Tootfinder

Uncovering Scaling Laws for Large Language Models via Inverse Problems
Arun Verma, Zhaoxuan Wu, Zijian Zhou, Xiaoqiang Lin, Zhiliang Chen, Rachael Hwee Ling Sim, Rui Qiao, Jingtan Wang, Nhung Bui, Xinyuan Niu, Wenyang Hu, Gregory Kang Ruey Lau, Zi-Yu Khoo, Zitong Zhao, Xinyi Xu, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low
https://

Uncovering Scaling Laws for Large Language Models via Inverse Problems
Large Language Models (LLMs) are large-scale pretrained models that have achieved remarkable success across diverse domains. These successes have been driven by unprecedented complexity and scale in both data and computations. However, due to the high costs of training such models, brute-force trial-and-error approaches to improve LLMs are not feasible. Inspired by the success of inverse problems in uncovering fundamental scientific laws, this position paper advocates that inverse problems can …

VRPAgent: LLM-Driven Discovery of Heuristic Operators for Vehicle Routing Problems
Andr\'e Hottung, Federico Berto, Chuanbo Hua, Nayeli Gast Zepeda, Daniel Wetzel, Michael R\"omer, Haoran Ye, Davide Zago, Michael Poli, Stefano Massaroli, Jinkyoo Park, Kevin Tierney
https://arxiv.org/abs/2510.07073

VRPAgent: LLM-Driven Discovery of Heuristic Operators for Vehicle Routing Problems
Designing high-performing heuristics for vehicle routing problems (VRPs) is a complex task that requires both intuition and deep domain knowledge. Large language model (LLM)-based code generation has recently shown promise across many domains, but it still falls short of producing heuristics that rival those crafted by human experts. In this paper, we propose VRPAgent, a framework that integrates LLM-generated components into a metaheuristic and refines them through a novel genetic search. By u…

EDUMATH: Generating Standards-aligned Educational Math Word Problems
Bryan R. Christ, Penelope Molitz, Jonathan Kropko, Thomas Hartvigsen
https://arxiv.org/abs/2510.06965 https:…

EDUMATH: Generating Standards-aligned Educational Math Word Problems
Math word problems (MWPs) are critical K-12 educational tools, and customizing them to students' interests and ability levels can increase learning outcomes. However, teachers struggle to find time to customize MWPs for each student given large class sizes and increasing burnout. We propose that LLMs can support math education by generating MWPs customized to student interests and math education standards. To this end, we use a joint human expert-LLM judge approach to evaluate over 11,000 MWPs …

"Carbon offsets fail to cut global heating due to ‘intractable’ systemic problems, study says"
#Climate #ClimateChange

A Globalized Semismooth Newton Method for Prox-regular Optimization Problems
Yuqia Wu, Pengcheng Wu, Yaohua Hu, Shaohua Pan, Xiaoqi Yang
https://arxiv.org/abs/2509.05765 https:/…

A Globalized Semismooth Newton Method for Prox-regular Optimization Problems
We are concerned with a class of nonconvex and nonsmooth composite optimization problems, comprising a twice differentiable function and a prox-regular function. We establish a sufficient condition for the proximal mapping of a prox-regular function to be single-valued and locally Lipschitz continuous. By virtue of this property, we propose a hybrid of proximal gradient and semismooth Newton methods for solving these composite optimization problems, which is a globalized semismooth Newton metho…

General expression for the energy and the equation of state for polycrystalline solids
O. Bystrenko (Frantsevich Institute for problems of materials science, Kyiv, Ukraine), B. Ilkiv (Frantsevich Institute for problems of materials science, Kyiv, Ukraine), S. Petrovska (Frantsevich Institute for problems of materials science, Kyiv, Ukraine), T. Bystrenko (Frantsevich Institute for problems of materials science, Kyiv, Ukraine), O. Foia (Frantsevich Institute for problems of materials sc…

General expression for the energy and the equation of state for polycrystalline solids
On the basis of the extended classical elasticity theory, we propose universal semi-empirical analytical expressions for the energy and the equation of state for poly-crystalline solids. The validation of the relations has been made by means of first principle density functional theory simulations with the use of pseudo-potential approach and generalized gradient approximation for the exchange-correlation energy. The calculations performed for a large number of inorganic crystalline compounds w…

Duality estimates for subdiffusion problems including time-fractional porous medium type equations
Arl\'ucio Viana, Patryk Wolejko, Rico Zacher
https://arxiv.org/abs/2509.07862

Duality estimates for subdiffusion problems including time-fractional porous medium type equations
We prove duality estimates for time-fractional and more general subdiffusion problems. An important example is given by subdiffusive porous medium type equations. Our estimates can be used to prove uniqueness of weak solutions to such problems, and they allow to extend a key estimate from classical reaction-diffusion systems to the subdiffusive case. Besides concrete equations involving a Laplacian, we also consider abstract problems in a Hilbert space setting.

End-to-end quantum algorithms for tensor problems
Enrico Fontana, Sivaprasad Omanakuttan, Junhyung Lyle Kim, Joseph Sullivan, Michael Perlin, Ruslan Shaydulin, Shouvanik Chakrabarti
https://arxiv.org/abs/2510.07273

End-to-end quantum algorithms for tensor problems
We present a comprehensive end-to-end quantum algorithm for tensor problems, including tensor PCA and planted kXOR, that achieves potential superquadratic quantum speedups over classical methods. We build upon prior works by Hastings~(\textit{Quantum}, 2020) and Schmidhuber~\textit{et al.}~(\textit{Phys.~Rev.~X.}, 2025), we address key limitations by introducing a native qubit-based encoding for the Kikuchi method, enabling explicit quantum circuit constructions and non-asymptotic resource esti…

I’m not interested in any model that doesn’t solve for those problems. No matter what utility it has.
Inversely, if one does solve for those problems in a way I find satisfactory, I’d be at least somewhat curious no matter what utility it may (or may not) have.

On Condensation Management - Learn how you can best avoid problems with condensation, damp and mould in winter. #mould #condensation #ventilation -

On Condensation Management
Learn how you can best avoid problems with condensation, damp and mould in winter. #mould #condensation #ventilation

A class of regularization schemes for linear ill-posed problems in Banach spaces under low order source conditions
Robert Plato
https://arxiv.org/abs/2509.05418 https://

A class of regularization schemes for linear ill-posed problems in Banach spaces under low order source conditions
In this work we consider, in a Banach space framework, the regularization of linear ill-posed problems. Our focus is on the recovery of solutions that have a logarithmic source representation. Such cases typically occur in exponentially ill-posed problems like the backwards heat equation. The mathematical framework on logarithms of operators is provided, and convergence rates for a class of parametric regularization schemes are deduced. This class includes the iterated version of Lavrentiev's m…

Open problems in information geometry: a discussion at FDIG 2025
Tomonari Sei, Hiroshi Matsuzoe
https://arxiv.org/abs/2509.06989 https://arxiv.org/pdf/2509…

Open problems in information geometry: a discussion at FDIG 2025
Open problems in information geometry are collected and discussed in the conference ``Further Developments of Information Geometry (FDIG) 2025'' held at the University of Tokyo, Japan, from March 18 to 21, 2025.

Multi-Bubble Isoperimetric Problems
Emanuel Milman
https://arxiv.org/abs/2510.07078 https://arxiv.org/pdf/2510.07078

Multi-Bubble Isoperimetric Problems
We survey recent advancements in the characterization of multi-bubble isoperimetric minimizers and the stability of soap bubble partitions. We conclude with some related open problems.

Generalized Graph Packing Problems Parameterized by Treewidth
Bar{\i}\c{s} Can Esmer, D\'aniel Marx
https://arxiv.org/abs/2509.06091 https://arxiv.org/…

Generalized Graph Packing Problems Parameterized by Treewidth
$H$-Packing is the problem of finding a maximum number of vertex-disjoint copies of $H$ in a given graph $G$. $H$-Partition is the special case of finding a set of vertex-disjoint copies that cover each vertex of $G$ exactly once. Our goal is to study these problems and some generalizations on bounded-treewidth graphs. The case of $H$ being a triangle is well understood: given a tree decomposition of $G$ having treewidth $tw$, the $K_3$-Packing problem can be solved in time $2^{tw} \cdot n^{O(1…

A Markov Decision Process Model for Intrusion Tolerance Problems
Patrick Kreidl
https://arxiv.org/abs/2509.07919 https://arxiv.org/pdf/2509.07919

A Markov Decision Process Model for Intrusion Tolerance Problems
We formulate and analyze a simplest Markov decision process model for intrusion tolerance problems, assuming that (i) each attack proceeds through one or more steps before the system's security fails, (ii) defensive responses that target these intermediate steps may only sometimes thwart the attack and (iii) reset responses that are sensible upon discovering an attack's completion may not always recover from the security failure. The analysis shows that, even in the ideal case of perfect detect…

Diffusing Trajectory Optimization Problems for Recovery During Multi-Finger Manipulation
Abhinav Kumar, Fan Yang, Sergio Aguilera Marinovic, Soshi Iba, Rana Soltani Zarrin, Dmitry Berenson
https://arxiv.org/abs/2510.07030

Diffusing Trajectory Optimization Problems for Recovery During Multi-Finger Manipulation
Multi-fingered hands are emerging as powerful platforms for performing fine manipulation tasks, including tool use. However, environmental perturbations or execution errors can impede task performance, motivating the use of recovery behaviors that enable normal task execution to resume. In this work, we take advantage of recent advances in diffusion models to construct a framework that autonomously identifies when recovery is necessary and optimizes contact-rich trajectories to recover. We use …

A Samsung researcher introduces the Tiny Recursion Model, a 7M-parameter model that was able to outperform LLMs 10,000x larger like o3-mini on specific problems (Carl Franzen/VentureBeat)
https://venturebeat.com/ai/samsung-ai-researchers-n…

A Composition-Based Approach to EKR Problems
J. B. Ebrahimi, A. Taherkhani
https://arxiv.org/abs/2509.06207 https://arxiv.org/pdf/2509.06207

A Composition-Based Approach to EKR Problems
Let ${\mathcal F}$ be a family of subsets of a finite set $X$. A subfamily of ${\mathcal F}$ is intersecting if any two members of ${\mathcal F}$ has nonempty intersection. We say ${\mathcal F}$ has the EKR property, if, for any fixed element of $X$ the subfamily of all sets in $\mathcal{F}$ that contain $x$ is an intersecting subfamily of $\mathcal{F}$ of possible maximum size. We say ${\mathcal F}$ has the strong EKR property (the strong EKR property), if every intersecting subfamily of $\mat…

Bilevel optimization for learning hyperparameters: Application to solving PDEs and inverse problems with Gaussian processes
Nicholas H. Nelsen, Houman Owhadi, Andrew M. Stuart, Xianjin Yang, Zongren Zou
https://arxiv.org/abs/2510.05568

Bilevel optimization for learning hyperparameters: Application to solving PDEs and inverse problems with Gaussian processes
Methods for solving scientific computing and inference problems, such as kernel- and neural network-based approaches for partial differential equations (PDEs), inverse problems, and supervised learning tasks, depend crucially on the choice of hyperparameters. Specifically, the efficacy of such methods, and in particular their accuracy, stability, and generalization properties, strongly depends on the choice of hyperparameters. While bilevel optimization offers a principled framework for hyperpa…

That some people find “text box that spits out a broken version of what they want and then you yell at it until it’s sufficing” more convenient than using existing tools says a lot more about existing tools than about the text box.
E.g. programming has long been extremely overwrought and complex for no reason other than enterprise wankery and gatekeeping, see the various frameworks from Big Tech.
The same companies now rent you expensive tools that “make programming easy”, while their overly complex frameworks and environments are free of course.
Instead of fixing the problem we’re now having two problems.
(The same is true in other industries.)

@… yeah, that’s a good take. it also has me wondering if the project has sufficient staffing. sometimes those post-acquisition things can get kinda lean due to leadership problems

Pseudo-MDPs: A Novel Framework for Efficiently Optimizing Last Revealer Seed Manipulations in Blockchains
Maxime Reynouard
https://arxiv.org/abs/2510.07080 https://

Pseudo-MDPs: A Novel Framework for Efficiently Optimizing Last Revealer Seed Manipulations in Blockchains
This study tackles the computational challenges of solving Markov Decision Processes (MDPs) for a restricted class of problems. It is motivated by the Last Revealer Attack (LRA), which undermines fairness in some Proof-of-Stake (PoS) blockchains such as Ethereum (\$400B market capitalization). We introduce pseudo-MDPs (pMDPs) a framework that naturally models such problems and propose two distinct problem reductions to standard MDPs. One problem reduction provides a novel, counter-intuitive per…

A unified theory of the high-dimensional Laplace approximation with application to Bayesian inverse problems
Anya Katsevich, Vladimir Spokoiny
https://arxiv.org/abs/2509.07952 h…

A unified theory of the high-dimensional Laplace approximation with application to Bayesian inverse problems
The Laplace approximation (LA) to posteriors is a ubiquitous tool to simplify Bayesian computation, particularly in the high-dimensional settings arising in Bayesian inverse problems. Precisely quantifying the LA accuracy is a challenging problem in the high-dimensional regime. We develop a theory of the LA accuracy to high-dimensional posteriors which both subsumes and unifies a number of results in the literature. The primary advantage of our theory is that we introduce a new degree of flexib…

UPS is 'disposing of' U.S.-bound packages over customs paperwork problems (Kayla Steinberg/NBC News)
https://www.nbcnews.com/business/business-news/ups-delay-customs-tariffs-packages-destroyed-rcna236607
http://www.memeorandum.com/251010/p38#a251010p38

“Artificially complex structures […] pose a number of practical and intellectual problems; man is responsible for their synthesis, regulation, and continued maintenance. In almost no instance can artificial-rational systems be built and left alone. They require continued attention, rebuilding, and repair. Eternal vigilance is the price of artificial complexity.”
—Langdon Winner (1977), Autonomous Technology, p. 183

“Artificially complex structures […] pose a number of practical and intellectual problems; man is responsible for their synthesis, regulation, and continued maintenance. In almost no instance can artificial-rational systems be built and left alone. They require continued attention, rebuilding, and repair. Eternal vigilance is the price of artificial complexity.”
—Langdon Winner (1977), Autonomous Technology, p. 183

“Artificially complex structures […] pose a number of practical and intellectual problems; man is responsible for their synthesis, regulation, and continued maintenance. In almost no instance can artificial-rational systems be built and left alone. They require continued attention, rebuilding, and repair. Eternal vigilance is the price of artificial complexity.”
—Langdon Winner (1977), Autonomous Technology, p. 183

Procrustes Problems on Random Matrices
Hajg Jasa, Ronny Bergmann, Christian K\"ummerle, Avanti Athreya, Zachary Lubberts
https://arxiv.org/abs/2510.05182 https://

Procrustes Problems on Random Matrices
Meaningful comparison between sets of observations often necessitates alignment or registration between them, and the resulting optimization problems range in complexity from those admitting simple closed-form solutions to those requiring advanced and novel techniques. We compare different Procrustes problems in which we align two sets of points after various perturbations by minimizing the norm of the difference between one matrix and an orthogonal transformation of the other. The minimization…

#FotoVorschlag 'Stressabbau' 'stress relief'
Well, definitely! I'm so grateful that I have hiking and cycling for stress relief. Especially hiking in the mountains when I'm just so physically exhausted that I can't think about my daily problems any more. Plus the overwhelming visual impressions.
To me, this kind of sports isn't a hobby any more. …

Variational Quantum Circuits in Offline Contextual Bandit Problems
Lukas Schulte, Daniel Hein, Steffen Udluft, Thomas A. Runkler
https://arxiv.org/abs/2509.07633 https://…

Variational Quantum Circuits in Offline Contextual Bandit Problems
This paper explores the application of variational quantum circuits (VQCs) for solving offline contextual bandit problems in industrial optimization tasks. Using the Industrial Benchmark (IB) environment, we evaluate the performance of quantum regression models against classical models. Our findings demonstrate that quantum models can effectively fit complex reward functions, identify optimal configurations via particle swarm optimization (PSO), and generalize well in noisy and sparse datasets.…

A Higher-Order Time Domain Boundary Element Formulation based on Isogeometric Analysis and the Convolution Quadrature Method
Thomas Kramer, Benjamin Marussig, Martin Schanz
https://arxiv.org/abs/2510.06804

A Higher-Order Time Domain Boundary Element Formulation based on Isogeometric Analysis and the Convolution Quadrature Method
An isogeometric boundary element method (BEM) is presented to solve scattering problems in an isotropic homogeneous medium. We consider wave problems governed by the scalar wave equation as in acoustics and the Lamé-Navier equations for elastodynamics considering the theory of linear elasticity. The underlying boundary integral equations imply time-dependent convolution integrals and allow us to determine the sought quantities in the bounded interior or the unbounded exterior after solving for…

Relaying for a friend and colleague
Sr. Network Engineer (Akamai) - US based Remote person. The role is on the the Akamai backbone network engineering team. If you have experience with large scale MPLS and Traffic Engineering and would like to works on some large scale networking problems... https://jobs.akamai.com/en/sit…

Causal Multi-fidelity Surrogate Forward and Inverse Models for ICF Implosions
Tyler E. Maltba, Ben S. Southworth, Jeffrey R. Haack, Marc L. Klasky
https://arxiv.org/abs/2509.05510

Causal Multi-fidelity Surrogate Forward and Inverse Models for ICF Implosions
Continued progress in inertial confinement fusion (ICF) requires solving inverse problems relating experimental observations to simulation input parameters, followed by design optimization. However, such high dimensional dynamic PDE-constrained optimization problems are extremely challenging or even intractable. It has been recently shown that inverse problems can be solved by only considering certain robust features. Here we consider the ICF capsule's deuterium-tritium (DT) interface, and cons…

Using Erd\H{o}s's methods to study Yorke's problems
Eran Igra, Valerii Sopin
https://arxiv.org/abs/2509.06852 https://arxiv.org/pdf/2509.06852

Using Erdős's methods to study Yorke's problems
In this paper, we study the possible bifurcations of periodic orbits by reducing them to graphs. The aforementioned allows to study the genericity of routes to chaos, as well as to analyze their possible complexity. In particular, our results show that there is no upper bound on the possible complexity. Moreover, it suggests general fermionic description via the virial expansion and universal description via the Rado graph.

Thermal Imaging Survey: DIY vs Professional - Learn how a thermal imaging survey can spot real problems. What does it cost? Is a trained operator useful? #thermalImaging #cutCarbon -

Thermal Imaging Survey: DIY vs Professional
Learn how a thermal imaging survey can spot real problems. What does it cost? Is a trained operator useful? #thermalImaging #cutCarbon

Deep Distillation Gradient Preconditioning for Inverse Problems
Romario Gualdr\'on-Hurtado, Roman Jacome, Leon Suarez, Laura Galvis, Henry Arguello
https://arxiv.org/abs/2508.04832

Deep Distillation Gradient Preconditioning for Inverse Problems
Imaging inverse problems are commonly addressed by minimizing measurement consistency and signal prior terms. While huge attention has been paid to developing high-performance priors, even the most advanced signal prior may lose its effectiveness when paired with an ill-conditioned sensing matrix that hinders convergence and degrades reconstruction quality. In optimization theory, preconditioners allow improving the algorithm's convergence by transforming the gradient update. Traditional linear…

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial
Bisheng Wei, Ruihong Jiang, Ruichen Zhang, Yinqiu Liu, Dusit Niyato, Yaohua Sun, Yang Lu, Yonghui Li, Shiwen Mao, Chau Yuen, Marco Di Renzo, Mugen Peng
https://arxiv.org/abs/2509.05946

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial
The rapid advancement toward sixth-generation (6G) wireless networks has significantly intensified the complexity and scale of optimization problems, including resource allocation and trajectory design, often formulated as combinatorial problems in large discrete decision spaces. However, traditional optimization methods, such as heuristics and deep reinforcement learning (DRL), struggle to meet the demanding requirements of real-time adaptability, scalability, and dynamic handling of user inte…

State Constrained Optimal Control Problems With Control On The Acceleration. Applications To Kinetic Mean Field Games
Yves Achdou (LJLL)
https://arxiv.org/abs/2510.07332 https:/…

State Constrained Optimal Control Problems With Control On The Acceleration. Applications To Kinetic Mean Field Games
Relying on the careful study of a related problem in the calculus of variations, we study a class of optimal control problems in which the control lies on the acceleration, with state constraints on the position variable. In dimension one, we find explicit formulas in the special case when the running cost is a power of the acceleration (in absolute value) and the terminal cost is zero. For more general costs or/and higher dimensions, we study the singularities of the value function. We also pr…

"I would like to propose that IPs of [NTP] pool-members should not be allowed to host [Tor exit nodes] simultaneously under the same IP."
or put another way, "my employer paid for this whizzy firewall but it complains when we make it talk to a free service run by a volunteer because of other software the volunteer runs. Please educate your volunteers about how they need to go about providing this free service to us."

⛹🏻‍♀️ Ball mill technique produces nanoscale scaffolds that filter PFAS
#pfas …

Ball mill technique produces nanoscale scaffolds that filter PFAS
PFAS are fluorinated compounds found in many everyday products, such as outdoor clothing and cookware like Teflon pans. This is because PFAS are durable, heat-resistant and dirt-repellent. Their stability is precisely what leads to problems: although potentially harmful to our health, these substances are scarcely broken down at all in the environment and are regarded as "forever chemicals." PFAS are also found in wastewater. Although they can be removed by filtration, this is a laborious proce…

Conditional McKean-Vlasov control
Ren\'e Carmona, Ludovic Tangpi, Kaiwen Zhang
https://arxiv.org/abs/2510.06543 https://arxiv.org/pdf/2510.06543…

Conditional McKean-Vlasov control
Conditional McKean-Vlasov control problems involve controlling McKean-Vlasov diffusions where the interaction occurs through the law of the state process conditionally on it staying in a domain. Introduced by Lions in his 2016 lectures at the Collège de France, these problems have notable applications, particularly in systemic risk. We establish well-posedness and provide a general characterization of optimal controls using a new Pontryagin maximum principle in the probabilistic weak formulati…

A Graph Width Perspective on Partially Ordered Hamiltonian Paths and Cycles II: Vertex and Edge Deletion Numbers
Jesse Beisegel, Katharina Klost, Kristin Knorr, Fabienne Ratajczak, Robert Scheffler
https://arxiv.org/abs/2510.08378

A Graph Width Perspective on Partially Ordered Hamiltonian Paths and Cycles II: Vertex and Edge Deletion Numbers
We consider the problem of finding a Hamiltonian path or cycle with precedence constraints in the form of a partial order on the vertex set. We study the complexity for graph width parameters for which the ordinary problems $\mathsf{Hamiltonian\ Path}$ and $\mathsf{Hamiltonian\ Cycle}$ are in $\mathsf{FPT}$. In particular, we focus on parameters that describe how many vertices and edges have to be deleted to become a member of a certain graph class. We show that the problems are $\mathsf{W[1]}$…

*sigh*
Darn those chicken and egg problems.
Killed my 3d-printer's hotend probably by over tightening the nozzle, about to change to another cold/hotend but only now discover that I need two different print head parts. But right now, I don't have a printer capable of printing ABS/ASA...
Anyone with a #3d

MRI-Based Brain Tumor Detection through an Explainable EfficientNetV2 and MLP-Mixer-Attention Architecture
Mustafa Yurdakul, \c{S}akir Ta\c{s}demir
https://arxiv.org/abs/2509.06713

MRI-Based Brain Tumor Detection through an Explainable EfficientNetV2 and MLP-Mixer-Attention Architecture
Brain tumors are serious health problems that require early diagnosis due to their high mortality rates. Diagnosing tumors by examining Magnetic Resonance Imaging (MRI) images is a process that requires expertise and is prone to error. Therefore, the need for automated diagnosis systems is increasing day by day. In this context, a robust and explainable Deep Learning (DL) model for the classification of brain tumors is proposed. In this study, a publicly available Figshare dataset containing 3,…

Cowboys-Rams joint practice: Micah Parsons is missed, CeeDee Lamb-George Pickens duo causing 'problems'

https://www.cbssports.com/nfl/news/cowboys…

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation
Shalev Manor, Mohammad Kohandel
https://arxiv.org/abs/2509.07245 https://arxiv.org/pdf/2…

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation
Solving inverse problems with Physics-Informed Neural Networks (PINNs) is computationally expensive for multi-query scenarios, as each new set of observed data requires a new, expensive training procedure. We present Inverse-Parameter Basis PINNs (IP-Basis PINNs), a meta-learning framework that extends the foundational work of Desai et al. (2022) to enable rapid and efficient inference for inverse problems. Our method employs an offline-online decomposition: a deep network is first trained offl…

Solving unimportant problems with poorly-supported browser APIs.
https://www.rossng.eu/posts/2025-08-09-where-should-i-aim/

Forward and inverse problems of a semilinear transport equation
Kui Ren, Yimin Zhong
https://arxiv.org/abs/2509.06183 https://arxiv.org/pdf/2509.06183

Forward and inverse problems of a semilinear transport equation
We study forward and inverse problems for a semilinear radiative transport model where the absorption coefficient depends on the angular average of the transport solution. Our first result is the well-posedness theory for the transport model with general boundary data, which significantly improves previous theories for small boundary data. For the inverse problem of reconstructing the nonlinear absorption coefficient from internal data, we develop stability results for the reconstructions and u…

Sequential symmetric interior penalty discontinuous Galerkin method for fully coupled quasi-static thermo-poroelasticity problems
Fan Chen, Ming Cui, Chenguang Zhou
https://arxiv.org/abs/2509.06480

Sequential symmetric interior penalty discontinuous Galerkin method for fully coupled quasi-static thermo-poroelasticity problems
In this paper, we investigate a sequentially decoupled numerical method for solving the fully coupled quasi-static thermo-poroelasticity problems with nonlinear convective transport. The symmetric interior penalty discontinuous Galerkin method is employed for spatial discretization and the backward Euler method for temporal discretization. Unlike other splitting algorithms, this type of sequential method does not require any internal iterations and the computational efficiency is higher than th…

MathSmith: Towards Extremely Hard Mathematical Reasoning by Forging Synthetic Problems with a Reinforced Policy
Shaoxiong Zhan, Yanlin Lai, Ziyu Lu, Dahua Lin, Ziqing Yang, Fei Tang
https://arxiv.org/abs/2508.05592

MathSmith: Towards Extremely Hard Mathematical Reasoning by Forging Synthetic Problems with a Reinforced Policy
Large language models have achieved substantial progress in mathematical reasoning, yet their advancement is limited by the scarcity of high-quality, high-difficulty training data. Existing synthesis methods largely rely on transforming human-written templates, limiting both diversity and scalability. We propose MathSmith, a novel framework for synthesizing challenging mathematical problems to enhance LLM reasoning. Rather than modifying existing problems, MathSmith constructs new ones from scr…

"We notice that ads are not being displayed" popup. No, I don't mind ads. What I object to are those damned intrusive scripts vacuuming every bit of info. If you make it that I must allow the scripts to run to read the article, then I won't read it, and I block the site.
There are sites I allow ads because THEY RESPECT MY CHOICE. Generic ads I have zero problems with.

The (No) Value of Commitment
Nathan Hancart
https://arxiv.org/abs/2510.07994 https://arxiv.org/pdf/2510.07994

The (No) Value of Commitment
I provide a sufficient condition under which a principal does not benefit from committing to a mechanism in economic models represented by a maximisation problem under constraints. These problems include mechanism design, principal-agent models or sender-receiver games. In principal-agent problems, this condition holds if the agent has a finite strategy space and the principal's value function is continuous in the mechanism.

Inverse scattering problem for a cubic string having the shape of a step
Vladimir A. Zolotarev
https://arxiv.org/abs/2509.06417 https://arxiv.org/pdf/2509.…

Inverse scattering problem for a cubic string having the shape of a step
Problem for a cubic string having the shape of a step is studied. It is proved that here we have two scattering problems: the direct one and its dual. The direct problem describes scattering of the waves coming from ``$+\infty$'', and its dual, correspondingly, of the waves from ``$-\infty$''. The main systems of linear singular equations for both problems are obtained. It is shown how to unambiguously restore potential from the solutions to these equation systems.

Termination Analysis of Linear-Constraint Programs
Amir M. Ben-Amram, Samir Genaim, Jo\"el Ouaknine, James Worrell
https://arxiv.org/abs/2509.06752 https://

Termination Analysis of Linear-Constraint Programs
This Survey provides an overview of techniques in termination analysis for programs with numerical variables and transitions defined by linear constraints. This subarea of program analysis is challenging due to the existence of undecidable problems, and this Survey systematically explores approaches that mitigate this inherent difficulty. These include foundational decidability results, the use of ranking functions, and disjunctive well-founded transition invariants. The Survey also discusses n…

I have a problem. Need to validate config file
Using #cuelang
Now I have 2 errors in empty disjunction problems
#shitpost

New constructions and bounds for nonabelian Sidon sets with applications to Tur\'an-type problems
John Byrne, Michael Tait
https://arxiv.org/abs/2509.07750 https://

New constructions and bounds for nonabelian Sidon sets with applications to Turán-type problems
An $S_k$-set in a group $Γ$ is a set $A\subseteqΓ$ such that $α_1\cdotsα_k=β_1\cdotsβ_k$ with $α_i,β_i\in A$ implies $(α_1,\ldots,α_k)=(β_1,\ldots,β_k)$. An $S_k'$-set is a set such that $α_1β_1^{-1}\cdotsα_kβ_k^{-1}=1$ implies that there exists $i$ such that $α_i=β_i\text{ or }β_i=α_{i+1}$. We give explicit constructions of large $S_k$-sets in the group $S_n$ and $S_2$-sets in $S_n\times S_n$ and $A_n\times A_n$. We give probabilistic constructions for `nice' groups which o…

Exponential Error Bounds for Information Bottleneck Source Coding Problems
Han Wu, Hamdi Joudeh
https://arxiv.org/abs/2510.08364 https://arxiv.org/pdf/2510…

Exponential Error Bounds for Information Bottleneck Source Coding Problems
We study the information bottleneck (IB) source coding problem, also known as remote lossy source coding under logarithmic loss. Based on a rate-limited description of noisy observations, the receiver produces a soft estimate for the remote source, i.e., a probability distribution, evaluated under the logarithmic loss. We focus on the excess distortion probability of IB source coding and investigate how fast it converges to 0 or 1, depending on whether the rate is above or below the rate-distor…

MixReasoning: Switching Modes to Think
Haiquan Lu, Gongfan Fang, Xinyin Ma, Qi Li, Xinchao Wang
https://arxiv.org/abs/2510.06052 https://arxiv.org/pdf/2510…

MixReasoning: Switching Modes to Think
Reasoning models enhance performance by tackling problems in a step-by-step manner, decomposing them into sub-problems and exploring long chains of thought before producing an answer. However, applying extended reasoning to every step introduces substantial redundancy, as sub-problems vary widely in difficulty and complexity: a small number of pivotal steps are genuinely challenging and decisive for the final answer, while many others only involve straightforward revisions or simple computation…

Multi-level informed optimization via decomposed Kriging for large design problems under uncertainty
Enrico Ampellio, Blazhe Gjorgiev, Giovanni Sansavini
https://arxiv.org/abs/2510.07904

Multi-level informed optimization via decomposed Kriging for large design problems under uncertainty
Engineering design involves demanding models encompassing many decision variables and uncontrollable parameters. In addition, unavoidable aleatoric and epistemic uncertainties can be very impactful and add further complexity. The state-of-the-art adopts two steps, uncertainty quantification and design optimization, to optimize systems under uncertainty by means of robust or stochastic metrics. However, conventional scenario-based, surrogate-assisted, and mathematical programming methods are not…

Engineering Select Support for Hybrid Bitvectors
Eric Chiu, Dominik Kempa
https://arxiv.org/abs/2509.06900 https://arxiv.org/pdf/2509.06900

Engineering Select Support for Hybrid Bitvectors
One of the central problems in the design of compressed data structures is the efficient support for rank and select queries on bitvectors. These two operations form the backbone of more complex data structures (such as wavelet trees) used for the compact representation of texts, trees, graphs, or grids. Their efficient implementation is one of the most frequently studied problems in compressed data structures. One effective solution is the so-called hybrid bitvector implementation, which par…

Chebyshev smoothing with adaptive block-FSAI preconditioners for the multilevel solution of higher-order problems
Pablo Jim\'enez Recio, Marc Alexander Schweitzer
https://arxiv.org/abs/2509.06744

Chebyshev smoothing with adaptive block-FSAI preconditioners for the multilevel solution of higher-order problems
In this paper, we assess the performance of adaptive and nested factorized sparse approximate inverses as smoothers in multilevel V-cycles, when smoothing is performed following the Chebyshev iteration of the fourth kind. For our test problems, we rely on the partition of unity method to discretize the biharmonic and triharmonic equations in a multilevel manner. Inspired by existing algorithms, we introduce a new adaptive algorithm for the construction of sparse approximate inverses, based on t…

Tensor Network Loop Cluster Expansions for Quantum Many-Body Problems
Johnnie Gray, Gunhee Park, Glen Evenbly, Nicola Pancotti, Garnet Kin-Lic Chan
https://arxiv.org/abs/2510.05647

Tensor Network Loop Cluster Expansions for Quantum Many-Body Problems
We analyze the tensor network loop cluster expansion, introduced in arXiv:2504.07344 as a systematic correction to belief propagation, in the context of general quantum many-body problems. We provide numerical examples of the accuracy and practical applicability of the approach for the computation of ground-state observables for high bond dimension tensor networks, in two- and three-dimensions, with open and periodic boundary conditions, and for spin and fermion problems.

Inertial accelerated primal-dual algorithms for non-smooth convex optimization problems with linear equality constraints
Huan Zhang, Xiangkai Sun, Shengjie Li, Kok Lay Teo
https://arxiv.org/abs/2509.07306

Inertial accelerated primal-dual algorithms for non-smooth convex optimization problems with linear equality constraints
This paper is devoted to the study of an inertial accelerated primal-dual algorithm, which is based on a second-order differential system with time scaling, for solving a non-smooth convex optimization problem with linear equality constraints. We first introduce a second-order differential system with time scaling associated with the non-smooth convex optimization problem, and then obtain fast convergence rates for the primal-dual gap, the feasibility violation, and the objective residual along…

A deep multiple instance learning approach based on coarse labels for high-resolution land-cover mapping
Gianmarco Perantoni, Lorenzo Bruzzone
https://arxiv.org/abs/2510.06769 h…

A deep multiple instance learning approach based on coarse labels for high-resolution land-cover mapping
The quantity and the quality of the training labels are central problems in high-resolution land-cover mapping with machine-learning-based solutions. In this context, weak labels can be gathered in large quantities by leveraging on existing low-resolution or obsolete products. In this paper, we address the problem of training land-cover classifiers using high-resolution imagery (e.g., Sentinel-2) and weak low-resolution reference data (e.g., MODIS -derived land-cover maps). Inspired by recent w…

On graphs, homology bases, and triangulated homology spheres
Karim Adiprasito, Marc Lackenby, Juan Souto, Geva Yashfe
https://arxiv.org/abs/2509.06275 https://

On graphs, homology bases, and triangulated homology spheres
We describe a construction that takes as input a graph and a basis for its first homology, and returns a triangulation of a 3-dimensional homology sphere. This makes precise an idea of M. Gromov and A. Nabutovski. The immediate application, essentially described by Gromov, is to translate problems about asymptotics of homology sphere triangulations to asymptotic counting problems for constant-degree graphs with "short" homology bases. We construct families of 3- sphere triangulations with dual …

Mass-Lumped Virtual Element Method with Strong Stability-Preserving Runge-Kutta Time Stepping for Two-Dimensional Parabolic Problems
Paulo Akira F. Enabe, Rodrigo Provasi
https://arxiv.org/abs/2510.06653

Mass-Lumped Virtual Element Method with Strong Stability-Preserving Runge-Kutta Time Stepping for Two-Dimensional Parabolic Problems
This paper presents a mass-lumped Virtual Element Method (VEM) with explicit Strong Stability-Preserving Runge-Kutta (SSP-RK) time integration for two-dimensional parabolic problems on general polygonal meshes. A diagonal mass matrix is constructed via row-sum operations combined with flooring to ensure uniform positivity. Stabilization terms vanish identically under row summation, so the lumped weights derive solely from the $L^2$ projector and are computable through a small polynomial system …

Online Matching via Reinforcement Learning: An Expert Policy Orchestration Strategy
Chiara Mignacco, Matthieu Jonckheere, Gilles Stoltz
https://arxiv.org/abs/2510.06515 https://…

Online Matching via Reinforcement Learning: An Expert Policy Orchestration Strategy
Online matching problems arise in many complex systems, from cloud services and online marketplaces to organ exchange networks, where timely, principled decisions are critical for maintaining high system performance. Traditional heuristics in these settings are simple and interpretable but typically tailored to specific operating regimes, which can lead to inefficiencies when conditions change. We propose a reinforcement learning (RL) approach that learns to orchestrate a set of such expert pol…

@… hopefully we can get some workflow improvements to npm to avoid or at least better mitigate these problems

Quasilinear problems with critical Sobolev exponent for the Grushin p-Laplace operator
Somnath Gandal, Annunziata Loiudice, Jagmohan Tyagi
https://arxiv.org/abs/2509.06138 https…

Quasilinear problems with critical Sobolev exponent for the Grushin p-Laplace operator
We study the following class of quasilinear degenerate elliptic equations with critical nonlinearity \begin{align*} \begin{cases}-Δ_{γ,p} u= λ|u|^{q-2}u+|u|^{p_γ^{*}-2}u & \text{ in } Ω\subset \mathbb{R}^N, \\ u=0 & \text{ on } \partial Ω, \end{cases} \end{align*} where $Δ_{γ, p}v:=\sum_{i=1}^N X_i(|\nabla_γu|^{p-2}X_i u)$ is the Grushin $p$-Laplace operator, $z:=(x, y) \in \mathbb{R}^N$, $N=m+n,$ $m,n \geq 1,$, where $\nabla_γ=(X_1, \ldots, X_N)$ is th…

Dimension Reduction for Clustering: The Curious Case of Discrete Centers
Shaofeng H. -C. Jiang, Robert Krauthgamer, Shay Sapir, Sandeep Silwal, Di Yue
https://arxiv.org/abs/2509.07444

Dimension Reduction for Clustering: The Curious Case of Discrete Centers
The Johnson-Lindenstrauss transform is a fundamental method for dimension reduction in Euclidean spaces, that can map any dataset of $n$ points into dimension $O(\log n)$ with low distortion of their distances. This dimension bound is tight in general, but one can bypass it for specific problems. Indeed, tremendous progress has been made for clustering problems, especially in the \emph{continuous} setting where centers can be picked from the ambient space $\mathbb{R}^d$. Most notably, for $k$-m…

Fine-Grained Unambiguous Measurements
Quentin Buzet, Andr\'e Chailloux
https://arxiv.org/abs/2510.07298 https://arxiv.org/pdf/2510.07298

Fine-Grained Unambiguous Measurements
Unambiguous measurements play an important role in quantum information, with applications ranging from quantum key distribution to quantum state reconstruction. Recently, such measurements have also been used in quantum algorithms based on Regev's reduction. The key problem for these algorithms is the S-LWE problem for lattice problems, or the Quantum Decoding Problem for code problems. A key idea for addressing this problem is to use unambiguous measurements to recover $k$ coordinates of a cod…

Existence of Solutions and Relative Regularity Conditions for Polynomial Vector Optimization Problems
Danyang Liu
https://arxiv.org/abs/2508.04991 https://…

Existence of Solutions and Relative Regularity Conditions for Polynomial Vector Optimization Problems
In this paper, we establish the existence of the efficient solutions for polynomial vector optimization problems on a nonempty closed constraint set without any convexity and compactness assumptions. We first introduce the relative regularity conditions for vector optimization problems whose objective functions are a vector polynomial and investigate their properties and characterizations. Moreover, we establish relationships between the relative regularity conditions, Palais-Smale condition, w…

EfficientNet in Digital Twin-based Cardiac Arrest Prediction and Analysis
Qasim Zia, Avais Jan, Zafar Iqbal, Muhammad Mumtaz Ali, Mukarram Ali, Murray Patterson
https://arxiv.org/abs/2509.07388

EfficientNet in Digital Twin-based Cardiac Arrest Prediction and Analysis
Cardiac arrest is one of the biggest global health problems, and early identification and management are key to enhancing the patient's prognosis. In this paper, we propose a novel framework that combines an EfficientNet-based deep learning model with a digital twin system to improve the early detection and analysis of cardiac arrest. We use compound scaling and EfficientNet to learn the features of cardiovascular images. In parallel, the digital twin creates a realistic and individualized card…

Autoformalizer with Tool Feedback
Qi Guo, Jianing Wang, Jianfei Zhang, Deyang Kong, Xiangzhou Huang, Xiangyu Xi, Wei Wang, Jingang Wang, Xunliang Cai, Shikun Zhang, Wei Ye
https://arxiv.org/abs/2510.06857

Autoformalizer with Tool Feedback
Autoformalization addresses the scarcity of data for Automated Theorem Proving (ATP) by translating mathematical problems from natural language into formal statements. Efforts in recent work shift from directly prompting large language models to training an end-to-end formalizer model from scratch, achieving remarkable advancements. However, existing formalizer still struggles to consistently generate valid statements that meet syntactic validity and semantic consistency. To address this issue,…

Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search
Xin Lai, Junyi Li, Wei Li, Tao Liu, Tianjian Li, Hengshuang Zhao
https://arxiv.org/abs/2509.07969 …

Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search
Recent advances in large multimodal models have leveraged image-based tools with reinforcement learning to tackle visual problems. However, existing open-source approaches often exhibit monotonous reasoning patterns and allow only a limited number of interaction turns, making them inadequate for difficult tasks that require trial-and-error exploration. In this work, we address this limitation by scaling up tool-based interactions and introduce Mini-o3, a system that executes deep, multi-turn re…

Vertex-ordering and arc-partitioning problems
N\'ora A. Borsik, P\'eter Madarasi
https://arxiv.org/abs/2509.05245 https://arxiv.org/pdf/2509.05245

Vertex-ordering and arc-partitioning problems
We study vertex-ordering problems in loop-free digraphs subject to constraints on the left-going arcs, focusing on existence conditions and computational complexity. As an intriguing special case, we explore vertex-specific lower and upper bounds on the left-outdegrees and right-indegrees. We show, for example, that deciding whether the left-going arcs can form an in-branching is solvable in polynomial time and provide a necessary and sufficient condition, while the analogous problem for an in-…

AI Knowledge Assist: An Automated Approach for the Creation of Knowledge Bases for Conversational AI Agents
Md Tahmid Rahman Laskar, Julien Bouvier Tremblay, Xue-Yong Fu, Cheng Chen, Shashi Bhushan TN
https://arxiv.org/abs/2510.08149

AI Knowledge Assist: An Automated Approach for the Creation of Knowledge Bases for Conversational AI Agents
The utilization of conversational AI systems by leveraging Retrieval Augmented Generation (RAG) techniques to solve customer problems has been on the rise with the rapid progress of Large Language Models (LLMs). However, the absence of a company-specific dedicated knowledge base is a major barrier to the integration of conversational AI systems in contact centers. To this end, we introduce AI Knowledge Assist, a system that extracts knowledge in the form of question-answer (QA) pairs from histo…

@… something needs to change or folks are going to hop off of the package manager train (and then we’ll have worse problems due to folks not updating things)

Conic optimization for extremal geometry
Frank Vallentin
https://arxiv.org/abs/2510.06960 https://arxiv.org/pdf/2510.06960…

Conic optimization for extremal geometry
The aim of this paper is to highlight recent progress in using conic optimization methods to study geometric packing problems. We will look at four geometric packing problems of different kinds: two on the unit sphere -- the kissing number problem and measurable $π/2$-avoiding sets -- and two in Euclidean space -- the sphere packing problem and measurable one-avoiding sets.

Symmetry-Aware Fully-Amortized Optimization with Scale Equivariant Graph Metanetworks
Bart Kuipers, Freek Byrman, Daniel Uyterlinde, Alejandro Garc\'ia-Castellanos
https://arxiv.org/abs/2510.08300 …

Symmetry-Aware Fully-Amortized Optimization with Scale Equivariant Graph Metanetworks
Amortized optimization accelerates the solution of related optimization problems by learning mappings that exploit shared structure across problem instances. We explore the use of Scale Equivariant Graph Metanetworks (ScaleGMNs) for this purpose. By operating directly in weight space, ScaleGMNs enable single-shot fine-tuning of existing models, reducing the need for iterative optimization. We demonstrate the effectiveness of this approach empirically and provide a theoretical result: the gauge …

Algorithm for constructing optimal explicit finite-difference formulas in the Hilbert space
R. S. Karimov, D. D. Atoev
https://arxiv.org/abs/2510.06643 https://

Algorithm for constructing optimal explicit finite-difference formulas in the Hilbert space
This work presents problems of constructing finite-difference formulas in the Hilbert space, i.e., setting problems of constructing finite-difference formulas using functional methods. The work presents a functional statement of the problem of optimizing finite-difference formulas in the space $W_{2}^{\left(m,m-1\right)} \left(0,1\right)$. Here, representations of optimal coefficients of explicit finite-difference formulas of the Adams type on classes $W_{2}^{\left(m,m-1\right)} \left(0,1\right…

A unified optimal control framework: time-optimal control and stochastic optimal control
Shuzhen Yang
https://arxiv.org/abs/2510.07765 https://arxiv.org/pd…

A unified optimal control framework: time-optimal control and stochastic optimal control
In this paper, we propose a unified stochastic optimal control framework that bridges time-optimal control problems and classical stochastic optimal control problems. Unlike traditional deterministic time-optimal control formulations, our framework incorporates a generalized stochastic control structure under minimum-time constraints. Here, the minimum-time condition characterizes the earliest achievable moment for reaching a target state in expectation, rendering the terminal time an endogenou…

MM-HELIX: Boosting Multimodal Long-Chain Reflective Reasoning with Holistic Platform and Adaptive Hybrid Policy Optimization
Xiangyu Zhao, Junming Lin, Tianhao Liang, Yifan Zhou, Wenhao Chai, Yuzhe Gu, Weiyun Wang, Kai Chen, Gen Luo, Wenwei Zhang, Junchi Yan, Hua Yang, Haodong Duan, Xue Yang
https://arxiv.org/abs/2510.08540

MM-HELIX: Boosting Multimodal Long-Chain Reflective Reasoning with Holistic Platform and Adaptive Hybrid Policy Optimization
While current Multimodal Large Language Models (MLLMs) have demonstrated proficiency in reasoning tasks such as mathematics and logic, their capacity for long-chain reflective reasoning, a prerequisite for solving complex real-world problems, remains largely underexplored. In this work, we first conduct an extensive empirical investigation to evaluate this capability. Leveraging a carefully designed data synthesis engine, we construct MM-HELIX, a multimodal benchmark consisting 1,260 samples of…

ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy Shaping
Shuang Chen, Yue Guo, Yimeng Ye, Shijue Huang, Wenbo Hu, Haoxi Li, Manyuan Zhang, Jiayu Chen, Song Guo, Nanyun Peng
https://arxiv.org/abs/2510.08457

ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy Shaping
Recent advances in multimodal large reasoning models (MLRMs) have substantially improved their ability to solve complex textual and visual tasks. However, these models tend to overthink on simple problems, producing unnecessarily lengthy reasoning traces, while under-exploring on challenging ones, leading to missed solutions. To address this imbalance, we propose ARES, a unified open-source framework for adaptive reasoning that dynamically allocates exploration effort based on task difficulty. …

Parameterized complexity of isometric path partition: treewidth and diameter
Dibyayan Chakraborty, Oscar Defrain, Florent Foucaud, Mathieu Mari, Prafullkumar Tale
https://arxiv.org/abs/2508.05448

Parameterized complexity of isometric path partition: treewidth and diameter
We investigate the parameterized complexity of the Isometric Path Partition problem when parameterized by the treewidth ($\mathrm{tw}$) of the input graph, arguably one of the most widely studied parameters. Courcelle's theorem shows that graph problems that are expressible as MSO formulas of constant size admit FPT algorithms parameterized by the treewidth of the input graph. This encompasses many natural graph problems. However, many metric-based graph problems, where the solution is defined …

h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
Sumeet Ramesh Motwani, Alesia Ivanova, Ziyang Cai, Philip Torr, Riashat Islam, Shital Shah, Christian Schroeder de Witt, Charles London
https://arxiv.org/abs/2510.07312

h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
Large language models excel at short-horizon reasoning tasks, but performance drops as reasoning horizon lengths increase. Existing approaches to combat this rely on inference-time scaffolding or costly step-level supervision, neither of which scales easily. In this work, we introduce a scalable method to bootstrap long-horizon reasoning capabilities using only existing, abundant short-horizon data. Our approach synthetically composes simple problems into complex, multi-step dependency chains o…

Regularity of solutions to degenerate and singular free boundary problems with volume constraint
T. M. Nascimento, X. H. Nguyen, P. R. Stinga
https://arxiv.org/abs/2508.04856 ht…

Regularity of solutions to degenerate and singular free boundary problems with volume constraint
We prove existence and regularity of solutions to degenerate and singular elliptic free boundary problems, where the volume of the positivity set of the solution is prescribed.

On the B-subdifferential of proximal operators of affine-constrained $\ell_1$ regularizer
Xudong Li, Meixia Lin, Kim-Chuan Toh
https://arxiv.org/abs/2510.06642 https://

On the B-subdifferential of proximal operators of affine-constrained $\ell_1$ regularizer
In this work, we study the affine-constrained $\ell_1$ regularizers, which frequently arise in statistical and machine learning problems across a variety of applications, including microbiome compositional data analysis and sparse subspace clustering. With the aim of developing scalable second-order methods for solving optimization problems involving such regularizers, we analyze the associated proximal mapping and characterize its generalized differentiability, with a focus on its B-subdiffere…

Beyond Pass@k: Breadth-Depth Metrics for Reasoning Boundaries
Marius Dragoi, Ioana Pintilie, Florin Gogianu, Florin Brad
https://arxiv.org/abs/2510.08325 https://

Beyond Pass@k: Breadth-Depth Metrics for Reasoning Boundaries
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful paradigm to improve Large Language Models on reasoning tasks such as coding, math or logic. To assess the reasoning boundary (the fraction of problems a model can solve) researchers often report Pass@k at large sampling budgets. Recent results reveal a crossover phenomenon: while RLVR models outperform the base model at small k values, the base model usually outperforms them when sampling a very large number of comp…

Fast Multipole Method with Complex Coordinates
Tristan Goodwill, Leslie Greengard, Jeremy Hoskins, Manas Rachh, Yuguan Wang
https://arxiv.org/abs/2509.05458 https://

Fast Multipole Method with Complex Coordinates
In this work we present a variant of the fast multipole method (FMM) for efficiently evaluating standard layer potentials on geometries with complex coordinates in two and three dimensions. The complex scaled boundary integral method for the efficient solution of scattering problems on unbounded domains results in complex point locations upon discretization. Classical real-coordinate FMMs are no longer applicable, hindering the use of this approach for large-scale problems. Here we develop the …

Quantum approximate optimization of bosonic finite-state systems
Shakib Daryanoosh
https://arxiv.org/abs/2510.05576 https://arxiv.org/pdf/2510.05576…

Quantum approximate optimization of bosonic finite-state systems
There exist numerous problems in nature inherently described by finite $D$-dimensional states. Formulating these problems for execution on qubit-based quantum hardware requires mapping the qudit Hilbert space to that of multiqubit which may be exponentially larger. To exclude the infeasible subspace, one common approach relies on penalizing the objective function. However, this strategy can be inefficient as the size of the illegitimate subspace grows. Here we propose to employ the Hamiltonian-…

Adaptive LLM-Symbolic Reasoning via Dynamic Logical Solver Composition
Lei Xu, Pierre Beckmann, Marco Valentino, Andr\'e Freitas
https://arxiv.org/abs/2510.06774 https://

Adaptive LLM-Symbolic Reasoning via Dynamic Logical Solver Composition
Neuro-symbolic NLP methods aim to leverage the complementary strengths of large language models and formal logical solvers. However, current approaches are mostly static in nature, i.e., the integration of a target solver is predetermined at design time, hindering the ability to employ diverse formal inference strategies. To address this, we introduce an adaptive, multi-paradigm, neuro-symbolic inference framework that: (1) automatically identifies formal reasoning strategies from problems expr…

RIMO: An Easy-to-Evaluate, Hard-to-Solve Olympiad Benchmark for Advanced Mathematical Reasoning
Ziye Chen, Chengwei Qin, Yao Shu
https://arxiv.org/abs/2509.07711 https://…

RIMO: An Easy-to-Evaluate, Hard-to-Solve Olympiad Benchmark for Advanced Mathematical Reasoning
As large language models (LLMs) reach high scores on established mathematical benchmarks, such as GSM8K and MATH, the research community has turned to International Mathematical Olympiad (IMO) problems to push the evaluation frontier. However, existing Olympiad-level benchmarks suffer from practical constraints that introduce grading noise and potential bias, such as heterogeneous answer formats requiring model-based judges and a reliance on potentially flawed solutions. We introduce RIMO, a tw…

Existence and nonexistence of commutativity gadgets for entangled CSPs
Eric Culf, Josse van Dobben de Bruyn, Matthijs Vernooij, Peter Zeman
https://arxiv.org/abs/2509.07835 http…

Existence and nonexistence of commutativity gadgets for entangled CSPs
Commutativity gadgets allow NP-hardness proofs for classical constraint satisfaction problems (CSPs) to be carried over to undecidability proofs for the corresponding entangled CSPs. This has been done, for instance, for NP-complete boolean CSPs and 3-colouring in the work of Culf and Mastel. For many CSPs over larger alphabets, including $k$-colouring when $k \geq 4$, it is not known whether or not commutativity gadgets exist, or if the entangled CSP is decidable. In this paper, we study commu…

Universal Representation of Generalized Convex Functions and their Gradients
Moeen Nehzati
https://arxiv.org/abs/2509.04477 https://arxiv.org/pdf/2509.0447…

Universal Representation of Generalized Convex Functions and their Gradients
Solutions to a wide range of optimization problems, from optimal transport theory to mathematical economics, often take the form of generalized convex functions (GCFs). This characterization can be used to convert nested bilevel optimization problems into single-level optimization problems. Despite this, the characterization has not been fully exploited in numerical optimization. When the solution to an optimization problem is known to belong to a particular class of objects, this information…

CP-Model-Zoo: A Natural Language Query System for Constraint Programming Models
Augustin Crespin, Ioannis Kostis, H\'el\`ene Verhaeghe, Pierre Schaus
https://arxiv.org/abs/2509.07867

CP-Model-Zoo: A Natural Language Query System for Constraint Programming Models
Constraint Programming and its high-level modeling languages have long been recognized for their potential to achieve the holy grail of problem-solving. However, the complexity of modeling languages, the large number of global constraints, and the art of creating good models have often hindered non-experts from choosing CP to solve their combinatorial problems. While generating an expert-level model from a natural-language description of a problem would be the dream, we are not yet there. We pr…

On the Quantum Equivalence between $S|LWE\rangle$ and $ISIS$
Andr\'e Chailloux, Paul Hermouet
https://arxiv.org/abs/2510.06097 https://arxiv.org/pdf/25…

On the Quantum Equivalence between $S|LWE\rangle$ and $ISIS$
Chen, Liu, and Zhandry [CLZ22] introduced the problems $S|LWE\rangle$ and $C|LWE\rangle$ as quantum analogues of the Learning with Errors problem, designed to construct quantum algorithms for the Inhomogeneous Short Integer Solution ($ISIS$) problem. Several later works have used this framework for constructing new quantum algorithms in specific cases. However, the general relation between all these problems is still unknown. In this paper, we investigate the equivalence between $S
…

On vehicle routing problems with stochastic demands -- Part I: Generic integer L-shaped formulations
Matheus J. Ota, Ricardo Fukasawa
https://arxiv.org/abs/2510.04043 https://…

On vehicle routing problems with stochastic demands -- Part I: Generic integer L-shaped formulations
We study a broad class of vehicle routing problems in which the cost of a route is allowed to be any nonnegative rational value computable in polynomial time in the input size. To address this class, we introduce a unifying framework that generalizes existing integer L-shaped (ILS) formulations developed for vehicle routing problems with stochastic demands (VRPSDs). This framework and subsequent analysis allow us to generalize previous ILS cuts and pinpoint which assumptions are needed to apply…

Calm local optimality for couple-constrained minimax problems
Xiaoxiao Ma, Jane Ye
https://arxiv.org/abs/2510.03861 https://arxiv.org/pdf/2510.03861…

Calm local optimality for couple-constrained minimax problems
Recently, a new local optimality concept for minimax problems, termed calm local minimax points, has been introduced. In this paper, we extend this concept to a general class of nonsmooth, nonconvex nonconcave minimax problems with coupled constraints, where the inner feasible set depends on the outer variable. We derive comprehensive first-order and second-order necessary and sufficient optimality conditions for calm local minimax points in the setting of nonsmooth, nonconvex nonconcave minima…

Modeling and Optimization of Control Problems on GPUs
Alexis Montoison, Jean-Baptiste Caillau
https://arxiv.org/abs/2510.03932 https://arxiv.org/pdf/2510.0…

Modeling and Optimization of Control Problems on GPUs
We present a fully Julia-based, GPU-accelerated workflow for solving large-scale sparse nonlinear optimal control problems. Continuous-time dynamics are modeled and then discretized via direct transcription with OptimalControl.jl into structured sparse nonlinear programs. These programs are compiled into GPU kernels using ExaModels.jl, leveraging SIMD parallelism for fast evaluation of objectives, constraints, gradients, Jacobians and Hessians. The resulting sparse problems are solved entirely …