Tootfinder

Einige der zuletzt hier besonders häufig geteilten #News:
Die Stimme von "Houston, we’ve had a problem" ist verstummt

In 2030, OpenAI projects $200B in revenue, with R&D spending hitting ~45% of that, or ~$90B; R&D costs of Alphabet and others are currently 10%-20% of revenue (The Information)
https://www.theinformation.com/articles/openais-350-billion-computing-co…

OpenAI’s $350 Billion Computing Cost Problem
The most popular consumer internet services usually figure out how to make money even after a decade or more of losses. Amazon, Uber, Netflix and Snap all started generating cash by raising prices or leveraging their large audiences to sell ads or other services. OpenAI’s growing audience would ...

The ROI of #UX is the value of your entire company, because user research is the work that determines what problem is most valuable to solve in the first place.
Trouble is, people won't believe you if you tell them this.
So the second job on top of that job is to convince people to trust us.

The ROI of UX is so massive that no one will believe you
User research makes the most difference when findings challenge closely-held assumptions. But the truth is often unpopular.

„Mit der Migration als Problem abzurechnen, bedeutet zu verstehen, dass sie kein Problem an sich darstellt. Es bedeutet, zu verstehen, wie gefährlich es ist, die Rede von Migration als Problem im politischen Diskurs zu normalisieren.“ https://www.blaetter.de/ausgabe/2025/septe

Quantum Annealing for the Set Splitting Problem
Sean Borneman
https://arxiv.org/abs/2508.06410 https://arxiv.org/pdf/2508.06410

Quantum Annealing for the Set Splitting Problem
I present a novel use of quantum annealing to solve the Set Splitting Problem using (QUBO) problem formulation. The contribution of the work is in formulating penalty functions that ensure the ground state of the QUBO Hamiltonian corresponds to valid solutions that split the input subsets. This approach scales linearly in terms of the number of logical qubits relative to problem size. Empirical tests of the proposed solution show convergence to globally optimal solutions, with high accuracy rat…

Some drugs work for diseases that they were not designed for, because both diseases have similar mechanisms.
How can we find out more of these drugs? It would save lots of lives: of people suffering rare diseases for which today there are no drugs.
This is what Every Cure does. Scanning all existing medicines (4k), matching them with all existing diseases (18.5k) - using AI, finding what drug can be repurposed.

This "service" is thanks to the numbskulls the Tories hired when they were still in power. Utter incompetence.

ProSEA: Problem Solving via Exploration Agents
William Nguyen, Vinh Luong, Christopher Nguyen
https://arxiv.org/abs/2510.07423 https://arxiv.org/pdf/2510.0…

ProSEA: Problem Solving via Exploration Agents
Large language models (LLMs) have empowered AI agents to tackle increasingly complex tasks. However, most existing agents remain limited to static planning and brittle interactions, falling short of true collaboration or adaptive reasoning. We introduce ProSEA, a modular, general-purpose multi-agent framework designed for iterative problem solving through exploration and plan evolution. ProSEA features a hierarchical architecture in which a Manager Agent orchestrates domain-specialized Expert A…

I have the same problem with the additional problem of reading past some of his personal history - which I wish we did not know.
https://thewalrus.ca/i-have-a-wodehouse-problem-the-problem-is-i-cant-stop-reading-him/

I Have a Wodehouse Problem. The Problem Is I Can’t Stop Reading Him | The Walrus
I have to limit myself to three pages at a go, once per day, with the first cup of coffee

"Research on the construction and application of problem-method-oriented academic graph empowered by LLM" https://doi.org/10.1007/s10791-025-09675-2
"Nowadays, the volume of literature in each field is huge and is growing rapidly, which posts challenge to researchers’ lit…

AirPods: Apple benachrichtigt künftig bei (fast) leerem Akku
Vielnutzer von Apples Stöpseln und Over-Ears kennen das Problem: Leere AirPods, wenn man das Haus verlässt. iOS 26 hat ein Gegenmittel.
https://www.

Complexity Results in Team Semantics: Nonemptiness Is Not So Complex
Aleksi Anttila, Juha Kontinen, Fan Yang
https://arxiv.org/abs/2510.08122 https://arxiv…

Complexity Results in Team Semantics: Nonemptiness Is Not So Complex
We initiate the study of the complexity-theoretic properties of convex logics in team semantics. We focus on the extension of classical propositional logic with the nonemptiness atom NE, a logic known to be both convex and union closed. We show that the satisfiability problem for this logic is NP-complete, that its validity problem is coNP-complete, and that its model-checking problem is in P.

Deep holes of a class of twisted Reed-Solomon codes
Haojie Gu, Nan Wang, Jun Zhang
https://arxiv.org/abs/2509.08526 https://arxiv.org/pdf/2509.08526…

Deep holes of a class of twisted Reed-Solomon codes
The deep hole problem is a fundamental problem in coding theory, and it has many important applications in code constructions and cryptography. The deep hole problem of Reed-Solomon codes has gained a lot of attention. As a generalization of Reed-Solomon codes, we investigate the problem of deep holes of a class of twisted Reed-Solomon codes in this paper. Firstly, we provide the necessary and sufficient conditions for $\boldsymbol{a}=(a_{0},a_{1},\cdots,a_{n-k-1})\in\mathbb{F}_{q}^{n-k}$ to …

Differential Dynamic Programming for the Optimal Control Problem with an Ellipsoidal Target Set and Its Statistical Inference
Sungjun Eom, Gyunghoon Park
https://arxiv.org/abs/2509.07546

Differential Dynamic Programming for the Optimal Control Problem with an Ellipsoidal Target Set and Its Statistical Inference
This work addresses an extended class of optimal control problems where a target for a system state has the form of an ellipsoid rather than a fixed, single point. As a computationally affordable method for resolving the extended problem, we present a revised version of the differential dynamic programming (DDP), termed the differential dynamic programming with ellipsoidal target set (ETS-DDP). To this end, the problem with an ellipsoidal target set is reformulated into an equivalent form with …

"Peer reviewers altered their recommendation based on whether they were cited or wanted to be cited. A matched study of open peer review. . . "
https://osf.io/preprints/osf/wdvr9_v1
The problem with this sort of metascience is that it makes no attempt to assess whether requests for c…

Addressing the Cold-Start Problem for Personalized Combination Drug Screening
Antoine de Mathelin, Christopher Tosh, Wesley Tansey
https://arxiv.org/abs/2509.07850 https://

Addressing the Cold-Start Problem for Personalized Combination Drug Screening
Personalizing combination therapies in oncology requires navigating an immense space of possible drug and dose combinations, a task that remains largely infeasible through exhaustive experimentation. Recent developments in patient-derived models have enabled high-throughput ex vivo screening, but the number of feasible experiments is limited. Further, a tight therapeutic window makes gathering molecular profiling information (e.g. RNA-seq) impractical as a means of guiding drug response predict…

I see no problem here. https://social.vmbrasseur.com/@vmbrasseur/115006183468266776

The Pandora's Box Problem with Sequential Inspections
Ali Aouad, Jingwei Ji, Yaron Shaposhnik
https://arxiv.org/abs/2507.07508 https://

The Pandora's Box Problem with Sequential Inspections
The Pandora's box problem (Weitzman 1979) is a core model in economic theory that captures an agent's (Pandora's) search for the best alternative (box). We study an important generalization of the problem where the agent can either fully open boxes for a certain fee to reveal their exact values or partially open them at a reduced cost. This introduces a new tradeoff between information acquisition and cost efficiency. We establish a hardness result and employ an array of techniques in stochasti…

The Problem of Atypicality in LLM-Powered Psychiatry
Bosco Garcia, Eugene Y. S. Chua, Harman Singh Brah
https://arxiv.org/abs/2508.06479 https://arxiv.org/…

The Problem of Atypicality in LLM-Powered Psychiatry
Large language models (LLMs) are increasingly proposed as scalable solutions to the global mental health crisis. But their deployment in psychiatric contexts raises a distinctive ethical concern: the problem of atypicality. Because LLMs generate outputs based on population-level statistical regularities, their responses -- while typically appropriate for general users -- may be dangerously inappropriate when interpreted by psychiatric patients, who often exhibit atypical cognitive or interpreti…

Classification is a RAG problem: A case study on hate speech detection
Richard Willats, Josh Pennington, Aravind Mohan, Bertie Vidgen
https://arxiv.org/abs/2508.06204 https://…

Classification is a RAG problem: A case study on hate speech detection
Robust content moderation requires classification systems that can quickly adapt to evolving policies without costly retraining. We present classification using Retrieval-Augmented Generation (RAG), which shifts traditional classification tasks from determining the correct category in accordance with pre-trained parameters to evaluating content in relation to contextual knowledge retrieved at inference. In hate speech detection, this transforms the task from "is this hate speech?" to "does this…

Generalized Zero-Shot Learning for Point Cloud Segmentation with Evidence-Based Dynamic Calibration
Hyeonseok Kim, Byeongkeun Kang, Yeejin Lee
https://arxiv.org/abs/2509.08280 h…

Generalized Zero-Shot Learning for Point Cloud Segmentation with Evidence-Based Dynamic Calibration
Generalized zero-shot semantic segmentation of 3D point clouds aims to classify each point into both seen and unseen classes. A significant challenge with these models is their tendency to make biased predictions, often favoring the classes encountered during training. This problem is more pronounced in 3D applications, where the scale of the training data is typically smaller than in image-based tasks. To address this problem, we propose a novel method called E3DPC-GZSL, which reduces overconf…

https://community.frame.work/t/framework-supporting-far-right-racists/75986/833

Framework supporting far-right racists?
The problem is that OSS (and especially FLOSS) is inherently political. The idea that we (and not some company controlled by billionaires) should have the final say over how we use our devices is political. The idea that software should be free to modify and transparent to users is political, as it puts control (and therefore power) in the hands of the users (rather than the company or organization making the software). The other, more specific problem here is that Framework made this politica…

A Minimal Perturbation Approach For The Rectangular Multiparameter Eigenvalue Problem
Shanheng Han, Lei-Hong Zhang, Ren-Cang Li
https://arxiv.org/abs/2508.05948 https://

A Minimal Perturbation Approach For The Rectangular Multiparameter Eigenvalue Problem
The rectangular multiparameter eigenvalue problem (RMEP) involves rectangular coefficient matrices (usually with more rows than columns) and may potentially have no solution in its original form. A minimal perturbation framework is proposed to defines approximate solutions. Computationally, two particular scenarios are considered: computing one approximate eigen-tuple or a complete set of approximate eigen-tuples. For computing one approximate eigen-tuple, an alternating iterative scheme with p…

Non-algebraicity of foliations via reduction modulo $2$
Jo\~ao Paulo Figueredo, Wodson Mendson
https://arxiv.org/abs/2507.07277 https://

Non-algebraicity of foliations via reduction modulo $2$
Motivated by the Jouanolou foliation problem, we investigate the non-algebraicity of foliations by curves on $\mathbb{P}^2_{\mathbb{C}}$. We present a criterion to show that such a foliation has no algebraic invariant curves, using a method of reduction modulo $2$. Finally, using this criterion, we give a new proof that the Jouanolou foliation of odd degree has no algebraic invariant curves. We also present other classes of foliations without algebraic invariant curves.

On Propositional Program Equivalence (extended abstract)
Tobias Kapp\'e
https://arxiv.org/abs/2507.07480 https://arxiv.org/pdf/25…

On Propositional Program Equivalence (extended abstract)
General program equivalence is undecidable. However, if we abstract away the semantics of statements, then this problem becomes not just decidable, but practically feasible. For instance, a program of the form "if $b$ then $e$ else $f$" should be equivalent to "if not $b$ then $f$ else $e$" - no matter what $b$, $e$ and $f$ are. This kind of equivalence is known as propositional equivalence. In this extended abstract, we discuss recent developments in propositional program equivalence from the …

Axion Quality Problem: Keep Calm and Baryon
Prateek Agrawal, Anson Hook, Vazha Loladze, Mario Reig
https://arxiv.org/abs/2510.07366 https://arxiv.org/pdf/2…

Axion Quality Problem: Keep Calm and Baryon
Axion models generically suffer from a severe quality problem when coupled to gravity. In this article we provide a very simple model with a high quality axion. The axion is a pseudo-Nambu-Goldstone boson of the baryon number symmetry, $U(1)_B$, of a new composite sector that breaks $U(1)_B$ spontaneously when it confines. A controlled example is a supersymmetric QCD (SQCD) with $N_c = N_f$. The axion shift symmetry is automatically protected due to the high dimension of the gauge-invariant bar…

A survey on the optimal partition problem
Roberto Ognibene, Bozhidar Velichkov
https://arxiv.org/abs/2510.08241 https://arxiv.org/pdf/2510.08241

A survey on the optimal partition problem
This survey synthesizes the current state of the art on the regularity theory for solutions to the optimal partition problem. Namely, we consider non-negative, vector-valued Sobolev functions whose components have mutually disjoint support, and which are either local minimizers of the Dirichlet energy or, more generally, critical points satisfying a system of variational inequalities. This is particularly meaningful as the problem has emerged on several occasions and in diverse contexts: our ai…

On the Complexity of Language Membership for Probabilistic Words
Antoine Amarilli, Mika\"el Monet, Paul Rapha\"el, Sylvain Salvati
https://arxiv.org/abs/2510.08127 htt…

On the Complexity of Language Membership for Probabilistic Words
We study the membership problem to context-free languages L (CFLs) on probabilistic words, that specify for each position a probability distribution on the letters (assuming independence across positions). Our task is to compute, given a probabilistic word, what is the probability that a word drawn according to the distribution belongs to L. This problem generalizes the problem of counting how many words of length n belong to L, or of counting how many completions of a partial word belong to L.…

'Confidence is high' for Cowboys offense heading into Panthers showdown https://www.sportingnews.com/us/nfl/dallas-cowboys/news/confidence-high-cowboys-offense-heading-panthers-showdown/2e45b9c71d568…

Time-Frequency Filtering Meets Graph Clustering
Marcelo A. Colominas, Stefan Steinerberger, Hau-Tieng Wu
https://arxiv.org/abs/2510.07503 https://arxiv.org…

Time-Frequency Filtering Meets Graph Clustering
We show that the problem of identifying different signal components from a time-frequency representation can be equivalently phrased as a graph clustering problem: given a graph $G=(V,E)$ one aims to identify `clusters', subgraphs that are strongly connected and have relatively few connections between them. The graph clustering problem is well studied, we show how these ideas can suggest (many) new ways to identify signal components. Numerical experiments illustrate the ideas.

Generalized Perturbed Kepler Problem: Gravitational Wave Imprints from Eccentric Compact Binaries
Rajes Ghosh, R. Prasad, Kabir Chakravarti, Prayush Kumar
https://arxiv.org/abs/2508.06245

Generalized Perturbed Kepler Problem: Gravitational Wave Imprints from Eccentric Compact Binaries
Observations of astrophysical binaries may reveal departures from pure Keplerian orbits due to environmental influences, modifications to the underlying gravitational dynamics, or signatures of new physics. In this work, we develop a unified framework to systematically study such perturbations in the ambit of perturbed Kepler problem, and explore their impact on eccentric orbital dynamics and gravitational wave emission. Unlike traditional parametrized frameworks such as post-Newtonian and post…

Behaviorally Heterogeneous Multi-Agent Exploration Using Distributed Task Allocation
Nirabhra Mandal, Aamodh Suresh, Carlos Nieto-Granda, Sonia Mart\'inez
https://arxiv.org/abs/2509.08242

Behaviorally Heterogeneous Multi-Agent Exploration Using Distributed Task Allocation
We study a problem of multi-agent exploration with behaviorally heterogeneous robots. Each robot maps its surroundings using SLAM and identifies a set of areas of interest (AoIs) or frontiers that are the most informative to explore next. The robots assess the utility of going to a frontier using Behavioral Entropy (BE) and then determine which frontier to go to via a distributed task assignment scheme. We convert the task assignment problem into a non-cooperative game and use a distributed alg…

RINO: Renormalization Group Invariance with No Labels
Zichun Hao, Raghav Kansal, Abhijith Gandrakota, Chang Sun, Ngadiuba Jennifer, Javier Duarte, Maria Spiropulu
https://arxiv.org/abs/2509.07486

RINO: Renormalization Group Invariance with No Labels
A common challenge with supervised machine learning (ML) in high energy physics (HEP) is the reliance on simulations for labeled data, which can often mismodel the underlying collision or detector response. To help mitigate this problem of domain shift, we propose RINO (Renormalization Group Invariance with No Labels), a self-supervised learning approach that can instead pretrain models directly on collision data, learning embeddings invariant to renormalization group flow scales. In this work,…

Uniqueness of $S_2$-isotropic solutions to the isotropic $L_p$ Minkowski problem
Yao Wan
https://arxiv.org/abs/2509.08588 https://arxiv.org/pdf/2509.08588

Uniqueness of $S_2$-isotropic solutions to the isotropic $L_p$ Minkowski problem
This paper investigates the spectral properties of the Hilbert-Brunn-Minkowski operator $L_K$ to derive stability estimates for geometric inequalities, including the local Brunn-Minkowski inequality. By analyzing the eigenvalues of $L_K$, we establish the uniqueness of $S_2$-isotropic solutions to the isotropic $L_p$ Minkowski problem in $\mathbb{R}^{n}$ for $\frac{1-3n^2}{2n}\leq p<-n$ with $λ_2(-L_K)\geq \frac{n-1}{2n-1+p}$. Furthermore, we extend this uniqueness result to the range $-2n-1 \…

A Randomized Rounding Approach for DAG Edge Deletion
Sina Kalantarzadeh, Nathan Klein, Victor Reis
https://arxiv.org/abs/2507.07943 https://

A Randomized Rounding Approach for DAG Edge Deletion
In the DAG Edge Deletion problem, we are given an edge-weighted directed acyclic graph and a parameter $k$, and the goal is to delete the minimum weight set of edges so that the resulting graph has no paths of length $k$. This problem, which has applications to scheduling, was introduced in 2015 by Kenkre, Pandit, Purohit, and Saket. They gave a $k$-approximation and showed that it is UGC-Hard to approximate better than $\lfloor 0.5k \rfloor$ for any constant $k \ge 4$ using a work of Svensson …

The Diophantine Frobenius Problem revisited
Yuchen Ding, Weijia Wang, Hao Zhang
https://arxiv.org/abs/2509.08599 https://arxiv.org/pdf/2509.08599

The Diophantine Frobenius Problem revisited
Let $k\ge 2$ and $a_1, a_2, \cdots, a_k$ be positive integers with \[ \gcd(a_1, a_2, \cdots, a_k)=1. \] It is proved that there exists a positive integer $G_{a_1, a_2, \cdots, a_k}$ such that every integer $n$ strictly greater than it can be represented as the form \[ n=a_1x_1+a_2x_2+\cdots+a_kx_k, \quad (x_1, x_2, \cdots, x_k\in\mathbb{Z}_{\ge 0},~\gcd(x_1, x_2, \cdots, x_k)=1). \] We then investigate the size of $G_{a_1, a_2}$ explicitly. Our result strengthens the primality requirement of $x…

No chyba wszystko już wraca do normy. Musiałem odespać dwie noce i masę stresu i w koncu udalo sie znalezc błąd.
Dajcie tutaj w wątku znać jakby coś jeszcze nie działało ( oprocz chat.pol social bo widze tam jeszcze problem)

@… the problem with the Octopus one is that it’s tied to the vehicle lease. So if you sign up for more miles, you’ll get more free.

An integrable Anderson-impurity problem embedded in the one-dimensional Hubbard model
Renjie Song, Mingchen Zheng, Junpeng Cao, Yupeng Wang
https://arxiv.org/abs/2509.07799 http…

An integrable Anderson-impurity problem embedded in the one-dimensional Hubbard model
An exactly solvable one-dimensional Hubbard model with a single Anderson impurity embedded at the boundary is constructed in the framework of the quantum inverse scattering method. The model is solved exactly by the nested Bethe ansatz method. We identify the boundary bound states and determine the ground state phase diagram. By deriving the impurity contribution to the magnetic susceptibility, we show that in the dilute electron limit, a nearly free local moment forms at the impurity site, whi…

Die Stimme von "Houston, we´ve had a problem" ist verstummt
Mit 97 Jahren ist NASA-Astronaut Jim Lovell gestorben. Seine Raumfahrt-Karriere ist eine Geschichte des Scheiterns und Weitermachens – und von viel Glück.

#XSLT used to be my goto tool for transforming documents. Today I was facing a document transformation problem (the daring fireball `markdown` program does not emit valid HTML, and although you can pipe it through `tidy`, tidy won't extract the first `h1` and use it as `title`), so I thought 'yay! XSLT'.
Reader, I am no longer competent to write a simple XSLT transform.
I *kno…

From Distrust to Retribution: America’s Escalating Spiral: https://blog.rmendes.net/2025/09/11/from-distrust-to-retribution-americas.html

Oh, so now the problem is #circumcision? Did any of these shit-for-brains "experts" go looking around for an #uncut #autistic guy? No? Not even one minute spent trying to rule out their la…

Autism ‘highly likely’ linked to Tylenol and circumcision, RFK Jr. says
Health Secretary Robert F. Kennedy Jr. claims that there may be a link between circumcision and autism.

Aw, flat tires, so sad. Hopefully that's not a sign of low quality tires, it would be tough situation if that became a common problem for ICE! https://kolektiva.social/@615ANTIFASCIST/115180400255033086

ANTIFASCIST 615 (@615ANTIFASCIST@kolektiva.social)
Attached: 1 image Crowd Jeers as Border Patrol vehicle with flattened tires leaves Rochester neighborhood. https://13wham.com/news/local/crowd-jeers-as-border-patrol-vehicle-with-flattened-tires-leaves-rochester-neighborhood-park-avenue-westminster-road-us-ice-customs-and-border-protection-federal-agents-trump-administration-immigration

Computation-resource-efficient Task-oriented Communications
Jingwen Fu, Ming Xiao, Chao Ren, Mikael Skoglund
https://arxiv.org/abs/2507.07422 https://

Computation-resource-efficient Task-oriented Communications
The rapid development of deep-learning enabled task-oriented communications (TOC) significantly shifts the paradigm of wireless communications. However, the high computation demands, particularly in resource-constrained systems e.g., mobile phones and UAVs, make TOC challenging for many tasks. To address the problem, we propose a novel TOC method with two models: a static and a dynamic model. In the static model, we apply a neural network (NN) as a task-oriented encoder (TOE) when there is no c…

A post from the archive 📫:
Invalid Access to memory location in KUDU App Services
https://www.poppastring.com/blog/invalid-access-to-memory-location-in-kudu-app-services

Electric Vehicle Routing Problem with Time Windows and Station-based or Route-based Charging Options
Tran Trung Duc, Vu Duc Minh, Nguyen Ngoc Doanh, Pham Gia Nguyen, Laurent El Ghaoui, Ha Minh Hoang
https://arxiv.org/abs/2509.07402

Electric Vehicle Routing Problem with Time Windows and Station-based or Route-based Charging Options
The Electric Vehicle Routing Problem with Time Windows and Station-based or Route-based Charging Options addresses fleet optimization incorporating both conventional charging stations and continuous wireless charging infrastructure. This paper extends Schneider et al.'s foundational EVRP-TW model with arc-based dynamic wireless charging representation, partial coverage modeling, and hierarchical multi-objective optimization prioritizing fleet minimization. Computational experiments on Schneider…

Study of Robust Features in Formulating Guidance for Heuristic Algorithms for Solving the Vehicle Routing Problem
Bachtiar Herdianto, Romain Billot, Flavien Lucas, Marc Sevaux
https://arxiv.org/abs/2508.06129

Study of Robust Features in Formulating Guidance for Heuristic Algorithms for Solving the Vehicle Routing Problem
The Vehicle Routing Problem (VRP) is a complex optimization problem with numerous real-world applications, mostly solved using metaheuristic algorithms due to its $\mathcal{NP}$-Hard nature. Traditionally, these metaheuristics rely on human-crafted designs developed through empirical studies. However, recent research shows that machine learning methods can be used the structural characteristics of solutions in combinatorial optimization, thereby aiding in designing more efficient algorithms, pa…

Combinatorial Algorithm for Tropical Linearly Factorized Programming
Yuki Nishida
https://arxiv.org/abs/2507.07596 https://arxiv.org/…

Combinatorial Algorithm for Tropical Linearly Factorized Programming
The tropical semiring is a set of numbers $\mathbb{R}\cup\{-\infty\}$ with addition $a\oplus b:=\max(a,b)$ and multiplication $a\otimes b:=a+b$. As well as in conventional algebra, linear programming problem in the tropical semiring has been developed. In this study, we introduce a new type of tropical optimization problem, namely, tropical linearly factorized programming problem. This problem involves minimizing the objective function given by the product of tropical linear forms $c_{k,1}\otim…

Anthropic adds a memory feature for Claude to reference information from past chats, available now for Max, Team, and Enterprise plans, and soon for other plans (Zac Hall/9to5Mac)
https://9to5mac.com/2025/08/11/claude-memory-feature/

Claude just learned a useful ChatGPT trick - 9to5Mac
Anthropic has introduced a helpful new feature for Claude that solves a problem similar to one ChatGPT already addressed. As...

Improved Hamiltonian learning and sparsity testing through Bell sampling
Savar D. Sinha, Yu Tong
https://arxiv.org/abs/2509.07937 https://arxiv.org/pdf/250…

Improved Hamiltonian learning and sparsity testing through Bell sampling
We consider the problem of learning an $M$-sparse Hamiltonian and the related problem of Hamiltonian sparsity testing. Through a detailed analysis of Bell sampling, we reduce the total evolution time required by the state-of-the-art algorithm for $M$-sparse Hamiltonian learning to $\widetilde{\mathcal{O}}(M/ε)$, where $ε$ denotes the $\ell^{\infty}$ error, achieving an improvement by a factor of $M$ (ignoring the logarithmic factor) while only requiring access to forward time-evolution. We th…

Fractional p-Laplacian Kirchhoff-type problem involving a singular term via Nehari manifold
Djamel Abid
https://arxiv.org/abs/2510.07911 https://arxiv.org/…

Fractional p-Laplacian Kirchhoff-type problem involving a singular term via Nehari manifold
This paper is dedicated to studying the existence of nontrivial positive solutions for a Kirchhoff-type problem with sign change nonlinearities and a singular term, Using the Nehari manifold and EkelandS variational principle we prove that for the appropriate choice of λ our problem has at least two positive solutions for both subcritical and critical cases.

Timeline Problems in Temporal Graphs: Vertex Cover vs. Dominating Set
Anton Herrmann, Christian Komusiewicz, Nils Morawietz, Frank Sommer
https://arxiv.org/abs/2510.08124 https:…

Timeline Problems in Temporal Graphs: Vertex Cover vs. Dominating Set
A temporal graph is a finite sequence of graphs, called snapshots, over the same vertex set. Many temporal graph problems turn out to be much more difficult than their static counterparts. One such problem is \textsc{Timeline Vertex Cover} (also known as \textsc{MinTimeline$_\infty$}), a temporal analogue to the classical \textsc{Vertex Cover} problem. In this problem, one is given a temporal graph $\mathcal{G}$ and two integers $k$ and $\ell$, and the goal is to cover each edge of each snapsho…

Relative spectral correspondence for parabolic Higgs bundles and Deligne--Simpson problem
Jia Choon Lee, Sukjoo Lee
https://arxiv.org/abs/2509.08527 https://

Relative spectral correspondence for parabolic Higgs bundles and Deligne--Simpson problem
In this paper, we generalize the spectral correspondence for parabolic Higgs bundles established by Diaconescu--Donagi--Pantev to the relative setting. We show that the relative moduli space of $\vecξ$-parabolic Higgs bundles on a curve can be realized as the relative moduli space of pure dimension one sheaves on a family of holomorphic symplectic surfaces. This leads us to formulate the image of the relative moduli space under the Hitchin map in terms of linear systems on the family of surfac…

A Modular Algorithm for Non-Stationary Online Convex-Concave Optimization
Qing-xin Meng, Xia Lei, Jian-wei Liu
https://arxiv.org/abs/2509.07901 https://arx…

A Modular Algorithm for Non-Stationary Online Convex-Concave Optimization
This paper investigates the problem of Online Convex-Concave Optimization, which extends Online Convex Optimization to two-player time-varying convex-concave games. The goal is to minimize the dynamic duality gap (D-DGap), a critical performance measure that evaluates players' strategies against arbitrary comparator sequences. Existing algorithms fail to deliver optimal performance, particularly in stationary or predictable environments. To address this, we propose a novel modular algorithm wit…

Are you In or Out (of gallery)? Wisdom from the Same-Identity Crowd
Aman Bhatta, Maria Dhakal, Michael C. King, Kevin W. Bowyer
https://arxiv.org/abs/2508.06357 https://

Are you In or Out (of gallery)? Wisdom from the Same-Identity Crowd
A central problem in one-to-many facial identification is that the person in the probe image may or may not have enrolled image(s) in the gallery; that is, may be In-gallery or Out-of-gallery. Past approaches to detect when a rank-one result is Out-of-gallery have mostly focused on finding a suitable threshold on the similarity score. We take a new approach, using the additional enrolled images of the identity with the rank-one result to predict if the rank-one result is In-gallery / Out-of-gal…

Apple behebt Apple-Intelligence-Problem beim iPhone 17
Ein Bug, der dazu führte, dass man mit einem der brandneuen Apple-Handys KI-Dienste nicht nutzen konnte, ist offenbar behoben – ohne Update.
https://www.

On the spectral theory in the Fock space with polynomial eigenfunctions
A. V. Turbiner (deceased), N. L. Vasilevski (deceased)
https://arxiv.org/abs/2508.05924 https://

On the spectral theory in the Fock space with polynomial eigenfunctions
The notion of the eigenvalue problem in the Fock space with polynomial eigenfunctions is introduced. This problem is classified by using the finite-dimensional representations of the $\mathfrak{sl}(2)$-algebra in Fock space. In the complex representation of the 3-dimensional Heisenberg algebra, proposed by Turbiner-Vasilevski (2021) in Ref.7, this construction is reduced to the linear differential operators in $(\frac{\partial}{\partial \overline{z}}\,,\,\frac{\partial}{\partial z})$ acting on …

Application of LLMs to Multi-Robot Path Planning and Task Allocation
Ashish Kumar
https://arxiv.org/abs/2507.07302 https://arxiv.org/…

Application of LLMs to Multi-Robot Path Planning and Task Allocation
Efficient exploration is a well known problem in deep reinforcement learning and this problem is exacerbated in multi-agent reinforcement learning due the intrinsic complexities of such algorithms. There are several approaches to efficiently explore an environment to learn to solve tasks by multi-agent operating in that environment, of which, the idea of expert exploration is investigated in this work. More specifically, this work investigates the application of large-language models as expert …

Vibroseis Vehicle Routing Problem with Spatio-Temporal Coupled Constraints
Kexin Zhu, Jialong Shi, Jianyong Sun, Heng Zhou, Mingen Kuang, Ye Fan
https://arxiv.org/abs/2508.06172

Vibroseis Vehicle Routing Problem with Spatio-Temporal Coupled Constraints
Simultaneous multi vibroseis vehicle operations are central to modern land seismic exploration and can be modeled as a Vehicle Routing Problem (VRP). A critical distinction from classical VRPs, however, is the need for a minimum start-time interval between nearby sources to prevent signal interference. This constraint introduces strong spatio-temporal coupling, as one vehicle's route directly impacts the schedules of others, leading to potential forced waits. This paper defines this novel probl…

Robust Lindbladian Estimation for Quantum Dynamics
Yinchen Liu, James R. Seddon, Tamara Kohler, Emilio Onorati, Toby S. Cubitt
https://arxiv.org/abs/2507.07912

Robust Lindbladian Estimation for Quantum Dynamics
We revisit the problem of fitting Lindbladian models to the outputs of quantum process tomography. A sequence of prior theoretical works approached the problem by considering whether there exists a Lindbladian generator close to a matrix logarithm of the tomographically estimated transfer matrix. This technique must take into account the non-uniqueness of the matrix logarithm, so that in general multiple branches of the logarithm must be checked. In contrast, all practical demonstrations of Lin…

Strong time-periodic solutions to a multilayered fluid-structure interaction problem
Felix Brandt, Claudiu M\^indril\u{a}, Arnab Roy
https://arxiv.org/abs/2507.07918

Strong time-periodic solutions to a multilayered fluid-structure interaction problem
This article studies a nonlinearly coupled, time-periodic fluid-structure interaction (FSI) problem involving the Navier-Stokes equations for an incompressible, viscous fluid coupled with a multilayered elastic structure consisting of a thin damped shell and a thick viscoelastic component. The main objective is to establish the existence of a strong time-periodic solution. To address the full nonlinear problem, we employ a fixed point argument, which relies on a detailed analysis of the lineari…

Graph-based Integrated Gradients for Explaining Graph Neural Networks
Lachlan Simpson, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
https://arxiv.org/abs/2509.07648

Graph-based Integrated Gradients for Explaining Graph Neural Networks
Integrated Gradients (IG) is a common explainability technique to address the black-box problem of neural networks. Integrated gradients assumes continuous data. Graphs are discrete structures making IG ill-suited to graphs. In this work, we introduce graph-based integrated gradients (GB-IG); an extension of IG to graphs. We demonstrate on four synthetic datasets that GB-IG accurately identifies crucial structural components of the graph used in classification tasks. We further demonstrate on t…

Skeleton-based sign language recognition using a dual-stream spatio-temporal dynamic graph convolutional network
Liangjin Liu, Haoyang Zheng, Pei Zhou
https://arxiv.org/abs/2509.08661

Skeleton-based sign language recognition using a dual-stream spatio-temporal dynamic graph convolutional network
Isolated Sign Language Recognition (ISLR) is challenged by gestures that are morphologically similar yet semantically distinct, a problem rooted in the complex interplay between hand shape and motion trajectory. Existing methods, often relying on a single reference frame, struggle to resolve this geometric ambiguity. This paper introduces Dual-SignLanguageNet (DSLNet), a dual-reference, dual-stream architecture that decouples and models gesture morphology and trajectory in separate, complementa…

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…

Existence and Uniqueness of Solution for Linear Complementarity Problem in Contact Mechanics
Jiamin Xu, Nazli Demirer, Vy Pho, He Zhang, Kaixiao Tian, Ketan Bhaidasna, Robert Darbe, Dongmei Chen
https://arxiv.org/abs/2508.05777

Existence and Uniqueness of Solution for Linear Complementarity Problem in Contact Mechanics
Although a unique solution is guaranteed in the Linear complementarity problem (LCP) when the matrix $\mathbf{M}$ is positive definite, practical applications often involve cases where $\mathbf{M}$ is only positive semi-definite, leading to multiple possible solutions. However, empirical observations suggest that uniqueness can still emerge under certain structural conditions on the matrix $\mathbf{M}$ and vector $\mathbf{q}$. Motivated by an unresolved problem in nonlinear modeling for beam co…

Quantum Probe Tomography
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang
https://arxiv.org/abs/2510.08499 https://arxiv.org/pdf/2510.08499

Quantum Probe Tomography
Characterizing quantum many-body systems is a fundamental problem across physics, chemistry, and materials science. While significant progress has been made, many existing Hamiltonian learning protocols demand digital quantum control over the entire system, creating a disconnect from many real-world settings that provide access only through small, local probes. Motivated by this, we introduce and formalize the problem of quantum probe tomography, where one seeks to learn the parameters of a man…

Robin problem with measure data and singular nonlinearities on the boundary
Andrzej Rozkosz
https://arxiv.org/abs/2507.07821 https://…

Robin problem with measure data and singular nonlinearities on the boundary
We consider the Robin problem for a uniformly elliptic divergence operator with measure data on the right-hand side of the equation and an absorption term on the boundary involving blowing up terms. We prove the existence of a positive renormalized solution and provide it stochastic representation, which can be viwed as a generalized nonlinear Feynman-Kac formula. From this representation we derive some additional regularity results for the solution and some uniqueness results.

Complexity Analysis of a Bicriteria Directed Multimodal Transportation Network Design Problem
Dominik Leib, Susanne Fritzler, Neele Leith\"auser
https://arxiv.org/abs/2507.07894

Complexity Analysis of a Bicriteria Directed Multimodal Transportation Network Design Problem
In this paper, we address a bicriteria network design problem that arises from practical applications in urban and rural public transportation planning. We establish the problem's complexity and demonstrate inapproximability results, highlighting the inherent difficulties in finding optimal solutions. Additionally, we identify special cases where approximability can be achieved, providing valuable insights for practitioners. Our proofs leverage complexity results related to directed network des…

GCond: Gradient Conflict Resolution via Accumulation-based Stabilization for Large-Scale Multi-Task Learning
Evgeny Alves Limarenko, Anastasiia Alexandrovna Studenikina
https://arxiv.org/abs/2509.07252

GCond: Gradient Conflict Resolution via Accumulation-based Stabilization for Large-Scale Multi-Task Learning
In multi-task learning (MTL), gradient conflict poses a significant challenge. Effective methods for addressing this problem, including PCGrad, CAGrad, and GradNorm, in their original implementations are computationally demanding, which significantly limits their application in modern large models and transformers. We propose Gradient Conductor (GCond), a method that builds upon PCGrad principles by combining them with gradient accumulation and an adaptive arbitration mechanism. We evaluated GC…

Absorbing detectors meet scattering theory
Will Cavendish, Siddhant Das
https://arxiv.org/abs/2509.07518 https://arxiv.org/pdf/2509.07518

Absorbing detectors meet scattering theory
Any proposed solution to the "screen problem" in quantum mechanics -- the challenge of predicting the joint distribution of particle arrival times and impact positions -- must align with the extensive data obtained from scattering experiments. In this paper, we conduct a direct consistency check of the Absorbing Boundary Condition (ABC) proposal, a prominent approach to address the screen problem, against the predictions derived from scattering theory (ST). Through a series of exactly solvable …

Maximal regularity of Dirichlet problem for the Laplacian in Lipschitz domains
Ch\'erif Amrouche, Mohand Moussaoui
https://arxiv.org/abs/2509.08543 https://

Maximal regularity of Dirichlet problem for the Laplacian in Lipschitz domains
The focus of this work is on the homogeneous and non-homogeneous Dirichlet problem for the Laplacian in bounded Lipschitz domains (BLD). Although it has been extensively studied by many authors, we would like to return to a number of fundamental questions and known results, such as the traces and the maximal regularity of solutions. First, to treat non-homogeneous boundary conditions, we rigorously define the notion of traces for non regular functions. This approach replaces the non-tangential …

DYNAMIX: RL-based Adaptive Batch Size Optimization in Distributed Machine Learning Systems
Yuanjun Dai, Keqiang He, An Wang
https://arxiv.org/abs/2510.08522 https://

DYNAMIX: RL-based Adaptive Batch Size Optimization in Distributed Machine Learning Systems
Existing batch size selection approaches in dis- tributed machine learning rely on static allocation or simplistic heuristics that fail to adapt to heterogeneous, dynamic computing environments. We present DYNAMIX, a reinforcement learning framework that formulates batch size optimization as a sequen- tial decision-making problem using Proximal Policy Optimiza- tion (PPO). Our approach employs a multi-dimensional state representation encompassing network-level metrics, system-level resource uti…

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 …

Computational Methods and Verification Theorem for Portfolio-Consumption Optimization under Exponential O-U Dynamics
Zhaoxiang Zhong, Haiming Song
https://arxiv.org/abs/2508.06491

Computational Methods and Verification Theorem for Portfolio-Consumption Optimization under Exponential O-U Dynamics
In this paper, we focus on the problem of optimal portfolio-consumption policies in a multi-asset financial market, where the n risky assets follow Exponential Ornstein-Uhlenbeck processes, along with one risk-free bond. The investor's preferences are modeled using Constant Relative Risk Aversion utility with state-dependent stochastic discounting. The problem can be formulated as a high-dimensional stochastic optimal control problem, wherein the associated value function satisfies a Hamilton-J…

Verifiable blind observable estimation: A composably secure protocol for near-term quantum advantage tasks
Bo Yang, Elham Kashefi, Harold Ollivier
https://arxiv.org/abs/2510.08548

Verifiable blind observable estimation: A composably secure protocol for near-term quantum advantage tasks
The rapid advance of quantum hardware is spotlighting pre-fault-tolerant tasks that may no longer be efficiently validated by classical means and are likely to run on potentially untrusted remote quantum servers. This motivates problem-independent verification protocols with rigorous guarantees. The Verifiable Blind Quantum Computation (VBQC) protocol provides delegated computation where the composable security spans the confidentiality and integrity of the computation. However, the success o…

Analysis of the transmission eigenvalue problem for biharmonic scattering considering penetrable scatterers
Rafael Ceja Ayala, Isaac Harris, Andreas Kleefeld
https://arxiv.org/abs/2510.08444

Analysis of the transmission eigenvalue problem for biharmonic scattering considering penetrable scatterers
In this paper, we provide an analytical study of the transmission eigenvalue problem in the context of biharmonic scattering with a penetrable obstacle. We will assume that the underlying physical model is given by an infinite elastic two--dimensional Kirchhoff--Love plate in $\mathbb{R}^2$, where the plate's thickness is small relative to the wavelength of the incident wave. In previous studies, transmission eigenvalues have been studied for acoustic scattering, whereas in this case, we consid…

SummDiff: Generative Modeling of Video Summarization with Diffusion
Kwanseok Kim, Jaehoon Hahm, Sumin Kim, Jinhwan Sul, Byunghak Kim, Joonseok Lee
https://arxiv.org/abs/2510.08458

SummDiff: Generative Modeling of Video Summarization with Diffusion
Video summarization is a task of shortening a video by choosing a subset of frames while preserving its essential moments. Despite the innate subjectivity of the task, previous works have deterministically regressed to an averaged frame score over multiple raters, ignoring the inherent subjectivity of what constitutes a good summary. We propose a novel problem formulation by framing video summarization as a conditional generation task, allowing a model to learn the distribution of good summarie…

Neurosymbolic Feature Extraction for Identifying Forced Labor in Supply Chains
Zili Wang, Frank Montabon, Kristin Yvonne Rozier
https://arxiv.org/abs/2507.07217

Neurosymbolic Feature Extraction for Identifying Forced Labor in Supply Chains
Supply chain networks are complex systems that are challenging to analyze; this problem is exacerbated when there are illicit activities involved in the supply chain, such as counterfeit parts, forced labor, or human trafficking. While machine learning (ML) can find patterns in complex systems like supply chains, traditional ML techniques require large training data sets. However, illicit supply chains are characterized by very sparse data, and the data that is available is often (purposely) co…

MPS-JuliQAOA: User-friendly, Scalable MPS-based Simulation for Quantum Optimization
Sean Feeney, Reuben Tate, John Golden, Stephan Eidenbenz
https://arxiv.org/abs/2508.05883 htt…

MPS-JuliQAOA: User-friendly, Scalable MPS-based Simulation for Quantum Optimization
We present the MPS-JuliQAOA simulator, a user-friendly, open-source tool to simulate the Quantum Approximate Optimization Algorithm (QAOA) of any optimization problem that can be expressed as diagonal Hamiltonian. By leveraging Julia-language constructs and the ITensor package to implement a Matrix Product State (MPS) approach to simulating QAOA, MPS-Juli-QAOA effortlessly scales to 512 qubits and 20 simulation rounds on the standard de-facto benchmark 3-regular MaxCut QAOA problem. MPS-JuliQAO…

Superadditivity properties and new valid inequalities for the vehicle routing problem with stochastic demands
Robin Legault, Panca Jodiawan, Jean-Fran\c{c}ois C\^ot\'e, Leandro C. Coelho
https://arxiv.org/abs/2508.05877

Superadditivity properties and new valid inequalities for the vehicle routing problem with stochastic demands
Over the past thirty years, the vehicle routing problem with stochastic demands has emerged as a canonical application of the integer L-shaped method, leading to an extensive body of literature and several methodological refinements. Recently, the disaggregated integer L-shaped (DL-shaped) method, which decomposes the recourse function by customer rather than treating it as an aggregate cost, has been proposed and successfully applied under the detour-to-depot recourse policy. However, the vali…

Nonlinear Stability of the Rayleigh-Taylor Problem in Quantum Navier-Stokes Equations
Fei Jiang, Yajie Zhang, Zhipeng Zhang, Youyi Zhao
https://arxiv.org/abs/2510.07695 https://…

Nonlinear Stability of the Rayleigh-Taylor Problem in Quantum Navier-Stokes Equations
It is well-known that the Rayleigh--Taylor (abbr. RT) instability can be completely inhibited by the quantum effect stabilization in proper circumstances leading to a cutoff wavelength in the \emph{linear} motion equations. Motivated by the linear theory, we further investigate the {stability} for the \emph{nonlinear} RT problem of quantum Navier--Stokes equations in a slab with Navier boundary condition, and rigorously prove the inhibition of RT instability by the quantum effect under a proper…

Towards solving industrial integer linear programs with Decoded Quantum Interferometry
Francesc Sabater, Ouns El Harzli, Geert-Jan Besjes, Marvin Erdmann, Johannes Klepsch, Jonas Hiltrop, Jean-Francois Bobier, Yudong Cao, Carlos A. Riofrio
https://arxiv.org/abs/2509.08328

Towards solving industrial integer linear programs with Decoded Quantum Interferometry
Optimization via decoded quantum interferometry (DQI) has recently gained a great deal of attention as a promising avenue for solving optimization problems using quantum computers. In this paper, we apply DQI to an industrial optimization problem in the automotive industry: the vehicle option-package pricing problem. Our main contributions are 1) formulating the industrial problem as an integer linear program (ILP), 2) converting the ILP into instances of max-XORSAT, and 3) developing a detaile…

ALICE: An Interpretable Neural Architecture for Generalization in Substitution Ciphers
Jeff Shen, Lindsay Smith
https://arxiv.org/abs/2509.07282 https://ar…

ALICE: An Interpretable Neural Architecture for Generalization in Substitution Ciphers
We present cryptogram solving as an ideal testbed for studying neural network generalization in combinatorially complex domains. In this task, models must decrypt text encoded with substitution ciphers, choosing from 26! possible mappings without explicit access to the cipher. We develop ALICE (an Architecture for Learning Interpretable Cryptogram dEcipherment): a simple encoder-only Transformer that sets a new state-of-the-art for both accuracy and speed on this decryption problem. Surprisingl…

Getting In Contract with Large Language Models -- An Agency Theory Perspective On Large Language Model Alignment
Sascha Kaltenpoth, Oliver M\"uller
https://arxiv.org/abs/2509.07642

Getting In Contract with Large Language Models -- An Agency Theory Perspective On Large Language Model Alignment
Adopting Large language models (LLMs) in organizations potentially revolutionizes our lives and work. However, they can generate off-topic, discriminating, or harmful content. This AI alignment problem often stems from misspecifications during the LLM adoption, unnoticed by the principal due to the LLM's black-box nature. While various research disciplines investigated AI alignment, they neither address the information asymmetries between organizational adopters and black-box LLM agents nor con…

A Stochastic Programming Approach to the Railcar Maintenance Problem with Service Level and Track Capacity Considerations
Murat Elh\"useyni, Burak Kocuk
https://arxiv.org/abs/2509.08427

A Stochastic Programming Approach to the Railcar Maintenance Problem with Service Level and Track Capacity Considerations
Railcars, as part of the rolling stock, perform regular transportation tasks with respect to a service level agreement (SLA) and undergo preventive maintenance at regular intervals based on the recommendations of train manufacturers. When unexpected failures occur, they need to enter corrective maintenance immediately. However, this reactive approach may result in large SLA violations and an excessive number of corrective maintenance actions. In this study, we utilize a predictive maintenance a…

Fourier Learning Machines: Nonharmonic Fourier-Based Neural Networks for Scientific Machine Learning
Mominul Rubel, Adam Meyers, Gabriel Nicolosi
https://arxiv.org/abs/2509.08759

Fourier Learning Machines: Nonharmonic Fourier-Based Neural Networks for Scientific Machine Learning
We introduce the Fourier Learning Machine (FLM), a neural network (NN) architecture designed to represent a multidimensional nonharmonic Fourier series. The FLM uses a simple feedforward structure with cosine activation functions to learn the frequencies, amplitudes, and phase shifts of the series as trainable parameters. This design allows the model to create a problem-specific spectral basis adaptable to both periodic and nonperiodic functions. Unlike previous Fourier-inspired NN models, the …

CaRT: Teaching LLM Agents to Know When They Know Enough
Grace Liu, Yuxiao Qu, Jeff Schneider, Aarti Singh, Aviral Kumar
https://arxiv.org/abs/2510.08517 https://

CaRT: Teaching LLM Agents to Know When They Know Enough
Many tasks require learned models to strategically gather relevant information over multiple rounds of interaction before actually acting on a task. Strategic information gathering requires models to know not only how to effectively acquire information, but also when to stop gathering information and make a decision, in order to avoid overthinking or getting derailed when acting. In this paper, we formalize this problem and introduce Counterfactuals and Reasoning for Termination (CaRT), an appr…

Mean field control with absorption
Pierre Cardaliaguet, Joe Jackson, Panagiotis E. Souganidis
https://arxiv.org/abs/2509.07877 https://arxiv.org/pdf/2509.0…

Mean field control with absorption
In this paper we study a mean field control problem in which particles are absorbed when they reach the boundary of a smooth domain. The value of the N-particle problem is described by a hierarchy of Hamilton-Jacobi equations which are coupled through their boundary conditions. The value function of the limiting problem; meanwhile, solves a Hamilton-Jacobi equation set on the space of sub-probability measures on the smooth domain, i.e. the space of non-negative measures with total mass at most …

Computational complexity of the homology problem with orientable filtration: MA-completeness
Ryu Hayakawa, Casper Gyurik, Mahtab Yaghubi Rad, Vedran Dunjko
https://arxiv.org/abs/2510.07014

Computational complexity of the homology problem with orientable filtration: MA-completeness
We show the existence of an MA-complete homology problem for a certain subclass of simplicial complexes. The problem is defined through a new concept of orientability of simplicial complexes that we call a "uniform orientable filtration", which is related to sign-problem freeness in homology. The containment in MA is achieved through the design of new, higher-order random walks on simplicial complexes associated with the filtration. For the MA-hardness, we design a new gadget with which we can …

Quantum and Simulated Annealing-Based Iterative Algorithms for QUBO Relaxations of the Sparsest $k$-Subgraph Problem
Omkar Bihani, Roman Ku\v{z}el, Janez Povh, Dunja Pucher
https://arxiv.org/abs/2509.08544

Quantum and Simulated Annealing-Based Iterative Algorithms for QUBO Relaxations of the Sparsest $k$-Subgraph Problem
In this paper, we introduce three QUBO (Quadratic Unconstrained Binary Optimization) relaxations for the sparsest $k$-subgraph (SkS) problem: a quadratic penalty relaxation, a Lagrangian relaxation, and an augmented Lagrangian relaxation. The effectiveness of these approaches strongly depends on the choice of penalty parameters. We establish theoretical results characterizing the parameter values for which the QUBO relaxations are exact. For practical implementation, we propose three iterative …

Perfectly-Private Analog Secure Aggregation in Federated Learning
Delio Jaramillo-Velez, Charul Rajput, Ragnar Freij-Hollanti, Camilla Hollanti, Alexandre Graell i Amat
https://arxiv.org/abs/2509.08683

Perfectly-Private Analog Secure Aggregation in Federated Learning
In federated learning, multiple parties train models locally and share their parameters with a central server, which aggregates them to update a global model. To address the risk of exposing sensitive data through local models, secure aggregation via secure multiparty computation has been proposed to enhance privacy. At the same time, perfect privacy can only be achieved by a uniform distribution of the masked local models to be aggregated. This raises a problem when working with real valued da…

Aggregate-Combine-Readout GNNs Are More Expressive Than Logic C2
Stan P Hauke, Przemys{\l}aw Andrzej Wa{\l}\k{e}ga
https://arxiv.org/abs/2508.06091 https://

Aggregate-Combine-Readout GNNs Are More Expressive Than Logic C2
In recent years, there has been growing interest in understanding the expressive power of graph neural networks (GNNs) by relating them to logical languages. This research has been been initialised by an influential result of Barceló et al. (2020), who showed that the graded modal logic (or a guarded fragment of the logic C2), characterises the logical expressiveness of aggregate-combine GNNs. As a ``challenging open problem'' they left the question whether full C2 characterises the logical ex…

Variable aggregation-based formulations for pumped storage hydro model in the day-ahead unit commitment problem
Shaoze Li, Junhao Wu, Zhibin Deng
https://arxiv.org/abs/2510.07751

Variable aggregation-based formulations for pumped storage hydro model in the day-ahead unit commitment problem
Pumped storage hydro (PSH) plants can improve the flexibility of power systems. A well-designed formulation for a PSH model is essential when incorporating the PSH units into a day-ahead unit commitment model. In the literature, the formulation of a PSH model is generally based on the individual PSH unit. This formulation is tight if there is only one PSH unit in the reservoir. However, when there are multiple units sharing the same reservoir in a PSH plant, the existing formulation may introdu…

Optimal Multi-Mode Propulsion Mission Design Using Direct Collocation
George V. Haman III, Anil V. Rao
https://arxiv.org/abs/2509.07336 https://arxiv.org/p…

Optimal Multi-Mode Propulsion Mission Design Using Direct Collocation
The problem of minimizing the transfer time between periodic orbits in the Earth-Moon elliptic restricted three-body problem using a multi-mode propulsion system is considered. By employing the true anomaly on the primary orbit as the independent variable and introducing normalized time as an additional state, the need to repeatedly solve Kepler's equation at arbitrary epochs is eliminated. Furthermore, a propellant constraint is imposed on the high-thrust mode to activate the multi-mode capabi…

Dynamic Redeployment of Nurses Across Hospitals: A Sample Robust Optimization Approach
Wei Liu, Tianchun Li, Mengshi Lu, Pengyi Shi
https://arxiv.org/abs/2509.07387 https://

Dynamic Redeployment of Nurses Across Hospitals: A Sample Robust Optimization Approach
Problem definition: We study a workforce redeployment problem in hospital networks, where clinical staff, such as nurses, are temporarily reassigned from overstaffed to understaffed sites to address short-term imbalances. This practice of ``internal travel,'' which gained traction during the COVID-19 pandemic to tackle nurse shortages, presents new operational challenges that require tailored analytical support. Key requirements such as advance notice and short-term secondments must be incorpor…

Hearing the Shape of a Cuboid Room Using Sparse Measure Recovery
Antoine Deleforge (MACARON, IRMA), C\'edric Foy (Cerema, UMRAE), Yannick Privat (IECL, SPHINX, IUF), Tom Sprunck (CEA, MACARON)
https://arxiv.org/abs/2509.08443

Hearing the Shape of a Cuboid Room Using Sparse Measure Recovery
This article explores a variant of Kac's famous problem, "Can one hear the shape of a drum?", by addressing a geometric inverse problem in acoustics. Our objective is to reconstruct the shape of a cuboid room using acoustic signals measured by microphones placed within the room. By examining this straightforward configuration, we aim to understand the relationship between the acoustic signals propagating in a room and its geometry. This geometric problem can be reduced to locating a finite set …

Bregman Douglas-Rachford Splitting Method
Shiqian Ma, Lin Xiao, Renbo Zhao
https://arxiv.org/abs/2509.08739 https://arxiv.org/pdf/2509.08739

Bregman Douglas-Rachford Splitting Method
In this paper, we propose the Bregman Douglas-Rachford splitting (BDRS) method and its variant Bregman Peaceman-Rachford splitting method for solving maximal monotone inclusion problem. We show that BDRS is equivalent to a Bregman alternating direction method of multipliers (ADMM) when applied to the dual of the problem. A special case of the Bregman ADMM is an alternating direction version of the exponential multiplier method. To the best of our knowledge, algorithms proposed in this paper are…

Data-Driven Density Steering via the Gromov-Wasserstein Optimal Transport Distance
Haruto Nakashima, Siddhartha Ganguly, Kenji Kashima
https://arxiv.org/abs/2508.06052 https://

Data-Driven Density Steering via the Gromov-Wasserstein Optimal Transport Distance
We tackle the data-driven chance-constrained density steering problem using the Gromov-Wasserstein metric. The underlying dynamical system is an unknown linear controlled recursion, with the assumption that sufficiently rich input-output data from pre-operational experiments are available. The initial state is modeled as a Gaussian mixture, while the terminal state is required to match a specified Gaussian distribution. We reformulate the resulting optimal control problem as a difference-of-con…