next-woman-up-emma-kaptein-director-of-social-strategy-for-the-new-york-giants

Hierarchical Importance Sampling for Estimating Occupation Time for SDE Solutions
Eya Ben Amar, Nadhir Ben Rached, Raul Tempone
https://arxiv.org/abs/2509.13950 https://

Hierarchical Importance Sampling for Estimating Occupation Time for SDE Solutions
This study considers the estimation of the complementary cumulative distribution function of the occupation time (i.e., the time spent below a threshold) for a process governed by a stochastic differential equation. The focus is on the right tail, where the underlying event becomes rare, and using variance reduction techniques is essential to obtain computationally efficient estimates. Building on recent developments that relate importance sampling (IS) to stochastic optimal control, this work …

PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
Tian Sun, Yuqi Chen, Weiwei Sun
https://arxiv.org/abs/2508.13773 https:…

PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
Long-term time series forecasting (LTSF) is a fundamental task with wide-ranging applications. Although Transformer-based models have made significant breakthroughs in forecasting, their effectiveness for time series forecasting remains debatable. In this paper, we revisit the significance of self-attention and propose a simple yet effective mechanism, Periodic-Nested Group Attention, namely PENGUIN. Our approach highlights the importance of explicitly modeling periodic patterns and incorporati…

Value-Guided KV Compression for LLMs via Approximated CUR Decomposition
Ayan Sengupta, Siddhant Chaudhary, Tanmoy Chakraborty
https://arxiv.org/abs/2509.15038 https://

Value-Guided KV Compression for LLMs via Approximated CUR Decomposition
Key-value (KV) cache compression has emerged as a critical technique for reducing the memory and latency overhead of autoregressive language models during inference. Prior approaches predominantly rely on query-key attention scores to rank and evict cached tokens, assuming that attention intensity correlates with semantic importance. However, this heuristic overlooks the contribution of value vectors, which directly influence the attention output. In this paper, we propose CurDKV, a novel, valu…

Exploring Nonreciprocal Noise Transfer under Onsager-Casimir Symmetry in Synthetic-Field Optomechanics
Beyza S\"utl\"uo\u{g}lu Ege, \c{S}ahin K. \"Ozdemir, Ceyhun Bulutay
https://arxiv.org/abs/2508.13902

Exploring Nonreciprocal Noise Transfer under Onsager-Casimir Symmetry in Synthetic-Field Optomechanics
An optomechanical system of fundamental importance consists of two intercoupled mechanical resonators, which are radiation-pressure coupled individually to a photonic cavity. This closed-loop and overall lossy configuration possesses two exceptional points (EPs) and offers the realization of synthetic magnetism, controlled by the loop phase. To elucidate the intricate role of loop phase and EPs in this setting, we analyze the noise power spectral density profiles of internal as well as output f…

ExT: Towards Scalable Autonomous Excavation via Large-Scale Multi-Task Pretraining and Fine-Tuning
Yifan Zhai, Lorenzo Terenzi, Patrick Frey, Diego Garcia Soto, Pascal Egli, Marco Hutter
https://arxiv.org/abs/2509.14992

ExT: Towards Scalable Autonomous Excavation via Large-Scale Multi-Task Pretraining and Fine-Tuning
Scaling up the deployment of autonomous excavators is of great economic and societal importance. Yet it remains a challenging problem, as effective systems must robustly handle unseen worksite conditions and new hardware configurations. Current state-of-the-art approaches rely on highly engineered, task-specific controllers, which require extensive manual tuning for each new scenario. In contrast, recent advances in large-scale pretrained models have shown remarkable adaptability across tasks a…

Nice article about the importance of connecting data, harmony without orchestration of millions of small flexible energy actions, inspired by a post of mine.
https://nemlog.substack.com/p/sustainability-will-not-be-commanded

Sustainability Will Not Be Commanded; It Will Be Coded
How smarter signals, flexible habits, and open systems could turn energy abundance into everyday opportunity

A Convergent Primal-Dual Algorithm for Computing Rate-Distortion-Perception Functions
Chunhui Chen, Linyi Chen, Xueyan Niu, Hao Wu
https://arxiv.org/abs/2508.13486 https://

A Convergent Primal-Dual Algorithm for Computing Rate-Distortion-Perception Functions
Recent advances in Rate-Distortion-Perception (RDP) theory highlight the importance of balancing compression level, reconstruction quality, and perceptual fidelity. While previous work has explored numerical approaches to approximate the information RDP function, the lack of theoretical guarantees remains a major limitation, especially in the presence of complex perceptual constraints that introduce non-convexity and computational intractability. Inspired by our previous constrained Blahut-Arim…

Variable Selection Using Relative Importance Rankings
Tien-En Chang, Argon Chen
https://arxiv.org/abs/2509.10853 https://arxiv.org/pdf/2509.10853

Variable Selection Using Relative Importance Rankings
Although conceptually related, variable selection and relative importance (RI) analysis have been treated quite differently in the literature. While RI is typically used for post-hoc model explanation, this paper explores its potential for variable ranking and filter-based selection before model creation. Specifically, we anticipate strong performance from the RI measures because they incorporate both direct and combined effects of predictors, addressing a key limitation of marginal correlation…

A Systematic Review of FAIR-compliant Big Data Software Reference Architectures
Jo\~ao Pedro de Carvalho Castro, Maria J\'ulia Soares De Grandi, Cristina Dutra de Aguiar
https://arxiv.org/abs/2509.14370

A Systematic Review of FAIR-compliant Big Data Software Reference Architectures
To meet the standards of the Open Science movement, the FAIR Principles emphasize the importance of making scientific data Findable, Accessible, Interoperable, and Reusable. Yet, creating a repository that adheres to these principles presents significant challenges. Managing large volumes of diverse research data and metadata, often generated rapidly, requires a precise approach. This necessity has led to the development of Software Reference Architectures (SRAs) to guide the implementation pro…

Deadline-Aware Bandwidth Allocation for Semantic Generative Communication with Diffusion Models
Jinhyuk Choi, Jihong Park, Seungeun Oh, Seong-Lyun Kim
https://arxiv.org/abs/2508.12701

Deadline-Aware Bandwidth Allocation for Semantic Generative Communication with Diffusion Models
The importance of Radio Access Network (RAN) in support Artificial Intelligence (AI) application services has grown significantly, underscoring the need for an integrated approach that considers not only network efficiency but also AI performance. In this paper we focus on a semantic generative communication (SGC) framework for image inpainting application. Specifically, the transmitter sends semantic information, i.e., semantic masks and textual descriptions, while the receiver utilizes a cond…

The Broadband View of the Bare Seyfert PG 1426 015: Relativistic Reflection, the Soft Excess and the Importance of Oxygen
D. J. Walton, A. Madathil-Pottayil, P. Kosec, J. Jiang, J. Garcia, A. C. Fabian, C. Pinto, D. J. K. Buisson, M. L. Parker, W. N. Alston, C. S. Reynolds
https://arxiv.org/abs/2509.13411

The Broadband View of the Bare Seyfert PG 1426+015: Relativistic Reflection, the Soft Excess and the Importance of Oxygen
We present results from a deep, coordinated $XMM$-$Newton$ + $NuSTAR$ observation of the type 1 Seyfert PG 1426+015, a source of particular interest as the most massive reverberation-mapped black hole to date ($\log [M_{\rm{BH}}/M_{\odot}]$ = $9.01^{+0.11}_{-0.16}$). The high-resolution RGS data confirm the 'bare' nature of the source, showing no evidence for absorption beyond the Galactic column, while the broadband spectrum unambiguously reveals the presence of relativistic reflection from th…

How Bad Is Forming Your Own Multidimensional Opinion?
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Mahdi JafariRaviz, Danny Mittal, Alipasha Montaseri
https://arxiv.org/abs/2509.14411

How Bad Is Forming Your Own Multidimensional Opinion?
Understanding the formation of opinions on interconnected topics within social networks is of significant importance. It offers insights into collective behavior and decision-making, with applications in Graph Neural Networks. Existing models propose that individuals form opinions based on a weighted average of their peers' opinions and their own beliefs. This averaging process, viewed as a best-response game, can be seen as an individual minimizing disagreements with peers, defined by a quadra…

Turn up the light: Radiative efficiency of protostars at birth
Asmita Bhandare, Adnan Ali Ahmad, Beno\^it Commer\c{c}on
https://arxiv.org/abs/2509.15009 https://

Turn up the light: Radiative efficiency of protostars at birth
Early stages of stellar birth comprise of a two-step process involving the formation of two hydrostatic cores. The second step of gravitational collapse sets the radiative efficiency and accretion rate of the young protostar. These two parameters, of prime importance for protostellar evolution, dictate the luminosities and thus play a key role in deciphering the current discrepancy between observational surveys and theoretical models. In this letter, we provide quantitative estimates on the evo…

Fast Percolation Centrality Approximation with Importance Sampling
Antonio Cruciani, Leonardo Pellegrina
https://arxiv.org/abs/2509.11454 https://arxiv.org…

Fast Percolation Centrality Approximation with Importance Sampling
In this work we present PercIS, an algorithm based on Importance Sampling to approximate the percolation centrality of all the nodes of a graph. Percolation centrality is a generalization of betweenness centrality to attributed graphs, and is a useful measure to quantify the importance of the vertices in a contagious process or to diffuse information. However, it is impractical to compute it exactly on modern-sized networks. First, we highlight key limitations of state-of-the-art sampling-bas…

We're wandering down this afternoon to the Jessie Price Keep Bean on the map: Reconnecting Our Supporter Community!
Enjoy a democracy sausage BBQ.
Jessie and David Pocock will be in conversation about the critical importance of community Independents on the crossbench in the context of a Coalition shambles and Labor majority - sharpening the role of the crossbench in holding the government to account and pushing for stronger action.
Tuggeranong Park Stage, 2-4pm and a…

False Data-Injection Attack Detection in Cyber-Physical Systems: A Wasserstein Distributionally Robust Reachability Optimization Approach
Yulin Feng, Dapeng Lan, Chao Shang
https://arxiv.org/abs/2508.12402

False Data-Injection Attack Detection in Cyber-Physical Systems: A Wasserstein Distributionally Robust Reachability Optimization Approach
Cyber-physical system (CPS) is the foundational backbone of modern critical infrastructures, so ensuring its security and resilience against cyber-attacks is of pivotal importance. This paper addresses the challenge of designing anomaly detectors for CPS under false-data injection (FDI) attacks and stochastic disturbances governed by unknown probability distribution. By using the Wasserstein ambiguity set, a prevalent data-driven tool in distributionally robust optimization (DRO), we first prop…

Singer-songwriter Nemahsis on the importance of being uncompromising – The Creative Independent https://thecreativeindependent.com/peo

Singer-songwriter Nemahsis on the importance of being uncompromising – The Creative Independent
Singer-songwriter Nemahsis discusses breaking through despite hardships, freedom of expression, and the power of building a genuine community online

From Sea to System: Exploring User-Centered Explainable AI for Maritime Decision Support
Doreen Jirak, Pieter Maes, Armeen Saroukanoff, Dirk van Rooy
https://arxiv.org/abs/2509.15084

From Sea to System: Exploring User-Centered Explainable AI for Maritime Decision Support
As autonomous technologies increasingly shape maritime operations, understanding why an AI system makes a decision becomes as crucial as what it decides. In complex and dynamic maritime environments, trust in AI depends not only on performance but also on transparency and interpretability. This paper highlights the importance of Explainable AI (XAI) as a foundation for effective human-machine teaming in the maritime domain, where informed oversight and shared understanding are essential. To sup…

Exploring new construction schemes for extended-hierarchy CI (ehCI) wavefunctions
Rugwed A. Lokhande, Carlos E. V. de Moura, Pratiksha B. Gaikwad, Ram\'on Alain Miranda-Quintana
https://arxiv.org/abs/2509.15190

Exploring new construction schemes for extended-hierarchy CI (ehCI) wavefunctions
Following the work of Loos et al. on hierarchy CI (hCI) we propose an extended way of partitioning the Hilbert space by combining the excitation and the seniority sectors in a more general way. We define the hierarchy parameter, h, involving two "weights" (alphas), measuring the importance of excitation (e) and seniority (s) contributions to the wavefunction according to: h = α1.e + α2.s. We test these new CI methods on the dissociation of chemical systems and analyze them based on the import…

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends
Zhenhua Xu, Xubin Yue, Zhebo Wang, Qichen Liu, Xixiang Zhao, Jingxuan Zhang, Wenjun Zeng, Wengpeng Xing, Dezhang Kong, Changting Lin, Meng Han
https://arxiv.org/abs/2508.11548

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends
Copyright protection for large language models is of critical importance, given their substantial development costs, proprietary value, and potential for misuse. Existing surveys have predominantly focused on techniques for tracing LLM-generated content-namely, text watermarking-while a systematic exploration of methods for protecting the models themselves (i.e., model watermarking and model fingerprinting) remains absent. Moreover, the relationships and distinctions among text watermarking, mo…

Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect
Jon Donnelly, Srikar Katta, Emanuele Borgonovo, Cynthia Rudin
https://arxiv.org/abs/2510.12734

Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect
Variable importance (VI) methods are often used for hypothesis generation, feature selection, and scientific validation. In the standard VI pipeline, an analyst estimates VI for a single predictive model with only the observed features. However, the importance of a feature depends heavily on which other variables are included in the model, and essential variables are often omitted from observational datasets. Moreover, the VI estimated for one model is often not the same as the VI estimated for…

Dak Prescott on Rams joint practice, importance of preseason reps https://www.dallascowboys.com/news/dak-prescott-on-rams-joint-practice-importance-of-preseason-reps

Revisiting thermodynamics at the outskirts of the Perseus cluster with Suzaku: importance of modeling the Hot Galactic gas
Kyoko Matsushita, Hayato Sugiyama, Masaki Ueda, Nobuhiro Okabe, Kotaro Fukushima, Shogo B. Kobayashi, Noriko Y. Yamasaki, Kosuke Sato
https://arxiv.org/abs/2509.12624

Revisiting thermodynamics at the outskirts of the Perseus cluster with Suzaku: importance of modeling the Hot Galactic gas
The thermodynamic properties of the intracluster medium (ICM) at the outskirts of galaxy clusters provide valuable insights into the growth of the dark matter halo and the heating of the ICM. Considering the results of the soft X-ray background study of non-cluster Suzaku fields, we revisit 65 Suzaku pointing observations of the Perseus cluster in eight azimuthal directions beyond 1 Mpc (0.8 $r_{500}$). A possible foreground component, whose spectrum is modeled as a 1 keV collisional ionization…

LKFMixer: Exploring Large Kernel Feature For Efficient Image Super-Resolution
Yinggan Tang, Quanwei Hu
https://arxiv.org/abs/2508.11391 https://arxiv.org/p…

LKFMixer: Exploring Large Kernel Feature For Efficient Image Super-Resolution
The success of self-attention (SA) in Transformer demonstrates the importance of non-local information to image super-resolution (SR), but the huge computing power required makes it difficult to implement lightweight models. To solve this problem, we propose a pure convolutional neural network (CNN) model, LKFMixer, which utilizes large convolutional kernel to simulate the ability of self-attention to capture non-local features. Specifically, we increase the kernel size to 31 to obtain the larg…

The fundamental physical importance of generic off-diagonal solutions and Grigori Perelman entropy in the Einstein gravity theory
Sergiu I. Vacaru, El\c{s}en V. Veliev
https://arxiv.org/abs/2508.10939 …

The fundamental physical importance of generic off-diagonal solutions and Grigori Perelman entropy in the Einstein gravity theory
The gravitational field equations in general relativity (GR) consist of a sophisticated system of nonlinear partial differential equations. Solving such equations in some generic off-diagonal forms is usually a hard analytic or numeric task. Physically important solutions in GR were constructed using a diagonal ansatz for metrics with a maximum of 4 independent coefficients. The Einstein equations can be solved in exact or parametric forms determined by some integration constants for correspond…

Crosslisted article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[1/1]:
- The fundamental physical importance of generic off-diagonal solutions and Grigori Perelman entrop...
Sergiu I. Vacaru, El\c{s}en V. Veliev

CLMIR: A Textual Dataset for Rumor Identification and Marking
Bin Ma, Yifei Zhang, Yongjin Xian, Qi Li, Linna Zhou, Gongxun Miao
https://arxiv.org/abs/2508.11138 https://…

CLMIR: A Textual Dataset for Rumor Identification and Marking
With the rise of social media, rumor detection has drawn increasing attention. Although numerous methods have been proposed with the development of rumor classification datasets, they focus on identifying whether a post is a rumor, lacking the ability to mark the specific rumor content. This limitation largely stems from the lack of fine-grained marks in existing datasets. Constructing a rumor dataset with rumor content information marking is of great importance for fine-grained rumor identific…

The Vast Importance of Raiders' Clash with Chargers https://www.si.com/nfl/raiders/las-vegas-geno-smith-los-angeles-chargers-jim-harbaugh-derwin-james

A mathematical model of HPAI transmission between dairy cattle and wild birds with environmental effects
H. O. Fatoyinbo, P. Tiwari, P. O. Olanipekun, I. Ghosh
https://arxiv.org/abs/2508.12201

A mathematical model of HPAI transmission between dairy cattle and wild birds with environmental effects
Highly pathogenic avian influenza (HPAI), especially the H5N1 strain, remains a major threat to animal health, food security, and public health. Recent spillover events in dairy cattle in the United States, linked to wild birds, highlight the critical importance of understanding transmission pathways at the cattle--wild bird--environment interface. In this work, we formulate and analyze a deterministic compartmental model that captures the transmission of HPAI between dairy cattle and wild bird…

Importance Sampling Approximation of Sequence Evolution Models with Site-Dependence
Joseph Mathews, Scott C. Schmidler
https://arxiv.org/abs/2508.11461 https://

Importance Sampling Approximation of Sequence Evolution Models with Site-Dependence
We consider models for molecular sequence evolution in which the transition rates at each site depend on the local sequence context, giving rise to a time-inhomogeneous Markov process in which sites evolve under a complex dependency structure. We introduce a randomized approximation algorithm for the marginal sequence likelihood under these models using importance sampling, and provide matching order upper and lower bounds on the finite sample approximation error. Given two sequences of length …

Age of Semantic Information-Aware Wireless Transmission for Remote Monitoring Systems
Xue Han, Biqian Feng, Yongpeng Wu, Xiang-Gen Xia, Wenjun Zhang, Shengli Sun
https://arxiv.org/abs/2508.12248

Age of Semantic Information-Aware Wireless Transmission for Remote Monitoring Systems
Semantic communication is emerging as an effective means of facilitating intelligent and context-aware communication for next-generation communication systems. In this paper, we propose a novel metric called Age of Incorrect Semantics (AoIS) for the transmission of video frames over multiple-input multiple-output (MIMO) channels in a monitoring system. Different from the conventional age-based approaches, we jointly consider the information freshness and the semantic importance, and then formul…

Stretchable and self-adhesive triboelectric sensor for real-time musculoskeletal monitoring and personalized recovery
Cai Lin, Yunyi Ding, Kai Lin, Ru Wang, Yichen Luo, Xiaofen Wu
https://arxiv.org/abs/2508.11655

Stretchable and self-adhesive triboelectric sensor for real-time musculoskeletal monitoring and personalized recovery
Recent advances in medical diagnostics have highlighted the importance of wearable technologies for continuous and real-time physiological monitoring. In this study, we introduce a flexible, self-powered triboelectric nanogenerator (MB-TENG) engineered from commercially available medical elastic bandages for biomechanical sensing during rehabilitation and gait analysis. Leveraging the porous and skin-friendly properties of the bandage combined with a PTFE film, the MB-TENG delivers robust elect…

Orthogonal Polynomials for the Gaussian Weight with a Jump and Discrete Painlev\'e Equations
Anton Dzhamay, Elizaveta Trunina
https://arxiv.org/abs/2508.12202 https://

Orthogonal Polynomials for the Gaussian Weight with a Jump and Discrete Painlevé Equations
We describe a refined version of the discrete Painlevé identification problem that emphasizes the importance on going beyond just the surface type in describing a discrete Painlevé dynamic. We give an example of solving such identification problem for a particular recurrence relation that previously appeared in studying orthogonal polynomials for the Gaussian weight with a single jump.

Steady Prandtl Layer for Compressible Fluids
Yan Guo, Yong Wang
https://arxiv.org/abs/2509.13988 https://arxiv.org/pdf/2509.13988

Steady Prandtl Layer for Compressible Fluids
Despite its importance, there have been few PDE results to investigate Prandtl layers for compressible fluids, in which the thermal boundary layer for the temperature field interacts with the classical velocity Prandtl boundary layer in a strong nonlinear fashion. We establish local-in-$x$ well-posedness of Prandtl layers for steady compressible fluids and construct Prandtl layer expansion in strong Sobolev norms, a foundation for the validity of Prandtl layer theory \cite{Guo-Wang}. Our method…

Mass Loss and Subsequent Thermal Evolution of Surviving Helium White Dwarfs Shocked by Thermonuclear Supernovae
Tin Long Sunny Wong, Lars Bildsten
https://arxiv.org/abs/2508.12529

Mass Loss and Subsequent Thermal Evolution of Surviving Helium White Dwarfs Shocked by Thermonuclear Supernovae
Following a type Ia supernova (SN Ia) in a double white dwarf (WD) binary, a surviving WD companion leaves at its orbital velocity $\approx 1$,000 - 3,000 km/s. The Gaia mission has discovered seven such hypervelocity WDs with inflated radii indicative of shock heating by SN ejecta. We study the interaction between SN ejecta and Roche lobe-filling 0.08 - 0.45 $M_{\odot}$ helium WD companions using three-dimensional hydrodynamical simulations with Athena++. Given the importance of the later ther…

Importance-Weighted Domain Adaptation for Sound Source Tracking
Bingxiang Zhong, Thomas Dietzen
https://arxiv.org/abs/2509.13215 https://arxiv.org/pdf/2509…

Importance-Weighted Domain Adaptation for Sound Source Tracking
In recent years, deep learning has significantly advanced sound source localization (SSL). However, training such models requires large labeled datasets, and real recordings are costly to annotate in particular if sources move. While synthetic data using simulated room impulse responses (RIRs) and noise offers a practical alternative, models trained on synthetic data suffer from domain shift in real environments. Unsupervised domain adaptation (UDA) can address this by aligning synthetic and re…

Lense-Thirring precession of accretion flows: relativistic versus classical precession
Gabriel T\"or\"ok, Martin Urbanec, Monika Matuszkov\'a, Gabriela Urbancov\'a, Kate\v{r}ina Klimovi\v{c}ov\'a, Debora Lan\v{c}ov\'a, Eva \v{S}r\'amkov\'a, Ji\v{r}\'i Hor\'ak
https://arxiv.org/abs/2508.13777…

Lense-Thirring precession of accretion flows: relativistic versus classical precession
The vertical (Lense-Thirring) precession of the innermost accretion flows has been discussed as a sensitive indicator of the rotational properties of neutron stars (NSs) and their equation of state because it vanishes for a non-rotating star. In this work, we apply the Hartle-Thorne spacetimes to study the frequencies of the precession for both geodesic and non-geodesic (fluid) flows. We build on previous findings on the effect of the NS quadrupole moment, which revealed the importance of the i…

Hubbard energy dependence of electronic structures in rare-earth monoxides
Mizuki Tago, Tsukasa Kurachi, Takayuki Makino
https://arxiv.org/abs/2508.12635 https://

Hubbard energy dependence of electronic structures in rare-earth monoxides
To realize the significant potential of optical materials such as strongly electron-correlated open-shell rare-earth monoxides, understanding the electron-localization Hubbard parameters ($U$) is of central importance. The Hubbard energy is believed to be material specific and constant. However, it has recently been pointed out that even subtle structural changes can induce changes in $U$ parameters. For LuO, we theoretically evaluated $U$ energy dependence of the differential transmission and …

Time-Varying Heterogeneous Treatment Effects in Event Studies
Irene Botosaru, Laura Liu
https://arxiv.org/abs/2509.13698 https://arxiv.org/pdf/2509.13698…

Time-Varying Heterogeneous Treatment Effects in Event Studies
This paper examines the identification and estimation of heterogeneous treatment effects in event studies, emphasizing the importance of both lagged dependent variables and treatment effect heterogeneity. We show that omitting lagged dependent variables can induce omitted variable bias in the estimated time-varying treatment effects. We develop a novel semiparametric approach based on a short-T dynamic linear panel model with correlated random coefficients, where the time-varying heterogeneous …

Definability of some $k$-ary Relations Over Second Order kinds of Logics
Simone Costa, Marco Dalai, Stefano Della Fiore, Anita Pasotti
https://arxiv.org/abs/2509.13063 https://

Definability of some $k$-ary Relations Over Second Order kinds of Logics
We consider the exprissibility in monadic second order logic of certain relations of importance in computer science. For integers $n\geq 1$ and $k\leq b$, a $k$-tuple of sequences in $\{0,1,\ldots, b-1\}^n$ are said to be $k$-hashed if there is a coordinate where they all differ. A set $\mathcal{C}$ of sequences is said to be a $k$-hash code if any $k$ distinct elements are $k$-hashed. Testing whether a code is $k$-hashing and determining the largest size of $k$-hash codes is an important probl…

Worker Discretion Advised: Co-designing Risk Disclosure in Crowdsourced Responsible AI (RAI) Content Work
Alice Qian, Ziqi Yang, Ryland Shaw, Jina Suh, Laura Dabbish, Hong Shen
https://arxiv.org/abs/2509.12140

Worker Discretion Advised: Co-designing Risk Disclosure in Crowdsourced Responsible AI (RAI) Content Work
Responsible AI (RAI) content work, such as annotation, moderation, or red teaming for AI safety, often exposes crowd workers to potentially harmful content. While prior work has underscored the importance of communicating well-being risk to employed content moderators, designing effective disclosure mechanisms for crowd workers while balancing worker protection with the needs of task designers and platforms remains largely unexamined. To address this gap, we conducted co-design sessions with 29…

Efficient Prior Sensitivity and Tipping-point Analysis for Medical Research: Revisiting Sampling Importance Resampling
Tomohiro Ohigashi, Shonosuke Sugasawa
https://arxiv.org/abs/2510.10034

Efficient Prior Sensitivity and Tipping-point Analysis for Medical Research: Revisiting Sampling Importance Resampling
Bayesian methods have received increasing attention in medical research, where sensitivity analysis of prior distributions is essential. Such analyses typically require the evaluation of the posterior distribution of a parameter under multiple alternative prior settings. When the posterior distribution of the parameter of interest cannot be derived analytically, the standard approach is to re-fit the Markov chain Monte Carlo (MCMC) algorithm for each setting, which incurs substantial computatio…

GitHub CEO Thomas Dohmke plans to step down to pursue entrepreneurial endeavors; memo: Microsoft is opting not to directly replace the position (Ina Fried/Axios)
https://www.axios.com/2025/08/11/github-ceo-dohmke-step-down

Exclusive: GitHub CEO to step down
The Microsoft-owned software development hub has grown in importance in the AI era.

Crystal Orientation Dependence of Extreme Near-Field Heat Transfer between Polar Materials Governed by Surface Phonon Modes
Wei-Zhe Yuan, Yangyu Guo, Hong-Liang Yi
https://arxiv.org/abs/2509.13837

Crystal Orientation Dependence of Extreme Near-Field Heat Transfer between Polar Materials Governed by Surface Phonon Modes
Due to the rapid development of micro- and nano-manufacturing and electronic devices, heat transfer at the transition regime between radiation and conduction becomes increasingly important. Recent work has demonstrated the importance of nonlocal optical response and phonon tunneling. However, it remains unclear how the crystal orientation impacts them. In this work, we study this effect on heat transport across vacuum gaps between magnesium oxide (MgO) by nonequilibrium molecular dynamics (NEMD…

Large Language Models Discriminate Against Speakers of German Dialects
Minh Duc Bui, Carolin Holtermann, Valentin Hofmann, Anne Lauscher, Katharina von der Wense
https://arxiv.org/abs/2509.13835

Large Language Models Discriminate Against Speakers of German Dialects
Dialects represent a significant component of human culture and are found across all regions of the world. In Germany, more than 40% of the population speaks a regional dialect (Adler and Hansen, 2022). However, despite cultural importance, individuals speaking dialects often face negative societal stereotypes. We examine whether such stereotypes are mirrored by large language models (LLMs). We draw on the sociolinguistic literature on dialect perception to analyze traits commonly associated wi…

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters
Michelle Ntampaka, A. Ciprijanovic, Ana Maria Delgado, John Soltis, John F. Wu, Mikaeel Yunus, John ZuHone
https://arxiv.org/abs/2510.09748

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters
The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observati…

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https://bsky.app/profile/lizafella.bsky.social/post/3m2zbqxbt3c2j

Importance-Aware Semantic Communication in MIMO-OFDM Systems Using Vision Transformer
Joohyuk Park, Yongjeong Oh, Jihun Park, Yo-Seb Jeon
https://arxiv.org/abs/2508.07696 https:…

Importance-Aware Semantic Communication in MIMO-OFDM Systems Using Vision Transformer
This paper presents a novel importance-aware quantization, subcarrier mapping, and power allocation (IA-QSMPA) framework for semantic communication in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, empowered by a pretrained Vision Transformer (ViT). The proposed framework exploits attention-based importance extracted from a pretrained ViT to jointly optimize quantization levels, subcarrier mapping, and power allocation. Specifically, IA-QSMPA maps…

Reasonable Experiments in Model-Based Systems Engineering
Johan Cederbladh, Loek Cleophas, Eduard Kamburjan, Lucas Lima, Rakshit Mittal, Hans Vangheluwe
https://arxiv.org/abs/2509.10649

Reasonable Experiments in Model-Based Systems Engineering
With the current trend in Model-Based Systems Engineering towards Digital Engineering and early Validation & Verification, experiments are increasingly used to estimate system parameters and explore design decisions. Managing such experimental configuration metadata and results is of utmost importance in accelerating overall design effort. In particular, we observe it is important to 'intelligent-ly' reuse experiment-related data to save time and effort by not performing potentially superfluous…

Dak Prescott on Rams joint practice, importance of preseason reps https://www.dallascowboys.com/news/dak-prescott-on-rams-joint-practice-importance-of-preseason-reps

James Burkett Hartle: a Biographical Memoir
Gary T. Horowitz, Kip S. Thorne
https://arxiv.org/abs/2509.14288 https://arxiv.org/pdf/2509.14288

James Burkett Hartle: a Biographical Memoir
James Burkett Hartle was a theoretical physicist who made major contributions to our understanding of relativistic stars, black holes, and cosmology. Most of his career, however, was devoted to studying the universe as a quantum system. As a result, he was known as the father of quantum cosmology. He is best known for two seminal papers with Stephen Hawking that introduced two quantum states of fundamental importance: the "Hartle-Hawking vacuum" for matter fields outside a black hole, and the "…

Replaced article(s) found for cs.DL. https://arxiv.org/list/cs.DL/new
[1/1]:
- Understanding the importance of SHAPE to the UK research ecosystem
Draux, Fane, Hook, Wastl, Lewis, Jones, Roblero, Wilsdon

Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction
Joseph Paillard, Antoine Collas, Denis A. Engemann, Bertrand Thirion
https://arxiv.org/abs/2508.08724

Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction
Recent advances in machine learning have greatly expanded the repertoire of predictive methods for medical imaging. However, the interpretability of complex models remains a challenge, which limits their utility in medical applications. Recently, model-agnostic methods have been proposed to measure conditional variable importance and accommodate complex non-linear models. However, they often lack power when dealing with highly correlated data, a common problem in medical imaging. We introduce H…

[Part 2] The GÉANT (GN5-2) Above-the-Net Services Incubator is proud to award 4 projects set to advance digital services for European R&E 🎉
The awarded initiatives address service development priorities across three areas of strategic importance for the GÉANT community: Digital Research Environment (DRE), Object Storage Infrastructure, Data Movement Infrastructure.
👏 Big congratulations to the organisations leading these initiatives.
➡️ Meet the awarded projects:

"""
All of which was of the utmost importance for subsequent developments in the medicine of the mind. In its positivist incarnation, this was little more than the combination of the two experiences that classicism had juxtaposed without ever joining them together: a social, normative and dichotomous experience of madness that revolved entirely around the imperative of confinement, formulated in a style as simple as ‘yes or no’, ‘dangerous or harmless’, and ‘good or not good for confinement’, and a finely differentiated, qualitative, juridical experience, well aware of limits and degrees, which looked into all the aspects of the behaviour of the subject for the polymorphous incarnations that insanity might assume. The psychopathology of the nineteenth century (and perhaps our own too, even now) believes that it orients itself and takes its bearings in relation to a homo natura, or a normal man pre-existing all experience of mental illness. Such a man is in fact an invention, and if he is to be situated, it is not in a natural space, but in a system that identifies the socius to the subject of the law. Consequently a madman is not recognised as such because an illness has pushed him to the margins of normality, but because our culture situates him at the meeting point between the social decree of confinement and the juridical knowledge that evaluates the responsibility of individuals before the law. The ‘positive’ science of mental illness and the humanitarian sentiments that brought the mad back into the realm of the human were only possible once that synthesis had been solidly established. They could be said to form the concrete a priori of any psychopathology with scientific pretensions.
"""
(Michel Foucault, History of Madness)

Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, Tadashi Maeno, Fatih Furkan Akman, Joseph Boudreau, Sankha Dutta, Shengyu Feng, Adolfy Hoisie, Kuan-Chieh Hsu, Raees Khan, Jaehyung Kim, Ozgur O. Kilic, Scott Klasky, Alexei Klimentov, Tatiana Korchuganova, Verena Ingrid Martinez Outschoorn, Paul Nilsson, David K. Park, Norbert Podhorszki, Yihui Ren, John Rembrandt Steele, Fr\'ed\'eric Suter, Sairam Sri Vatsavai, Torre Wenaus,…

Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
The collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimat…

Replaced article(s) found for physics.soc-ph. https://arxiv.org/list/physics.soc-ph/new
[1/1]:
- Understanding the importance of SHAPE to the UK research ecosystem
Draux, Fane, Hook, Wastl, Lewis, Jones, Roblero, Wilsdon

Learning to Generate 4D LiDAR Sequences
Ao Liang, Youquan Liu, Yu Yang, Dongyue Lu, Linfeng Li, Lingdong Kong, Huaici Zhao, Wei Tsang Ooi
https://arxiv.org/abs/2509.11959 https:…

Learning to Generate 4D LiDAR Sequences
While generative world models have advanced video and occupancy-based data synthesis, LiDAR generation remains underexplored despite its importance for accurate 3D perception. Extending generation to 4D LiDAR data introduces challenges in controllability, temporal stability, and evaluation. We present LiDARCrafter, a unified framework that converts free-form language into editable LiDAR sequences. Instructions are parsed into ego-centric scene graphs, which a tri-branch diffusion model transfor…

Scaling green hydrogen and CCUS via cement-methanol co-production in China
Yuezhang He, Hongxi Luo, Yuancheng Lin, Carl J. Talsma, Anna Li, Zhenqian Wang, Yujuan Fang, Pei Liu, Jesse D. Jenkins, Eric Larson, Zheng Li
https://arxiv.org/abs/2509.13674

Scaling green hydrogen and CCUS via cement-methanol co-production in China
High costs of green hydrogen and of carbon capture, utilization, and sequestration (CCUS) have hindered policy ambition and slowed real-world deployment, despite their importance for decarbonizing hard-to-abate sectors, including cement and methanol. Given the economic challenges of adopting CCUS in cement and green hydrogen in methanol production separately, we propose a renewable-powered co-production system that couples electrolytic hydrogen and CCUS through molecule exchange. We optimize sy…

Combining Evidence and Reasoning for Biomedical Fact-Checking
Mariano Barone, Antonio Romano, Giuseppe Riccio, Marco Postiglione, Vincenzo Moscato
https://arxiv.org/abs/2509.13879

Combining Evidence and Reasoning for Biomedical Fact-Checking
Misinformation in healthcare, from vaccine hesitancy to unproven treatments, poses risks to public health and trust in medical sys- tems. While machine learning and natural language processing have advanced automated fact-checking, validating biomedical claims remains uniquely challenging due to complex terminol- ogy, the need for domain expertise, and the critical importance of grounding in scientific evidence. We introduce CER (Combin- ing Evidence and Reasoning), a novel framework for biomed…

Crosslisted article(s) found for math.PR. https://arxiv.org/list/math.PR/new
[1/1]:
- Importance Sampling Approximation of Sequence Evolution Models with Site-Dependence
Joseph Mathews, Scott C. Schmidler

The Sunburst Arc with JWST. IV. The importance of interaction, turbulence, and feedback for Lyman-continuum escape
T. Emil Rivera-Thorsen, Brian Welch, Taylor Hutchison, Matthew J. Hayes, Jane R. Rigby, Keunho Kim, Suhyeon Choe, Michael Florian, Matthew B. Bayliss, Gourav Khullar, Keren Sharon, H{\aa}kon Dahle, John Chisholm, Erik Solhaug, M. Riley Owens, Michael D. Gladders

The Sunburst Arc with JWST. IV. The importance of interaction, turbulence, and feedback for Lyman-continuum escape
At present, the best opportunity for detailed Lyman Continuum escape studies is in gravitationally lensed galaxies at z >= 2. Only one such galaxy currently exists in the literature with sufficient spatial magnification: The Sunburst Arc at redshift z = 2.37. Here, we present rest-frame optical JWST NIRSpec integral field observations of the Sunburst Arc that cover a large fraction of the source plane. From this dataset, we generate precise maps of ISM kinematics, dust geometry, ionization, and…

The Importance of In-Person Inspiration https://muz4now.com/2022/the-importance-of-in-person-inspiration/

The Importance of In-Person Inspiration
Stan Stewart - @muz4now

Recursive Adaptive Importance Sampling with Optimal Replenishment
Daniel W\"urzler Barreto, Mevin B. Hooten
https://arxiv.org/abs/2509.08102 https://a…

Recursive Adaptive Importance Sampling with Optimal Replenishment
Increased access to computing resources has led to the development of algorithms that can run efficiently on multi-core processing units or in distributed computing environments. In the context of Bayesian inference, many parallel computing approaches to fit statistical models have been proposed in the context of Markov Chain Monte Carlo methods, but they either have limited gains due to high latency cost or rely on model-specific decompositions. Alternatively, adaptive importance sampling, seq…

Event2Vec: A Geometric Approach to Learning Composable Representations of Event Sequences
Antonin Sulc
https://arxiv.org/abs/2509.12188 https://arxiv.org/p…

Event2Vec: A Geometric Approach to Learning Composable Representations of Event Sequences
The study of neural representations, both in biological and artificial systems, is increasingly revealing the importance of geometric and topological structures. Inspired by this, we introduce Event2Vec, a novel framework for learning representations of discrete event sequences. Our model leverages a simple, additive recurrent structure to learn composable, interpretable embeddings. We provide a theoretical analysis demonstrating that, under specific training objectives, our model's learned rep…

Combating Biomedical Misinformation through Multi-modal Claim Detection and Evidence-based Verification
Mariano Barone, Antonio Romano, Giuseppe Riccio, Marco Postiglione, Vincenzo Moscato
https://arxiv.org/abs/2509.13888

Combating Biomedical Misinformation through Multi-modal Claim Detection and Evidence-based Verification
Misinformation in healthcare, from vaccine hesitancy to unproven treatments, poses risks to public health and trust in medical systems. While machine learning and natural language processing have advanced automated fact-checking, validating biomedical claims remains uniquely challenging due to complex terminology, the need for domain expertise, and the critical importance of grounding in scientific evidence. We introduce CER (Combining Evidence and Reasoning), a novel framework for biomedical f…

Overlooked Raiders' Importance Is on the Rise https://www.si.com/nfl/raiders/las-vegas-tennessee-titans-dylan-parham-kolton-miller

Importance of Pride as an NFL Player | Players Lounge https://www.youtube.com/watch?v=5Pg5MhebRCs

Characterizing Human Limb Movements Using An In-House Multi-Channel Non-Invasive Surface-EMG System
Vinay C K, Vikas Vazhayil, Madhav rao
https://arxiv.org/abs/2509.13840 https:…

Characterizing Human Limb Movements Using An In-House Multi-Channel Non-Invasive Surface-EMG System
Electromyography (EMG) signals are obtained from muscle cell activity. The recording and analysis of EMG signals has several applications. The EMG is of diagnostic importance for treating patients suffering from neurological and neuromuscular disorders. Conventional methods involve placement of invasive electrodes within the muscles to record EMG signals. The goal is to showcase the usage of surface based EMG signals to characterize all possible human limb movements. An in-house non-invasive EM…

Decorrelated feature importance from local sample weighting
Benedikt Fr\"ohlich, Alison Durst, Merle Behr
https://arxiv.org/abs/2508.06337 https://arx…

Decorrelated feature importance from local sample weighting
Feature importance (FI) statistics provide a prominent and valuable method of insight into the decision process of machine learning (ML) models, but their effectiveness has well-known limitations when correlation is present among the features in the training data. In this case, the FI often tends to be distributed among all features which are in correlation with the response-generating signal features. Even worse, if multiple signal features are in strong correlation with a noise feature, while…

Safe cross-entropy-based importance sampling for rare event simulations
Zhiwei Gao, George Karniadakis
https://arxiv.org/abs/2509.07160 https://arxiv.org/p…

Safe cross-entropy-based importance sampling for rare event simulations
The Improved Cross-Entropy (ICE) method is a powerful tool for estimating failure probabilities in reliability analysis. Its core idea is to approximate the optimal importance-sampling density by minimizing the forward Kullback-Leibler divergence within a chosen parametric family-typically a mixture model. However, conventional mixtures are often light-tailed, which leads to slow convergence and instability when targeting very small failure probabilities. Moreover, selecting the number of mixtu…

Replaced article(s) found for stat.CO. https://arxiv.org/list/stat.CO/new
[1/1]:
- Quantile Importance Sampling
Jyotishka Datta, Nicholas G. Polson
https://

Pulsations change the structures of massive stars before they explode: interpreting the nearby supernova SN 2023ixf
Eva Laplace, Vincent A. Bronner, Fabian R. N. Schneider, Philipp Podsiadlowski
https://arxiv.org/abs/2508.11088

Pulsations change the structures of massive stars before they explode: interpreting the nearby supernova SN 2023ixf
It is known that massive red supergiants (RSGs) become hydrodynamically unstable and experience radial pulsations before they explode. Still, the vast majority of supernova (SN) models assume RSG progenitors in hydrostatic equilibrium. Here, we self-consistently follow the hydrodynamic evolution of RSGs with different masses and the development of radial envelope pulsations. Pulsations significantly alter the observable pre- and post-SN properties, and their importance increases substantially a…

"Low Frequency Tweeters Have More to Say!" A New Approach to Identify Importance of Tweets
Gautam Khannaa, Yeliz Yesilada, Sukru Eraslan, Simon Harper
https://arxiv.org/abs/2509.03931

"Low Frequency Tweeters Have More to Say!" A New Approach to Identify Importance of Tweets
Twitter is one of the most popular social media platforms.With a large number of tweets, the activity feed of users becomes noisy, challenging to read, and most importantly tweets often get lost. We present a new approach to personalise the ranking of the tweets toward solving the problem of information overload which is achieved by analysing the relationship between the importance of tweets to the frequency at which the author tweets. The hypothesis tested is that "low-frequency tweeters have …

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/5]:
- Hyperflux: Pruning Reveals the Importance of Weights
Eugen Barbulescu, Antonio Alexoaie, Lucian Busoniu

The importance of being non-minimally coupled: scalar Hawking radiation from regular black holes
Marco Calz\`a, Massimiliano Rinaldi, Sunny Vagnozzi
https://arxiv.org/abs/2510.12257

The importance of being non-minimally coupled: scalar Hawking radiation from regular black holes
In curved space-time, a scalar field $ϕ$ is generically expected to couple to curvature, via a coupling of the form $ξϕ^2R$. Yet in the study of Hawking emission from regular black holes (RBHs), where scalar fields are often introduced as simple probes of the geometry, and the Ricci scalar is generically non-zero, this non-minimal coupling is almost always ignored. We revisit this assumption by studying scalar Hawking emission from four representative RBHs (the Bardeen, Hayward, Simpson-Viss…

Quasi-Monte Carlo integration over $\mathbb{R}^s$ with boundary-damping importance sampling
Zexin Pan, Du Ouyang, Zhijian He
https://arxiv.org/abs/2509.07509 https://

Quasi-Monte Carlo integration over $\mathbb{R}^s$ with boundary-damping importance sampling
This paper proposes a new importance sampling (IS) that is tailored to quasi-Monte Carlo (QMC) integration over $\mathbb{R}^s$. IS introduces a multiplicative adjustment to the integrand by compensating the sampling from the proposal instead of the target distribution. Improper proposals result in severe adjustment factor for QMC. Our strategy is to first design a adjustment factor to meet desired regularities and then determine a tractable transport map from the standard uniforms to the propos…

Crosslisted article(s) found for stat.CO. https://arxiv.org/list/stat.CO/new
[1/1]:
- Hierarchical Importance Sampling for Estimating Occupation Time for SDE Solutions
Eya Ben Amar, Nadhir Ben Rached, Raul Tempone

Room acoustics affect communicative success in hybrid meeting spaces: a pilot study
Robert Einig, Stefan Janscha, Jonas Schuster, Julian Koch, Martin Hagmueller, Barbara Schuppler
https://arxiv.org/abs/2509.11709

Room acoustics affect communicative success in hybrid meeting spaces: a pilot study
Since the COVID-19 pandemic in 2020, universities and companies have increasingly integrated hybrid features into their meeting spaces, or even created dedicated rooms for this purpose. While the importance of a fast and stable internet connection is often prioritized, the acoustic design of seminar rooms is frequently overlooked. Poor acoustics, particularly excessive reverberation, can lead to issues such as misunderstandings, reduced speech intelligibility or cognitive and vocal fatigue. Thi…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/6]:
- Hyperflux: Pruning Reveals the Importance of Weights
Eugen Barbulescu, Antonio Alexoaie, Lucian Busoniu

Brian Schottenheimer preaches importance of discipline for Cowboys https://www.si.com/nfl/cowboys/news/brian-schottenheimer-preaches-importance-discipline-dallas-cowboys

Evaluation of Black-Box XAI Approaches for Predictors of Values of Boolean Formulae
Stav Armoni-Friedmann, Hana Chockler, David A. Kelly
https://arxiv.org/abs/2509.09982 https:/…

Evaluation of Black-Box XAI Approaches for Predictors of Values of Boolean Formulae
Evaluating explainable AI (XAI) approaches is a challenging task in general, due to the subjectivity of explanations. In this paper, we focus on tabular data and the specific use case of AI models predicting the values of Boolean functions. We extend the previous work in this domain by proposing a formal and precise measure of importance of variables based on actual causality, and we evaluate state-of-the-art XAI tools against this measure. We also present a novel XAI tool B-ReX, based on the e…

Randomized Quasi-Monte Carlo with Importance Sampling for Functions under Generalized Growth Conditions and Its Applications in Finance
Jianlong Chen, Yu Xu, Xiaoqun Wang
https://arxiv.org/abs/2510.06705

Randomized Quasi-Monte Carlo with Importance Sampling for Functions under Generalized Growth Conditions and Its Applications in Finance
Many problems can be formulated as high-dimensional integrals of discontinuous functions that often exhibit significant growth, challenging the error analysis of randomized quasi-Monte Carlo (RQMC) methods. This paper studies RQMC methods for functions with generalized exponential growth conditions, with a special focus on financial derivative pricing. The main contribution of this work is threefold. First, by combining RQMC and importance sampling (IS) techniques, we derive a new error bound f…

Neural Scaling Laws for Deep Regression
Tilen Cadez, Kyoung-Min Kim
https://arxiv.org/abs/2509.10000 https://arxiv.org/pdf/2509.10000

Neural Scaling Laws for Deep Regression
Neural scaling laws--power-law relationships between generalization errors and characteristics of deep learning models--are vital tools for developing reliable models while managing limited resources. Although the success of large language models highlights the importance of these laws, their application to deep regression models remains largely unexplored. Here, we empirically investigate neural scaling laws in deep regression using a parameter estimation model for twisted van der Waals magnet…

MultimodalHugs: Enabling Sign Language Processing in Hugging Face
Gerard Sant, Zifan Jiang, Carlos Escolano, Amit Moryossef, Mathias M\"uller, Rico Sennrich, Sarah Ebling
https://arxiv.org/abs/2509.09729

MultimodalHugs: Enabling Sign Language Processing in Hugging Face
In recent years, sign language processing (SLP) has gained importance in the general field of Natural Language Processing. However, compared to research on spoken languages, SLP research is hindered by complex ad-hoc code, inadvertently leading to low reproducibility and unfair comparisons. Existing tools that are built for fast and reproducible experimentation, such as Hugging Face, are not flexible enough to seamlessly integrate sign language experiments. This view is confirmed by a survey we…

Evaluation of Real-Time Preprocessing Methods in AI-Based ECG Signal Analysis
Jasmin Freudenberg, Kai Hahn, Christian Weber, Madjid Fathi
https://arxiv.org/abs/2510.12541 https:…

Evaluation of Real-Time Preprocessing Methods in AI-Based ECG Signal Analysis
The increasing popularity of portable ECG systems and the growing demand for privacy-compliant, energy-efficient real-time analysis require new approaches to signal processing at the point of data acquisition. In this context, the edge domain is acquiring increasing importance, as it not only reduces latency times, but also enables an increased level of data security. The FACE project aims to develop an innovative machine learning solution for analysing long-term electrocardiograms that synergi…

Understanding Textual Emotion Through Emoji Prediction
Ethan Gordon, Nishank Kuppa, Rigved Tummala, Sriram Anasuri
https://arxiv.org/abs/2508.10222 https://

Understanding Textual Emotion Through Emoji Prediction
This project explores emoji prediction from short text sequences using four deep learning architectures: a feed-forward network, CNN, transformer, and BERT. Using the TweetEval dataset, we address class imbalance through focal loss and regularization techniques. Results show BERT achieves the highest overall performance due to its pre-training advantage, while CNN demonstrates superior efficacy on rare emoji classes. This research shows the importance of architecture selection and hyperparamete…